Internet of things

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pages: 322 words: 84,752

Pax Technica: How the Internet of Things May Set Us Free or Lock Us Up by Philip N. Howard

Affordable Care Act / Obamacare, Berlin Wall, bitcoin, blood diamonds, Bretton Woods, Brian Krebs, British Empire, butter production in bangladesh, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, corporate social responsibility, creative destruction, crowdsourcing, digital map, Edward Snowden, en.wikipedia.org, failed state, Fall of the Berlin Wall, feminist movement, Filter Bubble, Firefox, Francis Fukuyama: the end of history, Google Earth, Howard Rheingold, income inequality, informal economy, Internet of things, Julian Assange, Kibera, Kickstarter, land reform, M-Pesa, Marshall McLuhan, megacity, Mikhail Gorbachev, mobile money, Mohammed Bouazizi, national security letter, Nelson Mandela, Network effects, obamacare, Occupy movement, packet switching, pension reform, prediction markets, sentiment analysis, Silicon Valley, Skype, spectrum auction, statistical model, Stuxnet, trade route, undersea cable, uranium enrichment, WikiLeaks, zero day

Moreover, there’s no guarantee that you will have access to the data about your behavior. Putting the Civic into the Internet of Things, Domestically In this day and age, you either set the technology standards or you follow them. Many brilliant civic projects provide governance through the open, considered, and deliberate use of the internet. So we need an internet of things that allows expression and experimentation. Brett Frischmann makes this same argument in Infrastructure: all public works like the internet of things should be open and nondiscriminatory.25 We need to make sure the internet of things is designed for civic engagement. These days, it’s normal for civil-society groups to have an internet strategy or a social-media strategy. Are such groups ready with a strategy for the internet of things? Authoritarian regimes and unscrupulous politicians who stay in character will throw bots into the internet to obscure issues and muddy public opinion.

In the second chapter, I analyze the important developments in technology and politics during what I call the internet interregnum: the period after the collapse of the Soviet Union in which our internet grew from a network of computers into a network of mobile phones. The next internet, the internet of things, is going to allow us to draw even more nuanced maps of the most meaningful social networks. In the third chapter I map out some of the new relationships among people, data, and the internet of things. Chapter four moves from observations and examples to the conservative generalizations we can make about technology diffusion and political communication. In this chapter I offer five basic premises about how we use the internet in politics, and it is important because these premises render the likely consequences of the internet of things. In the fifth chapter I explore five reasonable political consequences of the emerging world order, this pax technica. What are the political consequences of an internet of things? The pax technica is not a guarantee of peace so much as a sociotechnical structure for political life, and in the sixth chapter I identify the major challenges to the stability of the evolving internet of things.

We are entering a period of global political life that will be profoundly shaped by how political actors use the internet of things. Indeed, the internet of things will define, express, and contain this period. The capacities and constraints of political life have often been shaped by technological innovation—and vice versa. Technology and politics have an impact on each other and on how current events and future prospects should be situated in the context of the recent past. More devices come online each month, and progressively more people are connected through these digital networks. Now almost every aspect of human security depends on digital media and this internet of things. Responsibility for creating this internet of things still rests with all of us. We use social media, and few of us are diligent about maintaining our privacy.


pages: 138 words: 40,787

The Silent Intelligence: The Internet of Things by Daniel Kellmereit, Daniel Obodovski

Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, connected car, crowdsourcing, data acquisition, en.wikipedia.org, Erik Brynjolfsson, first square of the chessboard, first square of the chessboard / second half of the chessboard, Freestyle chess, Google X / Alphabet X, Internet of things, lifelogging, Metcalfe’s law, Network effects, Paul Graham, Ray Kurzweil, RFID, Robert Metcalfe, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

Chapter 3 looks into the future of M2M and the Internet of Things and focuses on what this brave new world may look like. We ask some provocative questions: What role will humans play when a lot of decision-making is done by machines, and might humans ever become a bottleneck to realizing the Internet of Things vision? We also take a peek at what the ubiquitous connectivity between various devices may look like in real terms. Chapter 4 is dedicated to the core industries of M2M. We picked connected cities, connected homes, connected health care, and connected cars. While these areas do not cover all the aspects of M2M (not even close), they do offer great examples of the impact Machine-to-Machine technology will have. We also hope this overview will help readers discover new areas for M2M and the Internet of Things on their own.

~ Bill Gates We made a point in chapter 1 that the exponential growth of the Internet of Things is going to have a profound effect on our lives over the next five to ten years. If we are correct, the quote above that opens Bill Gates’s book Business @ the Speed of Thought: Succeeding in the Digital Economy,15 written over a decade ago, seems to be more relevant today than ever. However, we decided to start this chapter with a provocative question: Will humans ever become a decision bottleneck in the Internet of Things? Considering how much decision-making ability has already been given to machines and how much more is going to go that way, and considering the speed at which information flows from sensors and devices to the cloud, will humans be able to comprehend? Are humans the major limiting factor in the development of the Internet of Things today? And, more importantly, will humans be able to cope with all this information?

CONCLUSION You have just finished reading The Silent Intelligence: The Internet of Things, a book that took us more than a year and a half to write. Quite a few things have changed in that time because the space has been growing so fast. Some of the things we viewed as hypotheses at the beginning became proven, companies merged, new entrants came in, and there have also been several successful exits for investors in this space. All these events point to the rapid growth of the Internet of Things, as more opportunities emerge and more companies jump on the M2M bandwagon. M2M is impossible to deny or ignore — it’s here to stay, and it will change our lives and the ways we do business in more profound ways than we can even imagine today. The impact of the Internet of Things will be comparable to that of the Web in the ’90s, but some think it will be more like the impact of the Industrial Revolution.


Industry 4.0: The Industrial Internet of Things by Alasdair Gilchrist

3D printing, additive manufacturing, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, business intelligence, business process, chief data officer, cloud computing, connected car, cyber-physical system, deindustrialization, DevOps, digital twin, fault tolerance, global value chain, Google Glasses, hiring and firing, industrial robot, inflight wifi, Infrastructure as a Service, Internet of things, inventory management, job automation, low cost airline, low skilled workers, microservices, millennium bug, pattern recognition, peer-to-peer, platform as a service, pre–internet, race to the bottom, RFID, Skype, smart cities, smart grid, smart meter, smart transportation, software as a service, stealth mode startup, supply-chain management, trade route, undersea cable, web application, WebRTC, Y2K

Industry 4.0 The Industrial Internet of Things ― Alasdair Gilchrist INDUSTRY 4.0 THE INDUSTRIAL INTERNET OF THINGS Alasdair Gilchrist Industry 4.0: The Industrial Internet of Things Alasdair Gilchrist Bangken, Nonthaburi Thailand ISBN-13 (pbk): 978-1-4842-2046-7 ISBN-13 (electronic): 978-1-4842-2047-4 DOI 10.1007/978-1-4842-2047-4 Library of Congress Control Number: 2016945031 Copyright © 2016 by Alasdair Gilchrist This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.

However this book focuses on the largest vertical © Alasdair Gilchrist 2016 A. Gilchrist, Industry 4.0, DOI 10.1007/978-1-4842-2047-4_1 2 Chapter 1 | Introduction to the Industrial Internet of them all, the Industrial Internet of Things, which encompasses a vast amount of disciplines such as energy production, manufacturing, agriculture, health care, retail, transportation, logistics, aviation, space travel and many more. Figure 1-1. Horizontal and vertical aspects of the Internet of Things In this book to avoid confusion we will follow GE’s lead and use the name Industrial Internet of Things (IIoT) as a generic term except where we are dealing with conceptually and strategically different paradigms, in which case it will be explicitly referred to by its name, such as Industry 4.0. Many industrial leaders forecast that the Industrial Internet will deliver unprecedented levels of growth and productivity over the next decade.

ICS, 185 PCL and DCS, 187–188 physical and behavioral security, 186 ping devices, 185 PLC, 183 Profibus, and Profinet, 189 system level, 190 VHF radio equipment, 192 VLAN network, 189 Y2K bug, 185 smartphones, 45 Ukraine power, 180 Wireless communication technology, 38 Industrial Internet. See Industrial internet of things (IIoT) Industrial operations technology (IOT), 1–2, 183 Industrial internet architecture framework (IIAF), 67 Industrial internet consortium (IIC), 66 Industrial internet of things (IIoT) B2C, 2 Big Data, 3, 5 building’s energy efficiency, 20 business gains, 3 catalysts and precursors adequately skilled and trained staff, 6 innovation, commitment to, 6 security, 7 cloud-computing model, 6 commercial market, 1 consumer market, 1 digital and human workforce, 11 digital twin, 11 green house gas emissions, 19 heath care, 14 Industry 4.0, 2 innovation, 7 installing sensors and actuators, 20 intelligent devices, 8 IOT, 1–2 IOT, disadvantages, 20 247 248 Index Industrial internet of things (IIoT) (cont.) IOT6 Smart Office, 21 IT sectors, 5 key opportunities and benefits, 8 logistics adopting sensor technologies, 24 advanced telemetric sensors, 26 augmented reality glasses, 25 automating stock control task, 24 barcode technology, 23 Big Data, 26–27 document scanning and verification, 26 forklift, 24–25 Google Glass, 25 multiple sensors, 26 pick-by-paper, 25 RFID, 23–24 SmartLIFT technology, 24–25 temperature and humidity sensors, 24 track and trace, 26 M2M, 3 manufacturers, 10 Oil and Gas industry automated remote control topology, 18 automation, 18 Big Data analytics, 19 cloud computing, 17 data analytics, 16 data collection and analysis, 18 data distribution system, 17 DDS bus, 18 down-hole sensors, 16 drilling and exploration, 16 industry regulations, 16 intelligent real-time reservoir management, 19 interconnectivity, 17 MQPP and XMPP, 17 remote node's status, 17 6LoWLAN and CoAP, 17 technological advances, 16 wireless technologies and protocols, 17 outcome economy, 10 power of 1%, 4 retailer innovations, 29 IT costs, 27 POS, 27–28 real-time reporting and visibility, 28 stock control, 28 sensor technology, 4 smartphone, 20 WSN, 21 WWAN, 5 Industrial Internet system communication protocols Ethernet protocol, 100 industrial Ethernet, 98 TCP/UDP containers, 100 concept of, IIoT, 88 diverse technology, 116 gateways, 115 heterogeneous networks, 116 industrial gateway, 118 industrial protocols current loop, 97 field bus technology, 98 RS232 serial communications, 96 proximity and access network address types, 114 IIoT context, 115 IPv4, 109 IPv6, 112 IPv6 Subnets, 114 NAT, 111 proximity network, 89 wireless communication technology, 102 bluetooth low energy, 103 IEEE 802.15.4, 102 NFC, 107 RFID, 106 RPL, 108 6LoWPAN, 107 Thread, 107 Wi-Fi backscatter, 105 ZigBee, 103 ZigBee IP, 104 Z-Wave, 105 WSN edge node, 90 functional layers, 93 IP layers vs.


pages: 565 words: 151,129

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism by Jeremy Rifkin

"Robert Solow", 3D printing, active measures, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, big-box store, bioinformatics, bitcoin, business process, Chris Urmson, clean water, cleantech, cloud computing, collaborative consumption, collaborative economy, Community Supported Agriculture, Computer Numeric Control, computer vision, crowdsourcing, demographic transition, distributed generation, en.wikipedia.org, Frederick Winslow Taylor, global supply chain, global village, Hacker Ethic, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, longitudinal study, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, mass immigration, means of production, meta analysis, meta-analysis, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, off grid, oil shale / tar sands, pattern recognition, peer-to-peer, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, QR code, RAND corporation, randomized controlled trial, Ray Kurzweil, RFID, Richard Stallman, risk/return, Ronald Coase, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transaction costs, urban planning, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, zero-sum game, Zipcar

The coming together of the Communications Internet with the fledgling Energy Internet and Logistics Internet in a seamless twenty-first-century intelligent infrastructure—the Internet of Things (IoT)—is giving rise to a Third Industrial Revolution. The Internet of Things is already boosting productivity to the point where the marginal cost of producing many goods and services is nearly zero, making them practically free. The result is corporate profits are beginning to dry up, property rights are weakening, and an economy based on scarcity is slowly giving way to an economy of abundance. The Internet of Things The Internet of Things will connect every thing with everyone in an integrated global network. People, machines, natural resources, production lines, logistics networks, consumption habits, recycling flows, and virtually every other aspect of economic and social life will be linked via sensors and software to the IoT platform, continually feeding Big Data to every node—businesses, homes, vehicles—moment to moment, in real time.

Evans and Marco Annunziata, “Industrial Internet: Pushing the Boundaries of Minds and Machines,” General Electric, November 26, 2012, http://www.ge.com/sites/default/files /Industrial_Internet.pdf, 4 (accessed January 5, 2013). 14. Ibid., 24. 15. “The Internet of Things Business Index: A Quiet Revolution Gathers Pace,” The Economist Intelligence Unit (2013), 10, http://www.arm.com/files/pdf/EIU_Internet_Business_Index_WEB .PDF (accessed October 29, 2013). 16. Ibid. 17. “The Difference Engine: Chattering Objects,” Economist (August 13, 2010), http://www.econo mist.com/blogs/babbage/2010/08/internet_things (accessed September 5, 2013). 18. Ibid. 19. Ibid. 20. Ibid. 21. “Conclusions of the Internet of Things Public Consultation,” Digital Agenda for Europe, A Europe 2020 Initiative, February 28, 2013, http://ec.europa.eu/digital-agenda/en/news/conclu sions-internet-things-public-consultation (accessed March 21, 2013). 22. “Internet of Things Factsheet Privacy and Security: IoT Privacy, Data Protection, Information Security,” Digital Agenda for Europe, A Europe 2020 Initiative (February 28, 2013): 1, http://ec.europa.eu/digital-agenda/en/news/conclusions-internet-things-public-consultation (accessed March 21. 2013). 23.

Big Data, in turn, will be processed with advanced analytics, transformed into predictive algorithms, and programmed into automated systems to improve thermodynamic efficiencies, dramatically increase productivity, and reduce the marginal cost of producing and delivering a full range of goods and services to near zero across the entire economy. The Internet of Things European Research Cluster, a body set up by the European Commission, the executive body of the European Union, to help facilitate the transition into the new era of “ubiquitous computing,” has mapped out some of the myriad ways the Internet of Things is already being deployed to connect the planet in a distributed global network. The IoT is being introduced across industrial and commercial sectors. Companies are installing sensors all along the commercial corridor to monitor and track the flow of goods and services.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Charles Lindbergh, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, global pandemic, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Joi Ito, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, low earth orbit, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Ross Ulbricht, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

Smith, “Most ‘Hackable’ Vehicles Are Jeep, Escalade, Infiniti, and Prius,” Network World, Aug. 3, 2014. 36 In a nod: Ina Fried, “Tesla Hires Hacker Kristin Paget to, Well, Secure Some Things,” Re/code, Feb. 7, 2014. 37 “expected to reach”: Transparency Market Research, “Home Automation Market (Lighting, Safety and Security, Entertainment, HVAC, Energy Management)—Global Industry Analysis, Size, Share, Growth, Tends, and Forecast, 2013–2019,” Sept. 30, 2013. 38 Many such systems: Kashmir Hill, “When ‘Smart Homes’ Get Hacked: I Haunted a Complete Stranger’s House via the Internet,” Forbes, July 26, 2013. 39 A July 2014 study: Daniel Miessler, “HP Study Reveals 70 Percent of Internet of Things Devices Vulnerable to Attack,” HP, July 29, 2014. 40 Major toy makers: Arrayent, “Internet of Things Toys with Mattel,” http://​www.​arrayent.​com/​internet-​of-​things-​case-​studies/​connecting-​toys-​with-​mattet/​Disney Research, “CALIPSO: Internet of Things.” http://​www.​disneyresearch.​com/​project/​calipso-​internet-​of-​things/. 41 But toys too can be subverted: Heather Kelly, “ ‘Smart Homes’ Are Vulnerable, Say Hackers,” CNN, Aug. 2, 2013. 42 They allow hackers to turn off: Dan Goodin, “Welcome to the ‘Internet of Things,’ Where Even Lights Aren’t Hacker Safe,” Ars Technica, Aug. 13, 2013. 43 Additional systems: Jane Wakefield, “Experts Hack Smart LED Light Bulbs,” BBC News, July 8, 2014; Leo King, “Smart Home?

Indeed, one such firm, the smartthermostat company Nest Labs, was acquired in 2014 for an astounding $3.2 billion just 854 days after the launch of its first product. And while there is undoubtedly big money to be made in the IoT, its social implications may even outstrip its economic impact. Imagining the Internet of Things The Internet of Things is a way of saying that more of the world will become part of the network … We are assimilating more and more of the world into the computer. GORDON BELL, MICROSOFT RESEARCHER The promise of the Internet of Things sounds rosy. Because chips and sensors will be embedded in everyday objects, we will have much better information and convenience in our lives. So, for example, because your alarm clock is connected to the Internet, it will be able to access and read your calendar. It will know where and when your first appointment of the day is and be able to cross-reference that information against the latest traffic conditions.

Given our inability to secure today’s global information matrix, how might we ever protect a world in which every physical object, from pets to pacemakers to self-driving cars, is connected to the Net and hackable from anywhere on the planet? The obvious reality is that we cannot. The Internet of Things will become nothing more than the Internet of Things to be hacked, a cornucopia of malicious opportunity for those with the means and motivation to exploit our common technological insecurity. The IoT and its underlying insecure protocols will open a Pandora’s box of security vulnerabilities on an unprecedented scale, potentially creating systemic malfunctions whose reach will be simultaneously unpredictable, extraordinary, and terrifying. Houston, we have a problem, particularly with our threat surface area—that is to say, the sum of the different points or attack vectors through which an enemy can strike. The challenge with the Internet of Things is that our technological threat surface area is growing exponentially and simply stated we have no idea how to defend it effectively.


pages: 448 words: 117,325

Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World by Bruce Schneier

23andMe, 3D printing, autonomous vehicles, barriers to entry, bitcoin, blockchain, Brian Krebs, business process, cloud computing, cognitive bias, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, Donald Trump, drone strike, Edward Snowden, Elon Musk, fault tolerance, Firefox, Flash crash, George Akerlof, industrial robot, information asymmetry, Internet of things, invention of radio, job automation, job satisfaction, John Markoff, Kevin Kelly, license plate recognition, loose coupling, market design, medical malpractice, Minecraft, MITM: man-in-the-middle, move fast and break things, move fast and break things, national security letter, Network effects, pattern recognition, profit maximization, Ralph Nader, RAND corporation, ransomware, Rodney Brooks, Ross Ulbricht, security theater, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart transportation, Snapchat, Stanislav Petrov, Stephen Hawking, Stuxnet, The Market for Lemons, too big to fail, Uber for X, Unsafe at Any Speed, uranium enrichment, Valery Gerasimov, web application, WikiLeaks, zero day

One of the premises of this book is that the Internet is a singular connected network—that any part of it can affect any other part of it—and needs to be viewed in this way to properly talk about security. 5“the network of physical objects”: Gartner (accessed 24 Apr 2018), “Internet of Things,” Gartner IT Glossary, https://www.gartner.com/it-glossary/internet-of-things. 5In 2017, there were 8.4 billion things: Gartner (7 Feb 2017), “Gartner says 8.4 billion connected ‘things’ will be in use in 2017, up 31 percent from 2016,” https://www.gartner.com/newsroom/id/3598917. 5By 2020, there are likely to be: Tony Danova (2 Oct 2013), “Morgan Stanley: 75 billion devices will be connected to the Internet of Things by 2020,” Business Insider, http://www.businessinsider.com/75-billion-devices-will-be-connected-to-the-internet-by-2020-2013-10. Peter Brown (25 Jan 2017), “20 billion connected Internet of Things devices in 2017, IHS Markit says,” Electronics 360, http://electronics360.globalspec.com/article/8032/20-billion-connected-internet-of-things-devices-in-2017-ihs-markit-says. Julia Boorstin (1 Feb 2016), “An Internet of Things that will number ten billions,” CNBC, https://www.cnbc.com/2016/02/01/an-internet-of-things-that-will-number-ten-billions.html.

There are advantages to computerizing everything—some that we can see today, and some that we’ll realize only once these computers have reached critical mass. The Internet of Things will embed itself into our lives at every level, and I don’t think we can predict the emergent properties of this trend. We’re reaching a fundamental shift that is due to scale and scope; these differences in degree are causing a difference in kind. Everything is becoming one complex hyper-connected system in which, even if things don’t interoperate, they’re on the same network and affect each other. There is more to this trend than the Internet of Things. Take the Internet of Things. Start with the IoT or, more generally, cyberphysical systems. Add the miniaturization of sensors, controllers, and transmitters. Then add autonomous algorithms, machine learning, and artificial intelligence.

Julia Boorstin (1 Feb 2016), “An Internet of Things that will number ten billions,” CNBC, https://www.cnbc.com/2016/02/01/an-internet-of-things-that-will-number-ten-billions.html. Statista (2018), “Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025 (in billions),” https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide. 6your T-shirt someday will: Michael Sawh (26 Sep 2017), “The best smart clothing: From biometric shirts to contactless payment jackets,” Wareable, https://www.wareable.com/smart-clothing/best-smart-clothing. 6“The ‘Smart Everything’ Trend”: J. R. Raphael (7 Jan 2016), “The ‘smart’-everything trend has officially turned stupid,” Computerworld, http://www.computerworld.com/article/3019713/internet-of-things/smart-everything-trend.html. 7It’s an Internet that senses: Something that senses, plans, and acts is the classic definition of a robot.


pages: 181 words: 52,147

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, distributed ledger, Donald Trump, double helix, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Google bus, Hyperloop, income inequality, Internet of things, job automation, Kevin Kelly, Khan Academy, Kickstarter, Law of Accelerating Returns, license plate recognition, life extension, longitudinal study, Lyft, M-Pesa, Menlo Park, microbiome, mobile money, new economy, personalized medicine, phenotype, precision agriculture, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, Tesla Model S, The Future of Employment, Thomas Davenport, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

Since designing its thermostat, Nest, which operates as an autonomous unit inside Google, has released a smoke detector and a video camera to monitor for intruders or behavior of pets (and perhaps children or teenagers?). It will probably release many new products, all controllable from the Nest application. Technology companies say they will use the Internet of Things in the same way: to reduce our energy usage, improve our health, make us more secure, and nudge us toward better lifestyles. Of course, the I.o.T., they say, will save us money too. The ability to collect such data will have a profound effect on the economy. The McKinsey Global Institute, in a report titled The Internet of Things: Mapping the Value beyond the Hype, says that the economic impact of the Internet of Things could be $3.9 to $11.1 trillion per year by 2025: up to 11 percent of the global economy.2 Much of the value of the I.o.T. is hard for us to comprehend, because it will be machines talking to other machines to enable different A.I. systems to work together and make better decisions.

And there will have to be a loss of autonomy for the drivers because we will ultimately have to take this away—they are too moody and dangerous. They will become the drivers in the driverless car. 13 When Your Scale Talks to Your Refrigerator: The Internet of Things Your refrigerator will talk to your toothbrush, your gym shoes, your car, and your bathroom scale. They will all have a direct line to your smartphone and tell your digital doctor whether you have been eating right, exercising, brushing your teeth, or driving too fast. I have no idea what they will think of us or gossip about; but I know that many more of our electronic devices will soon be sharing information about us—with each other and with the companies that make or support them. The Internet of Things (I.o.T.) is a fancy name for the increasing array of sensors embedded in our commonly used appliances and electronic devices, our vehicles, our homes, our offices, and our public places.

It will help us learn from our behaviors, manage our environment, and live a richer life. But there is a really dark side to this machine vigilance. The Internet of Things will offer unprecedented spying possibilities, from the insurance company monitoring how you drive by using an accelerometer device in your car (which insurance giant Generali is already doing, under a scheme it calls Pago como Conduzco, “Pay as I Drive”1) to the little Samsung Paddle placed under your pillow that records your sleep cycles and vital signs, to the camera in your TV that gets hacked and allows people to watch you. The possibilities for unhealthy and potentially illegal invasions of privacy grow along with the growth of the I.o.T. The Awesome Things about the Internet of Things The smash-hit Nest home thermostat may surprise you. What could be more boring and mundane than a thermostat, right?


pages: 230 words: 61,702

The Internet of Us: Knowing More and Understanding Less in the Age of Big Data by Michael P. Lynch

Affordable Care Act / Obamacare, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bitcoin, Cass Sunstein, Claude Shannon: information theory, crowdsourcing, Edward Snowden, Firefox, Google Glasses, hive mind, income inequality, Internet of things, John von Neumann, meta analysis, meta-analysis, Nate Silver, new economy, Panopticon Jeremy Bentham, patient HM, prediction markets, RFID, sharing economy, Steve Jobs, Steven Levy, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, WikiLeaks

As Sue Halpern, an astute observer of the digital age, remarks: “The Internet of Things creates the perfect conditions to bolster and expand the surveillance state. In the world of the Internet of Things, your car, your heating system, your refrigerator, your fitness apps, your credit card, your television set, your window shades, your scale, your medications, your camera, your heart rate monitor, your electric toothbrush, and your washing machine—to say nothing of your phone—generate a continuous stream of data that resides largely out of reach of the individual but not of those willing to pay for it or in other ways commandeer it.”13 Earlier I noted there are two marks to information privacy: control and protection. Control over our information may be increasingly under threat by the Internet of Things. But that only makes concentrating on restricting and regulating information flow all the more important.

Internet wonks tend to think that we are seeing the arrival of the “third wave” of the Internet. First there was Web 1.0 (the ancient days of “Wow! You should check out this email thing!”). Then, starting in the early 2000s, there was Web 2.0. (“Wow! You should check out this Facebook thing!”). Now we have Web 3.0 (the “smart Web”) and, most significantly, the so-called Internet of Things (“Wow! You should check out my smart … watch, refrigerator, lamp, socks!”). In essence, the “Internet of Things” is a way of describing the phenomenon of networked objects—objects that are embedded with data-streaming sensors and software that connect them to the Net. The “things” in question run the gamut from autonomous connected devices like smartphones to the tiny radio-frequency identification (RFID) microchips and other sorts of sensors attached to everything from UPS trucks and cargo containers to pets, farm animals, cars, thermostats, and NFL helmets.

By 2007 there were already 10 million sensors of all sorts connected to the Internet, and some projections have that number rising to 100 trillion by 2030 if not before.4 These sensors are being used not only for economic purposes but for scientific ones (to track migratory animals, for example), and for security and military purposes (such as tracking human beings). According to Jeremy Rifkin, a leading economist of the digital world, the Internet of Things is even giving rise to a “Third Industrial Revolution,” precipitating huge changes in how human beings around the globe interact with one another, economically and otherwise.5 The Internet of Things is made possible by—and is also producing—big data. The term “big data” has no fixed definition, but rather three connected uses. First, it names the ever-expanding volume of data that surrounds us. You’ve heard some of the statistics. As long ago as 2009, there were already 260 million page views per month on Facebook; in 2012, there were 2.7 billion likes per day.


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, disruptive innovation, distributed ledger, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce

It seems strange to assert that anything as broad as a class of technologies might have a dominant emotional tenor, but the internet of things does. That tenor is sadness. When we pause to listen for it, the overriding emotion of the internet of things is a melancholy that rolls off of it in waves and sheets. The entire pretext on which it depends is a milieu of continuously shattered attention, of overloaded awareness, and of gaps between people just barely annealed with sensors, APIs and scripts. Implicit in its propositions is a vision of inner states and home lives alike savaged by bullshit jobs, overcranked schedules and long commutes, of intimacy stifled by exhaustion and the incapacity or unwillingness to be emotionally present. The internet of things in all of its manifestations so often seems like an attempt to paper over the voids between us, or slap a quick technical patch on all the places where capital has left us unable to care for one another.

The arrangements through which we allocate resources, transact value, seek to exert form on the material world, share our stories with one another, and organize ourselves into communities and polities will from now on draw upon a fundamentally new set of concepts and practices, and this is a horizon of possibilities that first opened up to us in equipping ourselves with the smartphone. 2 The internet of things A planetary mesh of perception and response In Copenhagen, a bus running two minutes behind schedule transmits its location and passenger count to the municipal traffic signal network, which extends the green light at each of the next three intersections long enough for its driver to make up some time. In Davao City in the Philippines, an unsecured webcam overlooks the storeroom of a fast-food stand, allowing anyone equipped with its address to peer in at will on all its comings and goings. In San Francisco, a young engineer hopes to “optimize” his life through sensors that track his heart rate, respiration and sleep cycle. What links these wildly different circumstances is a vision of connected devices now being sold to us as the “internet of things,” in which a weave of networked perception wraps every space, every place, every thing and every body on Earth.

The technologist Mike Kuniavsky, a pioneer and early proponent of this vision, characterizes it as a state of being in which “computation and data communication [are] embedded in, and distributed through, our entire environment.”1 I prefer to see it for what it is: the colonization of everyday life by information processing. Like the smartphone, the internet of things isn’t a single technology, but an unruly assemblage of protocols, sensing regimes, capabilities and desires, all swept under a single rubric for the sake of disciplinary convenience. Just about all that connects the various devices, services, vendors and efforts involved is the ambition to raise awareness of some everyday circumstance to the network for analysis and response. Though it can often feel as if this colonization proceeds of its own momentum, without any obvious driver or particularly pressing justification beyond the fact that it is something our technology now makes possible, it always pays to remember that distinct ambitions are being served wherever and however the internet of things appears, whether as rhetoric or reality.


pages: 116 words: 31,356

Platform Capitalism by Nick Srnicek

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative economy, collective bargaining, deindustrialization, deskilling, disintermediation, future of work, gig economy, Infrastructure as a Service, Internet of things, Jean Tirole, Jeff Bezos, knowledge economy, knowledge worker, liquidity trap, low skilled workers, Lyft, Mark Zuckerberg, means of production, mittelstand, multi-sided market, natural language processing, Network effects, new economy, Oculus Rift, offshore financial centre, pattern recognition, platform as a service, quantitative easing, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, software as a service, TaskRabbit, the built environment, total factor productivity, two-sided market, Uber and Lyft, Uber for X, uber lyft, unconventional monetary instruments, unorthodox policies, Zipcar

Network effects are, as always, essential to gaining a monopoly position, and this openness enables them to incorporate more and more users. These platforms already are strong revenue sources for the companies: Predix currently brings GE $5 billion and is expected to triple this revenue by 2020.49 Predictions are that the sector will be worth $225 billion by 2020 – more than both the consumer internet of things and enterprise cloud computing.50 Nevertheless, demonstrating the power of monopolies, GE continues to use AWS for its internal needs.51 Product Platforms Importantly, the preceding developments – particularly the internet of things and cloud computing – have enabled a new type of on-demand platform. They are two closely related but distinct business models: the product platform and the lean platform. Take, for example, Uber and Zipcar – both platforms designed for consumers who wish to rent some asset for a time.

Brenner, Robert, and Mark Glick. 1991. ‘The Regulation Approach: Theory and History’. New Left Review, 188: 45–119. ‘Britain’s Lonely High-Flier’ (Editor’s Note). 2009. The Economist, 8 January. http://www.economist.com/node/12887368 (accessed 4 June 2016). Bughin, Jacques, Michael Chui, and James Manyika. 2015. ‘An Executive’s Guide to the Internet of Things’. McKinsey&Company.August.http://www.mckinsey.com/business-functions/business-technology/our-insights/an-executives-guide-to-the-internet-of-things (accessed 4 June 2016). Burrington, Ingrid. 2016. ‘Why Amazon’s Data Centers Are Hidden in Spy Country’. The Atlantic, 8 January. http://www.theatlantic.com/technology/archive/2016/01/amazon-web-services-data-center/423147 (accessed 4 June 2016). Burson-Marsteller. 2016. ‘Net Display Ad Revenues Worldwide, by Company, 2014–2016’. https://pbs.twimg.com/media/Chsi8ZwUgAA-NnG.jpg (accessed 4 June 2016).

TechCrunch, 26 May. https://techcrunch.com/2016/05/26/microsoft-and-facebook-are-building-the-fastest-trans-atlantic-cable-yet (accessed 30 June 2016). Levine, Dan, and Heather Somerville. 2016. ‘Uber Drivers, if Employees, Owed $730 Million More: US Court Papers’. Reuters. 10 May. http://www.reuters.com/article/us-uber-tech-driverslawsuit-idUSKCN0Y02E8 (accessed 22 May 2016). Löffler, Markus, and Andreas Tschiesner. 2013. ‘The Internet of Things and the Future of Manufacturing’. McKinsey & Company. http://www.mckinsey.com/insights/business_technology/the_internet_of_things_and_the_future_of_manufacturing (accessed 22 May 2016). Manyika, James, Susan Lund, Kelsey Robinson, John Valentino, and Richard Dobbs. 2015. ‘A Labor Market That Works: Connecting Talent with Opportunity in the Digital Age’. McKinsey Global Institute. http://www.mckinsey.com/global-themes/employment-and-growth/connecting-talent-with-opportunity-in-the-digital-age (accessed 22 May 2016).


pages: 327 words: 84,627

The Green New Deal: Why the Fossil Fuel Civilization Will Collapse by 2028, and the Bold Economic Plan to Save Life on Earth by Jeremy Rifkin

1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, American Society of Civil Engineers: Report Card, autonomous vehicles, Bernie Sanders, blockchain, borderless world, business cycle, business process, carbon footprint, collective bargaining, corporate governance, corporate social responsibility, creative destruction, decarbonisation, en.wikipedia.org, energy transition, failed state, ghettoisation, hydrogen economy, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, Joseph Schumpeter, means of production, megacity, Network effects, new economy, off grid, oil shale / tar sands, peak oil, planetary scale, renewable energy credits, Ronald Reagan, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, sovereign wealth fund, Steven Levy, the built environment, The Wealth of Nations by Adam Smith, Tim Cook: Apple, trade route, union organizing, urban planning, women in the workforce, zero-sum game

Only after sealing the building envelope to make it more energy efficient can the smart IoT infrastructure be embedded, transforming the building into a smart node, ready to engage its neighbors locally and globally in collective endeavors. Early on, the Internet of Things was viewed more as an ancillary aid to industries to help them increase their surveillance of equipment and improve performance across assembly lines and supply chains—for example, embedding sensors in airplanes that could alert a company when a component needed to be replaced before standard maintenance checkups. While the term “Internet of Things” was coined by Kevin Ashton back in 1999, the prospects for its widespread application remained unexplored for another thirteen years because of the high cost of sensors and actuators. Then, in an eighteen-month period in 2012 and 2013, the cost of radiofrequency identification chips used to monitor and track things plummeted by 40 percent, opening up the possibility of embedding sensors across the whole of society.35 A year later, in 2014, our office published The Zero Marginal Cost Society, suggesting that the IoT has a far more important role to play by becoming a smart nervous system to improve commercial and social life.36 We argued that the IoT’s ultimate application would be to embed it within and across the residential, commercial, industrial, and institutional building stock.

Willis Towers Watson, Thinking Ahead Institute, Global Pension Assets Study 2018, https://www.thinkingaheadinstitute.org/en/Library/Public/Research-and-Ideas/2018/02/Global-Pension-Asset-Survey-2018 (accessed April 5, 2019), 9. 24.  “1,000+ Divestment Commitments,” Fossil Free, https://gofossilfree.org/divestment/commitments/ (accessed March 15, 2019). CHAPTER 1   1.  Brian Merchant, “With a Trillion Sensors, the Internet of Things Would Be the ‘Biggest Business in the History of Electronics,’” Motherboard, October 29, 2013, https://motherboard.vice.com/en_us/article/8qx4gz/the-internet-of-things-could-be-the-biggest-business-in-the-history-of-electronics (accessed February 6, 2019).   2.  “Wikipedia.org Traffic Statistics,” Alexa, https://www.alexa.com/siteinfo/wikipedia.org (accessed February 6, 2019).   3.  Robert U. Ayres and Benjamin Warr, The Economic Growth Engine: How Energy and Work Drive Material Prosperity (Northampton, MA: Edward Elgar Publishing, 2009), 334–37; John A.

“Questions and Answers: Energy Efficiency Tips for Buildings and Heating,” Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (Germany), https://www.bmu.de/en/topics/climate-energy/energy-efficiency/buildings/questions-and-answers-energy-efficiency-tips-for-buildings-and-heating/ (accessed February 1, 2019); John Calvert and Kaylin Woods, “Climate Change, Construction and Labour in Europe: A Study of the Contribution of Building Workers and Their Unions to ‘Greening’ the Built Environment in Germany, the United Kingdom and Denmark,” paper presented at the Work in a Warming World (W3) Researchers’ Workshop “Greening Work in a Chilly Climate,” Toronto, November 2011, http://warming.apps01.yorku.ca/wp-content/uploads/WP_2011-04_Calvert_Climate-Change-Construction-Labour-in-Europe.pdf (accessed March 23, 2019), 15. 35.  The Internet of Things Business Index: A Quiet Revolution Gathers Pace, Economist Intelligence Unit, 2013, http://fliphtml5.com/atss/gzeh/basic (accessed May 9, 2019), 10. 36.  Jeremy Rifkin, The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism (New York: Palgrave Macmillan, 2014). 37.  Haier, “Haier Group Announces Phase 2.0 of Its Cornerstone ‘Rendanheyi’ Business Model,” Cision PR Newswire, September 21, 2015, https://www.prnewswire.com/news-releases/haier-group-announces-phase-20-of-its-cornerstone-rendanheyi-business-model-300146135.html (accessed March 5, 2019). 38.  


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The Age of Surveillance Capitalism by Shoshana Zuboff

Amazon Web Services, Andrew Keen, augmented reality, autonomous vehicles, barriers to entry, Bartolomé de las Casas, Berlin Wall, bitcoin, blockchain, blue-collar work, book scanning, Broken windows theory, California gold rush, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, citizen journalism, cloud computing, collective bargaining, Computer Numeric Control, computer vision, connected car, corporate governance, corporate personhood, creative destruction, cryptocurrency, dogs of the Dow, don't be evil, Donald Trump, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, Ford paid five dollars a day, future of work, game design, Google Earth, Google Glasses, Google X / Alphabet X, hive mind, impulse control, income inequality, Internet of things, invention of the printing press, invisible hand, Jean Tirole, job automation, Johann Wolfgang von Goethe, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, knowledge economy, linked data, longitudinal study, low skilled workers, Mark Zuckerberg, market bubble, means of production, multi-sided market, Naomi Klein, natural language processing, Network effects, new economy, Occupy movement, off grid, PageRank, Panopticon Jeremy Bentham, pattern recognition, Paul Buchheit, performance metric, Philip Mirowski, precision agriculture, price mechanism, profit maximization, profit motive, recommendation engine, refrigerator car, RFID, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Mercer, Second Machine Age, self-driving car, sentiment analysis, shareholder value, Shoshana Zuboff, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, smart cities, Snapchat, social graph, social web, software as a service, speech recognition, statistical model, Steve Jobs, Steven Levy, structural adjustment programs, The Future of Employment, The Wealth of Nations by Adam Smith, Tim Cook: Apple, two-sided market, union organizing, Watson beat the top human players on Jeopardy!, winner-take-all economy, Wolfgang Streeck

Kevin Ashton, a former Procter and Gamble brand manager who pioneered the marriage of radio-enabled microchips and physical products, birthed the term “internet of things,” and helped drive RFID innovation at MIT’s Media Lab, criticizes the US government for its lack of a comprehensive vision for the “internet of things” and the leadership of private firms in this domain. See Kevin Ashton, “America Last?” Politico, June 29, 2015, http://www.politico.com/agenda/story/2015/06/kevin-ashton-internet-of-things-in-the-us-000102. 20. See Nick Statt, “What the Volkswagen Scandal Means for the Future of Connected Devices,” Verge, October 21, 2015, http://www.theverge.com/2015/10/21/9556153/internet-of-things-privacy-paranoia-data-volkswagen-scandal. 21. Matt Weinberger, “Companies Stand to Make a Lot of Money Selling Data from Smart Devices, Says Microsoft,” Business Insider, December 6, 2015, http://www.businessinsider.com/microsoft-azure-internet-of-things-boss-sam-george-interview-2015-12; “Live on a Screen Near You: IoT Slam, a New Virtual Conference for All Things IoT,” Microsoft IoT Blog, December 9, 2015, https://blogs.microsoft.com/iot/2015/12/09/live-on-a-screen-near-you-iot-slam-a-new-virtual-conference-for-all-things-iot. 22.

Rachel Ward and Rebecca Lancaster, “The Contribution of Individual Factors to Driving Behaviour: Implications for Managing Work-Related Road Safety” (research report, Doherty Innovation Centre, Midlothian, UK, 2002), http://www.hse.gov.uk/research/rrhtm/rr020.htm. 32. “Insurers Need to Plug into the Internet of Things—or Risk Falling Behind,” McKinsey, January 8, 2017, http://www.mckinsey.com/industries/financial-services/our-insights/insurers-need-to-plug-into-the-internet-of-things-or-risk-falling-behind. 33. “Overcoming Speed Bumps on the Road to Telematics,” Deloitte University Press, April 21, 2014, https://dupress.deloitte.com/dup-us-en/industry/insurance/telematics-in-auto-insurance.html. 34. “Overcoming Speed Bumps on the Road to Telematics.” 35. Leslie Scism, “State Farm Is There: As You Drive,” Wall Street Journal, August 5, 2013. 36. “Insurers Need to Plug into the Internet of Things.” 37. Joseph Reifel, Alyssa Pei, Neeti Bhardwaj, and Shamik Lala, “The Internet of Things: Opportunity for Insurers,” ATKearney, 2014, https://www.atkearney.co.uk/documents/10192/5320720/internet+of+Things+-+Opportunity+for +Insurers.pdf/4654e400-958a-40d5-bb65-1cc7ae64bc72. 38.

., Operator benefits and rewards through sensory tracking of a vehicle, US20150019270 A1, published January 2015, 2015, http://www.google.com/patents/US20150019270. 42. Joao Lima, “Insurers Look Beyond Connected Cars for IOT Driven Business Boom,” Computer Business Review, December 9, 2015, http://www.cbronline.com/news/internet-of-things/insurers-look-beyond-connected-cars-for-iot-driven-business-boom-4748866. 43. Sam Ramji, “Looking Beyond the Internet of Things Hype: Here’s What’s in Store,” VentureBeat, March 28, 2014, http://venturebeat.com/2014/03/28/looking-beyond-the-internet-of-things-hype-heres-whats-in-store. 44. “Overcoming Speed Bumps on the Road to Telematics.” 45. Corin Nat, “Think Outside the Box—Motivate Drivers Through Gamification,” Spireon, August 11, 2015, https://web.archive.org/web/20150811014300/spireon.com/motivate-drivers-through-gamification; “Triad Isotopes,” 2017, http://www.triadisotopes.com. 46.


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Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Blythe Masters, Bretton Woods, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, commoditize, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, information asymmetry, intangible asset, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, money market fund, Network effects, new economy, Oculus Rift, off grid, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, QR code, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social intelligence, social software, standardized shipping container, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, unorthodox policies, wealth creators, X Prize, Y2K, Zipcar

Interview with Michelle Tinsley, June 25, 2015. 19. Ibid. 20. McKinsey Global Institute, “The Internet of Things: Mapping the Value Beyond the Hype,” June 2015. 21. Interview with Eric Jennings, July 10, 2015. 22. IBM Institute for Business Value, “The Economy of Things: Extracting New Value from the Internet of Things,” 2015. 23. Cadie Thompson, “Apple Has a Smart Home Problem: People Don’t Know They Want It Yet,” Business Insider, June 4, 2015; www.businessinsider.com/apple-homekit-adoption-2015-6. 24. McKinsey Global Institute, “The Internet of Things.” 25. Interview with Eric Jennings, July 10, 2015. 26. IBM, “Device Democracy,” 9. 27. Ibid., 13. 28. McKinsey Global Institute, “The Internet of Things.” MGI defined nine settings with value potential. 29. www.wikihow.com/Use-Uber. 30. http://consumerist.com/tag/uber/page/2/. 31.

Blockchain technology is critical. This Internet of Things (IoT) application depends on a Ledger of Things. With tens of thousands of smart poles collecting data through numerous sensors and communicating that data to another device, computer, or person, the system needs to continually track everything—including the ability to identify each unique pole—to ensure its reliability. “Nothing else works without identity,” said Jennings. “The blockchain for identity is the core for the Internet of Things. We create a unique path for each device. That path, that identity, is then stored in the bitcoin blockchain assigned to Filament. Just like a bitcoin, it can be sent to any address.”4 The blockchain (along with smart contracts) also ensures that the devices are paid for so they continue to work. The Internet of Things cannot function without blockchain payment networks, where bitcoin is the universal transactional language.

To overcome these obstacles, the Internet of Everything needs the Ledger of Everything—machines, people, animals, and plants. THE INTERNET OF THINGS NEEDS A LEDGER OF THINGS Welcome to the Internet of Everything enabled by the Ledger of Everything—distributed, reliable, and secure information sharing, sensing, and automating actions and transactions across the Internet, thanks to blockchain technology. Technologists and science fiction writers have long envisioned a world where a seamless global network of Internet-connected sensors could capture every event, action, and change on earth. With ubiquitous networks, continued advancements of processing capability, and an increasing array of cheap and tiny connected devices, that vision of an “Internet of Things” is edging closer to reality. Remember, Satoshi Nakamoto designed the bitcoin blockchain to ensure the integrity of each bitcoin transaction online and the bitcoin currency overall.


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Digital Bank: Strategies for Launching or Becoming a Digital Bank by Chris Skinner

algorithmic trading, AltaVista, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, bank run, Basel III, bitcoin, business cycle, business intelligence, business process, business process outsourcing, buy and hold, call centre, cashless society, clean water, cloud computing, corporate social responsibility, credit crunch, crowdsourcing, cryptocurrency, demand response, disintermediation, don't be evil, en.wikipedia.org, fault tolerance, fiat currency, financial innovation, Google Glasses, high net worth, informal economy, Infrastructure as a Service, Internet of things, Jeff Bezos, Kevin Kelly, Kickstarter, M-Pesa, margin call, mass affluent, MITM: man-in-the-middle, mobile money, Mohammed Bouazizi, new economy, Northern Rock, Occupy movement, Pingit, platform as a service, Ponzi scheme, prediction markets, pre–internet, QR code, quantitative easing, ransomware, reserve currency, RFID, Satoshi Nakamoto, Silicon Valley, smart cities, social intelligence, software as a service, Steve Jobs, strong AI, Stuxnet, trade route, unbanked and underbanked, underbanked, upwardly mobile, We are the 99%, web application, WikiLeaks, Y2K

This means that everything will be intelligently and wirelessly communicating with everything through what is now called the internet of things. The internet of things delivers a new wireless augmented world of digital reality where, in the very near future, fifty billion devices will be communicating with each other. The internet of things The internet of things is where internet communication – both wired and wireless – are placed into everyday objects from cars to refrigerators, keys to key rings, jewellery to watches and more. Anything that can have a chip placed inside in fact. We will all soon be wearing and watching and being monitored by chips in everything, and the vision of the internet of things is just that: ubiquitous connectivity with everything communicating and transacting non-stop. The key point about the internet of things is that it will be the next big wave of change.

We can see the opportunity this change offers today, thanks to Near Field Communication (NFC) and Radio Frequency IDentification (RFID) will provide the internet of things with the ability to transact. When we talk about chips inside everything, so that they can wirelessly communicate, those chips in everything will be RFID chips today. RFID can only hold a small amount of intelligence right now, so it needs something to receive the RFID information and that is NFC. Hence, NFC will become the reader mechanism in phones and other devices for RFID in the internet of things. Today, you buy things by taking them to the teller; tomorrow, if you want to buy something, you just read the QR code or hold your phone over its RFID tag. In addition, in the near future, the internet of things will be driven by the mobile internet of things, where everything is geo-located and identified by the network.

Meanwhile, my favourite authentication is Nymi by Biomix, a watchstrap that uses your heartbeat as verification. The reason the latter is my favourite is that mobile is rapidly moving from devices to wearable, and so we will soon have mobile chips embedded in jewellery, watches, handbags, shoes and fashion times. Yes, it’s back to the internet of things, but it goes beyond the internet of things to the knowledge of everything. Intellisensing and locating customers and verifying and authenticating them through the internet of things will become the norm. It will be the case of knowing who is where doing what in real-time, and being able to check it is who you think it is without forcing an action – a token or PIN being activated – but by sensing it who you think it is through the network. We are very near to this today and getting nearer every day, so let’s stop worrying about fraud and risk with mobiles and start thinking far more about fraud and risk minimisation with mobiles.


pages: 348 words: 97,277

The Truth Machine: The Blockchain and the Future of Everything by Paul Vigna, Michael J. Casey

3D printing, additive manufacturing, Airbnb, altcoin, Amazon Web Services, barriers to entry, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, blood diamonds, Blythe Masters, business process, buy and hold, carbon footprint, cashless society, cloud computing, computer age, computerized trading, conceptual framework, Credit Default Swap, crowdsourcing, cryptocurrency, cyber-physical system, dematerialisation, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, failed state, fault tolerance, fiat currency, financial innovation, financial intermediation, global supply chain, Hernando de Soto, hive mind, informal economy, intangible asset, Internet of things, Joi Ito, Kickstarter, linked data, litecoin, longitudinal study, Lyft, M-Pesa, Marc Andreessen, market clearing, mobile money, money: store of value / unit of account / medium of exchange, Network effects, off grid, pets.com, prediction markets, pre–internet, price mechanism, profit maximization, profit motive, ransomware, rent-seeking, RFID, ride hailing / ride sharing, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, smart contracts, smart meter, Snapchat, social web, software is eating the world, supply-chain management, Ted Nelson, the market place, too big to fail, trade route, transaction costs, Travis Kalanick, Turing complete, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, universal basic income, web of trust, zero-sum game

Casey, August 8, 2017. CHAPTER FIVE World Economic Forum founder Klaus Schwab says: Klaus Schwab, The Fourth Industrial Revolution (Crown, 2017). Security expert Bruce Schneier laid it all bare: Bruce Schneier, “The Internet of Things Will Turn Large-Scale Hacks into Real World Disasters,” Motherboard, July 25, 2016, https://motherboard.vice.com/en_us/article/qkjzwp/the-internet-of-things-will-cause-the-first-ever-large-scale-internet-disaster. In a widely read paper titled “Device Democracy…”: Veena Pureswaran and Paul Brody, “Device Democracy: Saving the Future of the Internet of Things,” September 2014, http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=GBE03620USEN. Demonstrating the extent of this challenge, researchers at the University of Michigan: Andy Greenberg, “This ‘Demonically Clever’ Backdoor Hides in a Tiny Slice of a Computer Chip,” Wired, June 1, 2016, https://www.wired.com/2016/06/demonically-clever-backdoor-hides-inside-computer-chip/.

“The Internet was originally built on trust,” write the authors of the IBM paper, Veena Pureswaran and Paul Brody. “In the post-Snowden era, it is evident that trust in the Internet is over. The notion of IoT solutions built as centralized systems with trusted partners is now something of a fantasy.” Pureswaran and Brody argue that the blockchain offers the only way to build the Internet of Things to scale while ensuring that no one entity has control over it. A blockchain-based system becomes the Internet of Things’ immutable seal. In an environment where so many machine-to-machine exchanges become transactions of value, we will need a blockchain in order for each device’s owner to trust the others. Once this decentralized trust structure is in place, it opens up a world of new possibilities. Consider this futuristic example: Imagine you drive your electric Tesla car to a small rural town to take a hike in the mountains for the day.

A decentralized, permissionless system means any device can participate in the network yet still give everyone confidence in the integrity of the data, of the devices, and of the value being transacted. A permissionless system would create a much more fluid, expansive Internet of Things network that’s not beholden to the say-so and fees of powerful gatekeepers. The problem is that the currently available decentralized, permissionless blockchains face limitations. Based on its block-size data limit and “on-chain” processing capability, Bitcoin can’t currently handle more than a few transactions a second—though the “off-chain” Lightning solution may advance that significantly—and Ethereum, though faster at processing blocks, will also often fail to process transactions when the network gets busy. Those limits, if they remain, are deal-breakers for the Internet of Things, which is projected to handle a massive amount of microtransaction traffic over billions of devices.


pages: 533

Future Politics: Living Together in a World Transformed by Tech by Jamie Susskind

3D printing, additive manufacturing, affirmative action, agricultural Revolution, Airbnb, airport security, Andrew Keen, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, blockchain, brain emulation, British Empire, business process, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Cass Sunstein, cellular automata, cloud computing, computer age, computer vision, continuation of politics by other means, correlation does not imply causation, crowdsourcing, cryptocurrency, digital map, distributed ledger, Donald Trump, easy for humans, difficult for computers, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, Filter Bubble, future of work, Google bus, Google X / Alphabet X, Googley, industrial robot, informal economy, intangible asset, Internet of things, invention of the printing press, invention of writing, Isaac Newton, Jaron Lanier, John Markoff, Joseph Schumpeter, Kevin Kelly, knowledge economy, lifelogging, Metcalfe’s law, mittelstand, more computing power than Apollo, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, night-watchman state, Oculus Rift, Panopticon Jeremy Bentham, pattern recognition, payday loans, price discrimination, price mechanism, RAND corporation, ransomware, Ray Kurzweil, Richard Stallman, ride hailing / ride sharing, road to serfdom, Robert Mercer, Satoshi Nakamoto, Second Machine Age, selection bias, self-driving car, sexual politics, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart contracts, Snapchat, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, technological singularity, the built environment, The Structural Transformation of the Public Sphere, The Wisdom of Crowds, Thomas L Friedman, universal basic income, urban planning, Watson beat the top human players on Jeopardy!, working-age population

David Rose, Enchanted Objects: Design, Human Desire, and the Internet of Things (New York: Scribner, 2014), 7. 31. Leo Mirani, ‘Personal Technology Gets Truly Personal’, in Megatech: Technology in 2050, ed. Daniel Franklin (New York: Profile Books, 2017), 150. 32. Alex Hern, ‘Vibrator Maker Ordered to Pay Out C$4m for Tracking Users’ Sexual Activity’, The Guardian, 14 March 2017 <https:// www.theguardian.com/technology/2017/mar/14/we-vibe-vibrator-tracking-users-sexual-habits?CMP=Share_iOSApp_Other> (accessed 1 December 2017). 33. Spencer Ackerman and Sam Thielman, ‘US Intelligence Chief: We Might Use the Internet of Things to Spy on You’, The Guardian, 9 February 2016 <https://www.theguardian.com/technology/2016/ feb/09/internet-of-things-smart-home-devices-governmentsurveillance-james-clapper> (accessed 1 December 2017).

In 2017 a vibrator maker agreed to pay customers compensation when it turned out that their ‘smart vibrator’ was tracking owners’ use without their knowledge and sending details of the devices’ temperature and vibration intensity OUP CORRECTED PROOF – FINAL, 26/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS 136 FUTURE POLITICS back to the manufacturer. It doesn’t get much more intimate than that. (Not to mention that the application used to control the vibrator was ‘barely secured’, meaning ‘anyone within Bluetooth range’ could ‘seize control’ of it.)32 Law enforcement officials have made no secret of their interest in the internet of things as a means of gathering information. Says the US Director of National Intelligence:33 In the future, intelligence services might use the [internet of things] for identification, surveillance, monitoring, location tracking, and targeting for recruitment, or to gain access to networks or user credentials. Imperishable We tend to think of forgetting as a vice. We curse our poor memories when we lose our keys or forget to call our mother on her birthday (a mistake the wise son only makes once).

Andrew Keen, The Internet is Not the Answer (London: Atlantic Books, 2015), 13; Richard Susskind and Daniel Susskind, The Future of the Professions: How Technology Will Transform the Work of Human Experts OUP CORRECTED PROOF – FINAL, 30/05/18, SPi РЕЛИЗ ПОДГОТОВИЛА ГРУППА "What's News" VK.COM/WSNWS Notes 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 377 (Oxford: Oxford University Press, 2015), 175; Gartner Newsroom, ‘Gartner Says By 2020, a Quarter Billion Connected Vehicles Will Enable New In-vehicle Services and Automated Driving Capabilities’, Gartner, 26 January 2015 <http://www.gartner.com/newsroom/ id/2970017> (accessed 30 November 2017). Samuel Greengard, The Internet of Things (Cambridge, Mass: MIT Press, 2015), 13. Greenfield, Everyware, 1. Greengard, Internet of Things; Greenfield, Everyware; Kitchin, Data Revolution. NYC Mayor’s Office of Technology and Innovation, ‘Preparing for the Internet of Everything’ (undated) <https://www1.nyc.gov/site/ forward/innovations/iot.page> (accessed 6 December 2017). Mat Smith, ‘Ralph Lauren Made a Great Fitness Shirt that Also Happens to Be “Smart”’, Engadget, 18 March 2016 <https://www. engadget.com/2016/03/18/ralph-lauren-polotech-review/> (accessed 6 December 2017).


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, offshore financial centre, open economy, Parag Khanna, paypal mafia, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, Travis Kalanick, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

Notably, all of North Korea’s Internet: Jack Kim and Lesley Wroughton, “North Korea’s Internet Links Restored amid US Hacking Dispute,” Reuters, December 23, 2014, http://www.reuters.com/article/2014/12/23/us-northkorea-cyberattack-idUSKBN0K107920141223. Cisco Systems chairman John Chambers: “Cisco Keynote Highlights from CES 2014,” YouTube, January 10, 2014, http://www.youtube.com/watch?v=TepUznT42ro. From 2015 to 2020, the number: “The Internet of Things Will Drive Wireless Connected Devices to 40.9 Billion in 2020,” ABI Research, August 20, 2014, https://www.abiresearch.com/press/the-internet-of-things-will-drive-wireless-connect. Chambers predicts that the Internet of Things: Don Clark, “Cisco CEO Chambers Still Biggest ‘Internet of Things’ Cheerleader,” Wall Street Journal, January 7, 2014, http://blogs.wsj.com/digits/2014/01/07/cisco-ceo-john-chambers-Internet-of-everything-ces-2014/. For context, the GDP: “Report for Selected Country Groups and Subjects,” International Monetary Fund: World Economic Outlook Database, October 2014, http://www.imf.org/external/pubs/ft/weo/2014/02/weodata/weorept.aspx?

McKinsey bases this estimate on potential savings of 2.5 to 5 percent in operating costs, the integration of the Internet of Things into the power grid, and its applications in public-sector services like waste, heating, and water systems that they believe could cut waste by 10 to 20 percent annually. There’s one huge catch: with the rapid growth of these technologies, we are also creating an almost unimaginable new set of vulnerabilities and openings for cybersecurity hacks. As the Internet of Things is rising, cybersecurity has not kept pace. “Security has often been an afterthought in the design of those systems,” says Chris Bronk, a computer and information systems professor at the University of Houston. The breach of confidentiality that occurred at Target was in many ways a precursor to what’s possible in a world that’s connected by an Internet of Things. In the Target hack, the tens of millions of credit card records were accessed because of a hack on Fazio Mechanical, a small company in Sharpsburg, Pennsylvania, that does heating, air-conditioning, and refrigeration jobs.

As a result, the stage is now set for what has become known as the “Internet of Things,” where any object has the potential to transmit and receive data, from cars and farm equipment to watches and appliances, even clothing. The digitization of nearly everything is poised to be one of the most consequential economic developments of the next ten years. Cisco Systems chairman John Chambers has said, “We will look back one decade from today [2014] and you’ll look at the impact of the Internet of Everything, and I predict it will be five to ten times more impactful in one decade than the whole Internet to date has been.” From 2015 to 2020, the number of wireless connected devices is going to grow from an estimated 16 billion to 40 billion. Chambers predicts that the Internet of Things will grow to be a $19 trillion global market.


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, basic income, Benevolent Dictator For Life (BDFL), Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, Ethereum, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Joan Didion, John Markoff, Joi Ito, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, MITM: man-in-the-middle, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, undersea cable, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

Fabbaloo, April 7, 2010, http://www.fabbaloo.com/blog/2010/4/7/the-3d-printer-virus-really.html. 20.  Cory Doctorow, “Metacrap: Putting the Torch to Seven Straw-men of the Meta-Utopia,” Well, August 26, 2011. 21.  Payam Barnaghi, Cory Henson, Kerry Taylor, and Wei Wang, “Semantics for the Internet of Things: Early Progress and Back to the Future,” International Journal on Semantic Web and Information System 8, no. 1 (2012): 1–21, http://knoesis.org/library/download/IJSWIS_SemIoT.pdf. 22.  Yann Moulier-Boutang, Cognitive Capitalism (London: Polity Press, 2012). 23.  Open Internet of Things Assembly, “Bill of Rights” http://postscapes.com/open-internet-of-things-assembly. (July 17, 2012). 24.  See, for example, Saul A. Kripke, Naming and Necessity (Cambridge, MA: Harvard University Press, 1980). I particularly care, in this instance, to underscore that citing this work is not the same as recommending this work. 25. 

As such, data centers may be moved closer to users, with relevant content sent from a central facility out to regional data centers only once, and further transmissions occurring over shorter regional links. As a result, every request from a user need not result in a transmission cross-country and through the Internet backbone; network activity may be more evenly balanced and confined to local areas.” 18.  Cisco proudly estimated the number of “things” connected to the Internet of Things as 50 billion by 2020. See Dave Evans, “The Internet of Things: How the Next Evolution of the Internet Is Changing Everything,” April 2011, https://www.cisco.com/web/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf. To say nothing of the more or less charted waters of the Dark Net, accessible only through tools like the Tor browser. 19.  But as Jameson notes, it is the irregularity of opposing forces that breaks down the order of the nomos: “With the religious wars, but perhaps also the English dominance of the sea—now leads to the Westphalian system of nation-states, in which, for the first time, the new nomos of state equality and friend-foe emerges.

Just as most of the traffic on the Internet today is machine-to-machine, or at least machine generated, so too a semantic web of things21 would be correlated less by the cognitive dispositions or instrumental intentions of human Users, but those of “objects” and other instances within the larger meta-assemblage all querying and programming one another without human intervention or supervision. In the hype, it's easy to forget that the Internet of Things is also an Internet for Things (or for any addressable entity, however immaterial). Control of this multitude of chattering things would represent enormous power, and the danger of overcentralization paired with a monetized opacity of data flows is real. The capture of the “general intellect” by search and other mechanisms of “cognitive capitalism” is one lens through which to imagine a future in which tracing objective knowledge about the appearance and disappearance of material culture is a proprietary narrative.22 At the same time, Internet of Things scenarios that prioritize human Users sensing and interacting with their responsive habitats, as masters of the data that appear in their midst, divert discussions of the politics of ubiquitous computing toward an overly local frame of reference within a larger landscape of humans and nonhuman associations.


Virtual Competition by Ariel Ezrachi, Maurice E. Stucke

Airbnb, Albert Einstein, algorithmic trading, barriers to entry, cloud computing, collaborative economy, commoditize, corporate governance, crony capitalism, crowdsourcing, Daniel Kahneman / Amos Tversky, David Graeber, demand response, disintermediation, disruptive innovation, double helix, Downton Abbey, Erik Brynjolfsson, experimental economics, Firefox, framing effect, Google Chrome, index arbitrage, information asymmetry, interest rate derivative, Internet of things, invisible hand, Jean Tirole, John Markoff, Joseph Schumpeter, Kenneth Arrow, light touch regulation, linked data, loss aversion, Lyft, Mark Zuckerberg, market clearing, market friction, Milgram experiment, multi-sided market, natural language processing, Network effects, new economy, offshore financial centre, pattern recognition, prediction markets, price discrimination, price stability, profit maximization, profit motive, race to the bottom, rent-seeking, Richard Thaler, ride hailing / ride sharing, road to serfdom, Robert Bork, Ronald Reagan, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, smart meter, Snapchat, social graph, Steve Jobs, supply-chain management, telemarketer, The Chicago School, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, Travis Kalanick, turn-by-turn navigation, two-sided market, Uber and Lyft, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, women in the workforce, yield management

The sale and ownership of information and risks associated with disclosure were key concerns with 71 per cent of users’ concerns with information being sold to a third party and 59 per cent concerned about a lack of information on where their data goes and who owns it.10 Extraction and Capture 163 With the rise of the Internet of Things, mobile platforms will become the key gateway to the flow of personal data. Google’s underlying operating system for the Internet of Things, dubbed “Brillo,” is based on its Android operating system.11 As our smartphones are always near us (except perhaps when we shower or swim), they will assist the super-platforms, governments,12 and others in tracking our behavior, harvesting our data, and targeting us with behavioral ads.13 This data trove will also attract hackers and criminals. Thus we should expect Frenemies to support the Internet of Things, to the extent that the sensors can effectively track and collect data on us when we are offline—data that can be used to fuel their advertising-supported business model.

And access to the many different clients’ data will improve Amazon’s, Microsoft’s and Google’s algorithms. Another contributing factor will be the “Internet of Things,” that is, the integration of soft ware and sensors embedded in everyday objects. This technology enables machine-to-machine communication (M2M), as well as the collection and analysis of information gathered through sensors. For instance, Amazon in 2015 launched its “IoT platform,” which “lets connected devices easily and securely interact with cloud applications and other devices.”63 The platform is designed to process trillions of messages from billions of devices “and can process and route those messages to [Amazon Web Ser vice] endpoints and to other devices reliably and securely.”64 The research firm International Data Corp estimated the “global market for Internet of Things” to nearly triple to $1.7 trillion by 2020.65 The firm also New Economic Reality 19 notes how technology firms, like Google, Intel Corp, Cisco Systems, Samsung Electronics and the major telecoms such as Vodafone and Verizon, “are betting heavily on it to drive revenue and profit in the future.” 66 Whereas traditional data is harvested through our interaction with online sellers and our digitalized environment, the Internet of Things would widen the scope of data for the algorithms.

Danny Palmer, “Amazon follows Microsoft and Google with AI tools in Amazon Machine Learning Ser vice,” Computing, April 10, 2015, http://www .computing.co.uk /ctg/news/2403533/amazon-follows-microsoft-and-google -into-offering-customers-ai-tools-with-amazon-machine-learning-service. 63. Ingrid Lunden, “Amazon Launches AWS IoT—A Platform for Building, Managing and Analyzing the Internet Of Things,” Tech Crunch, October 8, 2015, http://techcrunch.com/2015/10/08/amazon-announces-aws-iot-a -platform-for-building-managing-and-analyzing-the-internet-of-things/# .gfgxjj:0nTE. 64. Ibid. Amazon Web Ser vices is a collection of cloud computing ser vices offered by Amazon. “Amazon Web Ser vices offers a broad set of global compute, storage, database, analytics, application, and deployment ser vices that help organizations move faster, lower IT costs, and scale applications”; Amazon Web Ser vices, Cloud Products (2015), https://aws.amazon.com /products/?


Smart Cities, Digital Nations by Caspar Herzberg

Asian financial crisis, barriers to entry, business climate, business cycle, business process, carbon footprint, clean water, cloud computing, corporate social responsibility, Dean Kamen, demographic dividend, Edward Glaeser, Edward Snowden, hive mind, Internet of things, knowledge economy, Masdar, megacity, New Urbanism, packet switching, QR code, remote working, RFID, rising living standards, risk tolerance, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley startup, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart meter, social software, special economic zone, Stephen Hawking, telepresence, too big to fail, trade route, transcontinental railway, upwardly mobile, urban planning, urban sprawl, women in the workforce, working poor, X Prize

Dan Kaplan, “Black Hat: Assessing Smart Meters for Hacker Footprints, Vulnerabilities,” SC Magazine, July 25, 2012, http://www.scmagazine.com/black-hat-assessing-smartmeters-for-hacker-footprints-vulnerabilities/article/251947/. 8 In addition to Cisco’s dedicated focus on security, there are many independent groups highlighting the vulnerabilities of devices and how consumers can protect themselves, e.g. “Abusing the Internet of Things: Blackouts. Freakouts. Stakeouts,” (Blackhat.com; https://www.blackhat.com/docs/asia-14/materials/Dhanjani/Asia-14-Dhanjani-Abusing-The-Internet-Of-Things-Blackouts-Freakouts-And-Stakeouts.pdf), which describes how several household devices can be compromised. 9 Dave Evans, “End of the Human Race?” LinkedIn, May 8, 2015, https://www.linkedin.com/pulse/end-humanrace-david-evans CONCLUSION AS THE AUTHOR THINKS BACK on a decade of work and its implications for the future of digital cities, there is the inescapable fact that very few details remain in place for long.

These new smart cities engage high-tech industrial pioneers to provide the digital infrastructure, and companies such as Cisco are finding success providing the Internet “plumbing” in this age of massive digital expansion. The countries and cities explored in this book are perfect examples with which to trace the development of smart cities and analyze the lessons learned in making them work. This, in turn, forms the basis for the “Internet of Things” (IoT), a network that enables physical objects to collect and exchange data, and the “Internet of Everything” (IoE), a future wherein devices, appliances, people, and process are connected via the global Internet. The IoE is a value proposition that is estimated to be worth trillions of dollars to the technology industry and the early adopters in business and the public sector. This new digital technology is also the source of the second challenge that threatens to overwhelm the modern city: data.

THE FUTURE: SEEN FROM THE EAST, COMING TO THE WEST History repeatedly tells us what happens when too many people are trying to live with insufficient land, resources, or jobs. And while data may be a new concern with regard to population growth, it poses unforeseen threats, in addition to the opportunities it creates. It could be argued that there has never been a time in history when “too much information” was even possible at the city level. But as the Internet of Things becomes the Internet of Everything, we will enter a new, in-formation-laden reality. The systems and platforms implemented today will harness more or less of that data, depending on how systematically it is captured and how aware people are of its potential uses. Data, like fire, is agnostic when it comes to humans—its value, or danger, depends wholly on who uses it and how they use it. We must keep our data under control even as we discover new sources and uses for it, which will create a delicate balancing act.


Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, bitcoin, business intelligence, business process, chief data officer, clean water, cloud computing, computer vision, continuous integration, crowdsourcing, data is the new oil, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, income inequality, Infrastructure as a Service, Internet of things, Masdar, microservices, Minecraft, platform as a service, ransomware, RFID, ride hailing / ride sharing, risk tolerance, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

This is what is typically referred to as the Internet of Things. We look at the challenges of managing thousands or even millions of devices and what it takes to secure them. We will also consider examples of how to build standards around the use of devices in a city context. Even the casual observer of the world of technology has heard about the Internet of Things or IoT for short. To many people, IoT is this magical thing that will manage our homes, mow our lawns, and bring us the food we need when we need it. This may indeed be one of the end results, but before we get there, we should consider what this really means. In the previous chapter, we broke down different ways to connect things. But what exactly is connected? What are these “things” that are connected in the Internet of Things? A more precise term than “thing” might be device, since most of the things we are thinking about in the context of IoT are devices.

You can find him online and read more on his blog at www.lisdorf.com . About the Technical Reviewer Ahmed Bakir is an iOS author, teacher, and entrepreneur. He has worked on over 30 mobile projects, ranging from advising startups to architecting apps for Fortune 500 companies. In 2014, he published his first book,Beginning iOS Media App Development , followed by the first edition ofProgram the Internet of Things with Swift for iOS in 2016 and the second edition in 2018. In 2015, he was invited to develop courses and teach iOS development at UCSD Extension. He is currently building cool stuff in Tokyo! You can find him online at www.devatelier.com . © Anders Lisdorf 2020 A. LisdorfDemystifying Smart Citieshttps://doi.org/10.1007/978-1-4842-5377-9_1 1. Introduction Anders Lisdorf1 (1)Copenhagen, Denmark One of the first musical memories I have is Queen’s music video for “Radio Gaga” in which a bleak future city with flying cars and high rises is portrayed.

A special case of hardware vendors is telecommunications providers. Whereas they don’t sell their hardware directly, the implementation and use of it is critically tied to cities allowing them to do it and using them for solution deployments. Software vendors – Only sell their products embedded with hardware in exceptional cases like appliances or when they supply peripheral hardware like AWS and Microsoft offering an Internet of Things (IoT) button. Consequently, these vendors are interested in solutions where their software generates license, support, or subscription fees, which means they are interested in embedding their software in lasting solutions or as is the case with cloud vendors, to become the main platform for any type of solution. This means they are interested in integrating their solutions with other existing solutions to create durable long-term solutions or platforms.


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Architecting For Scale by Lee Atchison

Amazon Web Services, business process, cloud computing, continuous integration, DevOps, Internet of things, microservices, platform as a service, risk tolerance, software as a service, web application

., Availability Zones Are Not Data Centers-Availability Zones Are Not Data Centers outages and, Availability Zones Are Not Data Centers AWS (Amazon Web Services)API Gateway, Mobile Backend architecture, AWS Architecture-Architecture Overview AutoScaling, Changing Allocations Availability Zones (see Availability Zones) data centers, Data Center, Availability Zones Are Not Data Centers-Availability Zones Are Not Data Centers DynamoDB, Allocated-Capacity Resource Allocation EC2 (see Amazon EC2) ecosystem terms, AWS Architecture-Data Center Elastic Load Balancer, Changing Allocations Kinesis, Internet of Things Data Intake Lambda (see AWS Lambda) maintaining location diversity for availability reasons, Maintaining Location Diversity for Availability Reasons overview, Architecture Overview-Architecture Overview Regions (see AWS Regions) S3 (see Amazon S3) SLAs, What are Service-Level Agreements? AWS Lambda, AWS Lambda-Advantages and Disadvantages of Lambdaadvantages/disadvantages, Microcompute, Advantages and Disadvantages of Lambda event processing, Event Processing Internet of Things data intake, Internet of Things Data Intake mobile backend, Mobile Backend picture management application, Event Processing using, Using Lambda-Internet of Things Data Intake AWS Regions, AWS Region, Architecture Overview B business requirements, service boundaries and, Guideline #1: Specific Business Requirements C call latency, Performance Measurements for SLAs-Latency Groups capabilities, shared, Guideline #4: Shared Capabilities/Data capacity units, Allocated-Capacity Resource Allocation cascading service failures, Cascading Service Failures Chaos Monkey, Concerns with Running Game Days in Production circuit breakers, Focus #1: Build with Failure in Mind, Determining Failures cloud-based servers, Cloud-Based Servers cloud-based services, Cloudallocated capacity resource allocation, Allocated-Capacity Resource Allocation-Reserved Capacity, The Pros and Cons of Resource Allocation Techniques application management, Greater Focus on the Application AWS architecture, AWS Architecture-Architecture Overview AWS Availability Zones, AWS Availability Zone, Availability Zones Are Not Data Centers-Availability Zones Are Not Data Centers(see also Availability Zones (AZs)) AWS Lambda, Microcompute, AWS Lambda-Advantages and Disadvantages of Lambda AWS Region, AWS Region changes in, Change and the Cloud-Change Continues choosing scalable computing options, Now What?

G game days, Game Days-Game Day TestingChaos Monkey, Concerns with Running Game Days in Production staging vs. production environments, Staging Versus Production Environments-Staging Versus Production Environments testing recovery plans in production environment, Concerns with Running Game Days in Production Google App Engines, Optimized Use Cases graceful backoff, Graceful Backoff graceful degradation, Graceful Degradation, Critical Dependency H Heroku Dynos, Compute Slices human error, Operational Processes I icon failure, Five Focuses to Improve Application Availability idempotent interfaces, Redundancy independence, risk mitigation and, Independence internal SLAs, External Versus Internal SLAs, How Many and Which Internal SLAs? Internet of Things, Internet of Things Data Intake K key-based partitioning, Data Partitioning-Data Partitioning L Lambda (see AWS Lambda) latency, Performance Measurements for SLAs-Latency Groups latency groups, Latency Groups likelihood, riskand changes in risk matrix reviews, Review Regularly, Maintaining the Risk Matrix as risk component, Likelihood Versus Severity severity vs., Likelihood Versus Severity-T-Shirt Photos: High Likelihood, High Severity Risk limit SLAs, Limit SLAs load balancing, Availability Zones Are Not Data Centers localization, data, Where’s the Data?

The necessary APIs are created by using an API Gateway1 that connects with a series of Lambda functions. The scripts perform the operations necessary, in conjunction with some form of database, to handle the cloud backend for the mobile game. This architecture is shown in Figure 25-2. Figure 25-2. Mobile backend lambda usage In this model, no servers are needed on the backend, and all scaling is handled automatically. Internet of Things Data Intake Consider an application that takes data from a huge quantity of data sensors deployed around the world. Data from these sensors arrives regularly. On the server side, this results in an enormous quantity of data being regularly presented to the application for storage in some form of data store. The data is used by some backend application, which will be ignored for this example.


pages: 464 words: 127,283

Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia by Anthony M. Townsend

1960s counterculture, 4chan, A Pattern Language, Airbnb, Amazon Web Services, anti-communist, Apple II, Bay Area Rapid Transit, Burning Man, business process, call centre, carbon footprint, charter city, chief data officer, clean water, cleantech, cloud computing, computer age, congestion charging, connected car, crack epidemic, crowdsourcing, DARPA: Urban Challenge, data acquisition, Deng Xiaoping, digital map, Donald Davies, East Village, Edward Glaeser, game design, garden city movement, Geoffrey West, Santa Fe Institute, George Gilder, ghettoisation, global supply chain, Grace Hopper, Haight Ashbury, Hedy Lamarr / George Antheil, hive mind, Howard Rheingold, interchangeable parts, Internet Archive, Internet of things, Jacquard loom, Jane Jacobs, jitney, John Snow's cholera map, Joi Ito, Khan Academy, Kibera, Kickstarter, knowledge worker, load shedding, M-Pesa, Mark Zuckerberg, megacity, mobile money, mutually assured destruction, new economy, New Urbanism, Norbert Wiener, Occupy movement, off grid, openstreetmap, packet switching, Panopticon Jeremy Bentham, Parag Khanna, patent troll, Pearl River Delta, place-making, planetary scale, popular electronics, RFC: Request For Comment, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social graph, social software, social web, special economic zone, Steve Jobs, Steve Wozniak, Stuxnet, supply-chain management, technoutopianism, Ted Kaczynski, telepresence, The Death and Life of Great American Cities, too big to fail, trade route, Tyler Cowen: Great Stagnation, undersea cable, Upton Sinclair, uranium enrichment, urban decay, urban planning, urban renewal, Vannevar Bush, working poor, working-age population, X Prize, Y2K, zero day, Zipcar

We’ll never know what tipped the balance—perhaps a new city bus fired up its GPS tracker for the first time, or some grad students at MIT plugged their coffee pot into Facebook. But at some point the Internet of people gave way to the Internet of Things.16 Today, there are at least two additional things connected to the Internet for every human being’s personal device. But by 2020 we will be hopelessly outnumbered—some 50 billion networked objects will prowl the reaches of cyberspace, with a few billion humans merely mingling among them.17 If you think banal chatter dominates the Web today, get ready for the cacophony of billions of sensors tweeting from our pockets, the walls, and city sidewalks, reporting on minutiae of every kind: vehicle locations, room temperatures, seismic tremors, and more. By 2016, the torrent of readings generated by this Internet of Things could exceed 6 petabytes a year on our mobile networks alone (one petabyte equaling one billion gigabytes).18 It will drown out the entire human web—the 10 billion photos currently archived on Facebook total a mere 1.5 petabytes.19 Software in the service of businesses, governments, and even citizens will tap this pool of observations to understand the world, react, and predict.

Instead of making funny videos to promote their invention, students would have spent their evenings holding smoking soldering irons, staring bleary-eyed into a tangle of wires. But Botanicalls is just one of thousands of projects that are exploiting a new approach to prototyping networked objects, allowing civic hackers, students, and artists around the world to invent their own visions of the Internet of Things. Botanicalls, like many objects on the Internet of Things, is powered by an unsung but utterly ubiquitous kind of computer called a microcontroller. Microcontrollers are the brains of the modern mechanical world, governing the operations of everything from elevators to the remote control on your TV. Like a personal computer, they contain a processor, memory, and input/output systems. But unlike PCs, microcontrollers are small, simple, and cheap.

Normally the combined outflow is processed by treatment plants before being released into the surrounding waterways, but during heavy rains the plants can’t keep up; to keep the deluge from backing up into city streets, a nasty mixture of runoff and raw sewage is discharged directly into the city’s rivers—some 27 billion gallons a year.40 But by hooking up an Arduino to a proximity sensor and a $15 cell phone he bought off eBay, Percifield’s gadget sits over the outflow pipe and transmits an alert across the Internet to a network of bathroom-based lightbulb overflow-warning indicators.41 The result is a guerrilla sensor net that encourages people to not flush toilets during overflow events, reducing the discharge of sewage. By changing people’s behavior, it could stanch the need for hundreds of millions of dollars of retrofits to the city’s sewage infrastructure. Projects like dontflush.me suggest a future where citizens decide what gets connected to the Internet of Things, and why. Instead of being merely a system for remote monitoring and management, as industry visionaries see it today, the Internet of Things could become a platform for local, citizen microcontrol of the physical world. And that’s what’s so disruptive about Arduino’s growing reach. Torrone suggests more prosaic applications for which Arduino is also the clear technology of choice. “Want to have a coffee pot tweet when the coffee is ready? Arduino. How about getting an alert on your phone when there’s physical mail in your mailbox?


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, crowdsourcing, digital twin, disintermediation, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, mass immigration, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Sam Altman, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, TaskRabbit, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

Eaton Corporation builds sensors into certain high-pressure hoses that sense when the hose is about to fray, preventing potentially dangerous accidents and saving the high costs of downtime of the machines that have the hoses as a key component. Source: “The Internet of Things: The Opportunities and Challenges of Interconnectedness”, Roundtable on Digital Strategies Overview, Center for Digital Strategies at the Tuck School of Business at Dartmouth, 2014 Already last year, according to BMW 8% of cars worldwide, or 84 million, were connected to the internet in some way., That number will grow to 22%, or 290 million cars, by 2020. Source: http://www.politico.eu/article/google-vs-german-car-engineer-industry-american-competition/ Insurance companies like Aetna are thinking about how sensors in a carpet could help if you’ve had a stroke. They would detect any gait change and have a physical therapist visit. Source: “The Internet of Things: The Opportunities and Challenges of Interconnectedness”, Roundtable on Digital Strategies Overview, Center for Digital Strategies at the Tuck School of Business at Dartmouth, 2014 Shift 9: The Connected Home Tipping point: Over 50% of internet traffic delivered to homes for appliances and devices (not for entertainment or communication) By 2025: 70% of respondents expected this tipping point to have occurred In the 20th century, most of the energy going into a home was for direct personal consumption (lighting).

We have yet to grasp fully the speed and breadth of this new revolution. Consider the unlimited possibilities of having billions of people connected by mobile devices, giving rise to unprecedented processing power, storage capabilities and knowledge access. Or think about the staggering confluence of emerging technology breakthroughs, covering wide-ranging fields such as artificial intelligence (AI), robotics, the internet of things (IoT), autonomous vehicles, 3D printing, nanotechnology, biotechnology, materials science, energy storage and quantum computing, to name a few. Many of these innovations are in their infancy, but they are already reaching an inflection point in their development as they build on and amplify each other in a fusion of technologies across the physical, digital and biological worlds. We are witnessing profound shifts across all industries, marked by the emergence of new business models, the disruption1 of incumbents and the reshaping of production, consumption, transportation and delivery systems.

New innovations in thermoset plastics, for example, could make reusable materials that have been considered nearly impossible to recycle but are used in everything from mobile phones and circuit boards to aerospace industry parts. The recent discovery of new classes of recyclable thermosetting polymers called polyhexahydrotriazines (PHTs) is a major step towards the circular economy, which is regenerative by design and works by decoupling growth and resource needs.8 2.1.2 Digital One of the main bridges between the physical and digital applications enabled by the fourth industrial revolution is the internet of things (IoT) – sometimes called the “internet of all things”. In its simplest form, it can be described as a relationship between things (products, services, places, etc.) and people that is made possible by connected technologies and various platforms. Sensors and numerous other means of connecting things in the physical world to virtual networks are proliferating at an astounding pace. Smaller, cheaper and smarter sensors are being installed in homes, clothes and accessories, cities, transport and energy networks, as well as manufacturing processes.


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Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

3D printing, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, Apple's 1984 Super Bowl advert, autonomous vehicles, barriers to entry, big data - Walmart - Pop Tarts, bitcoin, blockchain, business cycle, business process, buy low sell high, chief data officer, Chuck Templeton: OpenTable:, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, digital map, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, information asymmetry, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, Khan Academy, Kickstarter, Lean Startup, Lyft, Marc Andreessen, market design, Metcalfe’s law, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel, pets.com, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the payments system, Tim Cook: Apple, transaction costs, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, winner-take-all economy, zero-sum game, Zipcar

And Internet-centered companies like Google and Apple are designing interfaces and operating systems that will enable both technology experts and ordinary people to have easy access to the Internet of things and use it in countless ways we’re only beginning to imagine and explore. What’s more, the potential power of the Internet of things will only continue to grow as the varieties of devices available to us and their capabilities continue to expand. To mention just a few examples, consider the transformative power of such just-around-the-corner technologies as driverless cars, cheap and powerful electrical storage batteries for the home, and easy-to-use 3D printers for quickly replicating useful objects. As these and other new tools become widely available, they’ll also quickly be linked to the Internet of things, making even more powerful value-creating platforms possible. Applied to the Internet of things, platform economics will dramatically alter the business models associated with countless familiar goods and services.

Many are now being located not in computing devices such as laptops and cell phones but in ordinary machines and appliances—including everything from home thermostats and garage door openers to industrial security systems. With designers and engineers finding more and more ways to usefully link the machines, gadgets, and other devices people interact with daily, a vast new layer of data infrastructure is emerging that has been dubbed the Internet of things. This new universe of networks will have a profound impact on the power of tomorrow’s platforms. A wide range of companies is deeply engaged in the effort to build the Internet of things—and, if possible, to control both the new infrastructure and the ultra-valuable data it will provide. As we’ve mentioned, industrial firms like GE, Siemens, and Westinghouse are moving to create information links among the turbines, engines, motors, heating and cooling systems, and manufacturing plants they build and operate, hoping to enable tremendous new efficiencies and cost savings.

But when home lighting systems are connected to the Internet of things, the very purpose of the lightbulb is transformed. Lights can be programmed for intruder alerts; they can flash to warn parents when a toddler is wandering near the stairs or the stove; they can blink to remind grandma to take her medication. Lights with wireless connectivity can track the energy consumption of other appliances, enabling lightbulb vendors to offer energy management services to homeowners and utility companies. Suddenly, the lightbulb maker can afford to give away a $40 LED in exchange for a share of the ongoing revenues provided by networked services. Platform-based connections among household and personal devices have attracted much of the publicity surrounding the Internet of things. But the potential for transformation in the B2B world is, if anything, even greater.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, uber lyft, unbanked and underbanked, underbanked, web application, WikiLeaks

It’s Called Post-PC Computing.” Radar (O’Reilly), October 24, 2011. http://radar.oreilly.com/2011/10/post-pc-revolution.html. 9 Gartner. “Gartner Says the Internet of Things Installed Base Will Grow to 26 Billion Units By 2020.” Gartner Press Release, December 12, 2013. http://www.gartner.com/newsroom/id/2636073. 10 Omohundro, S. “Cryptocurrencies, Smart Contracts, and Artificial Intelligence.” Submitted to AI Matters (Association for Computing Machinery), October 22, 2014. http://steveomohundro.com/2014/10/22/cryptocurrencies-smart-contracts-and-artificial-intelligence/. 11 Dawson, R. “The New Layer of the Economy Enabled by M2M Payments in the Internet of Things.” Trends in the Living Networks, September 16, 2014. http://rossdawsonblog.com/weblog/archives/2014/09/new-layer-economy-enabled-m2m-payments-internet-things.html. 12 Petschow, K.

Mobile and social networking was the most recent paradigm. The current emerging paradigm for this decade could be the connected world of computing relying on blockchain cryptography. The connected world could usefully include blockchain technology as the economic overlay to what is increasingly becoming a seamlessly connected world of multidevice computing that includes wearable computing, Internet-of-Things (IoT) sensors, smartphones, tablets, laptops, quantified self-tracking devices (i.e., Fitbit), smart home, smart car, and smart city. The economy that the blockchain enables is not merely the movement of money, however; it is the transfer of information and the effective allocation of resources that money has enabled in the human- and corporate-scale economy. With revolutionary potential equal to that of the Internet, blockchain technology could be deployed and adopted much more quickly than the Internet was, given the network effects of current widespread global Internet and cellular connectivity.

The world is already being prepared for more pervasive Internet-based money: Apple Pay (Apple’s token-based ewallet mobile app) and its competitors could be a critical intermediary step in moving to a full-fledged cryptocurrency world in which the blockchain becomes the seamless economic layer of the Web. Figure P-1. Disruptive computing paradigms: Mainframe, PC, Internet, Social-Mobile, Blockchain8 M2M/IoT Bitcoin Payment Network to Enable the Machine Economy Blockchain is a revolutionary paradigm for the human world, the “Internet of Individuals,” and it could also be the enabling currency of the machine economy. Gartner estimates the Internet of Things will comprise 26 billion devices and a $1.9 trillion economy by 2020.9 A corresponding “Internet of Money” cryptocurrency is needed to manage the transactions between these devices,10 and micropayments between connected devices could develop into a new layer of the economy.11 Cisco estimates that M2M (machine-to-machine) connections are growing faster than any other category (84 percent), and that not only is global IP traffic forecast to grow threefold from 2012 to 2018, but the composition is shifting in favor of mobile, WiFi, and M2M traffic.12 Just as a money economy allows for better, faster, and more efficient allocation of resources on a human scale, a machine economy can provide a robust and decentralized system of handling these same issues on a machine scale.


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Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It by Tien Tzuo, Gabe Weisert

3D printing, Airbnb, airport security, Amazon Web Services, augmented reality, autonomous vehicles, blockchain, Build a better mousetrap, business cycle, business intelligence, business process, call centre, cloud computing, cognitive dissonance, connected car, death of newspapers, digital twin, double entry bookkeeping, Elon Musk, factory automation, fiat currency, Internet of things, inventory management, iterative process, Jeff Bezos, Kevin Kelly, Lean Startup, Lyft, manufacturing employment, minimum viable product, natural language processing, Network effects, Nicholas Carr, nuclear winter, pets.com, profit maximization, race to the bottom, ride hailing / ride sharing, Sand Hill Road, shareholder value, Silicon Valley, skunkworks, smart meter, social graph, software as a service, spice trade, Steve Ballmer, Steve Jobs, subscription business, Tim Cook: Apple, transport as a service, Uber and Lyft, uber lyft, Y2K, Zipcar

drop in global productivity IMF Staff Discussion Note, “Gone with the Headwinds: Global Productivity,” April 3, 2017, www.imf.org/~/media/Files/Publications/SDN/2017/sdn1704.ashx. manufacturers contributed $2.2 trillion National Association of Manufacturers, “Top 20 Facts About Manufacturing,” www.nam.org/Newsroom/Facts-About-Manufacturing. And if you sell technology to help sense conditions Scott Pezza, “How to Make Money with the Internet of Things,” Blue Hill Research, May 18, 2015, http://bluehillresearch.com/how-to-make-money-with-the-internet-of-things. most of our factories look the same Olivier Scalabre, “The Next Manufacturing Revolution Is Here,” TED talk, May 2016, www.ted.com/talks/olivier_scalabre_the_next_manufacturing_revolution_is_here/transcript. We recently hosted Gytis Barzdukas “Gytis Barzdukas, GE Digital,” Zuora Subscribed conference, www.youtube.com/watch?v=OEq5HTz7MDE.

Zuora, November 19, 2015, www.zuora.com/2015/11/19/how-do-you-price-a-connected-device. Everything that we formerly electrified Kevin Kelly, The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future (New York: Viking, 2016). This ‘as-a-service’ approach can give the supplier McKinsey & Company, “Unlocking the Potential of the Internet of Things,” www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-internet-of-things-the-value-of-digitizing-the-physical-world. CHAPTER 8: THE END OF OWNERSHIP digitally enhanced products, services, and experiences International Data Corporation, “IDC Sees the Dawn of the DX Economy and the Rise of the Digitally Native Enterprise, International Data Corporation,” November 1, 2016, www.idc.com/getdoc.jsp?containerId=prUS41888916.

Superman (film), 41 Baxter, Robbie Kellman, 29 Ben Hur (film), 38 Benioff, Marc, 5–6, 165 Berg, Björn, 110–11 Berger, Edgar, 47 Bezos, Jeff, 26 Birchbox, 23, 28, 34 Bishop, Bill, 66 BlaBlaCar, 62–63 Blockbuster, 3, 17 blockbuster business model, 38 Boll & Branch, 23 Bonnington, Christina, 52 Bonobos, 33 Borders, 17 Born to Run (album), 38 Bowie, David, 47 BowieNet, 47 Box, 2, 13–14, 167–68, 185, 190, 192 brick and mortar retail, 22–24 Budget, 3 budgeting for recurring expenses, 185 BuzzFeed, 66, 67, 71 cable industry, opportunity cord cutting presents for, 44–46 Cadillac, 52 capability-driven growth, and packaging, 153–54 Carey, Mariah, 38 Carr, Nicholas, 83, 96 Casablanca (film), 37 Casper, 23 Caterpillar, 99–100 channels, 146, 147–48 Chegg, 117 Chrono Therapeutics, 107 Chrysler, 57 churn accounting for, 181 reducing, 161–62 subscription churn rate statistics, 218–20 Circuit City, 17 Cisco, 93–96 CLEAR, 167 Columbia House, 28–29 Columbia Records, 38 Comcast, 46 Concur, 190 construction industry, 98–100 consumption-driven growth, and pricing, 153 content creation, 41 continuous innovation, 133–42 Gmail and, 133–35 Graze and, 137–38 Manifesto for Agile Software Development and, 135–36 market research as element of service, 137–38 Netflix and, 138–40 never-ending products and, 135 Starbucks’ subscriber IDs and, 140–42 sustainable development, creating environment to support, 135–36 user data and, 138–40 West’s The Life of Pablo album and, 136–37 cost plus pricing, 151 costs, recurring, 181 Cowboy Bebop (anime), 42 Cox, 46 cross-selling, 164–67 Crunchyroll, 42–43 customer-centric organizational mindset, 19–21 customer-first focus, 18 customer relationship management (CRM) databases, 18, 193 customers, 17–21 business model shift to circular, dynamic relationship with, 19–21 direct ongoing relationship with, establishing, 18 initial customers, acquisition of, 159–61 mindset of, 17 ownership not important to, 17 customer service departments, 16 CVS, 115 Daily Beast, The, 66 Daily Mail, 169 DAZN, 43–44 Dediu, Horace, 56 delivery service, 34 Dell, Michael, 16 Deploy element, of PADRE operating model, 203 DeRamus, Reid, 43 Digital Equipment Corporation, 56 digital transformation, 11–14, 19–21 digital twins of physical machinery, 104–6 Disney, 13, 107 Doctor, Ken, 69–70, 71 DocuSign, 163–64 Dollar Shave Club, 28, 33 double-entry bookkeeping, 176–79 Dragon Ball Z (anime), 42 Dropbox, 2 Drucker, Peter, 16 Economist, The, 63, 74, 79, 119 education, 116–17 Elgan, Mike, 32 EMEA growth, 220–21 ENGIE, 119 enterprise resource planning (ERP) systems, 15–16, 189–95 enthusiast networks, 72–73 Enthusiast Network (TEN), 72–73 ESPN, 44–45 Expand element, of PADRE operating model, 204 Fabletics, 28 Facebook, 13, 67–68, 77 Fender, 30–32 Fender Play, 31 Fender Tune, 31 Field, Marshall, 18 finance, 129, 174–89 budgeting for recurring expenses, 185 finance team, role of, 129, 187–88 Growth Efficiency Index (GEI), 186 growth versus profitability, 182–84 subscription economy income statements, 179–82 trade-off between recurring expenses and growth expenses, managing, 185–86 traditional financial model income statements, problems with, 176–79 finance industry, 120–21 Financial Times, 73–74, 79, 198 fish model, 85–86 Fletcher, Anthony, 137 flexible consumption models, 118 FloorInMotion, 108, 112 Fluidware, 171 Ford, 52, 58–59 Ford, Henry, 14–15, 58–59 Forrester Research, 17 Fortune, 1 Fortune 500 companies, 11–13 characteristics of successful, 12–13 life expectancy of, 11 freemium model, 76 Freshly, 28 Friedland, Jonathan, 139 gaming industry, 125–27 Garrett, Mark, 80, 81, 82, 87–88 Gartner, 55, 84, 130, 209 General Electric (GE), 12, 104–6 General Motors (GM), 55–56, 57, 148 Gerber Technology, 112 Gilette, 33 Girouard, Mike, 94–95 Glow (show), 41 Gmail, 2, 133–35 Godless (show), 41 Gold, Carl, 114, 210 Goldman Sachs, 27 Google, 13, 67–68, 77, 133–35, 145 government, 116 Graze, 28, 137–38 Greenberg, Reid, 24 Grossman-Cohen, Rebecca, 77 growth costs, 182 Growth Efficiency Index (GEI), 186 growth hackers, 145 Guardian, The, 65–66 guided selling model, 164 Hajman, Pavel, 36 hardware technology companies, 93–96 Harry’s, 33 Hastings, Reed, 3, 40 HBR, 121 health care industry, 115 HealthIQ, 117 Heidelberg Druckmaschinen, 112 Hertz, 3 Heston, Charlton, 38 Hive, 106 HomeAway, 120 Honeywell, 108 Houghton Mifflin Harcourt, 117 House of Cards (show), 139–40 “How Investors React When Companies Announce They’re Moving to a SaaS Model” (HBR), 93 HP Enterprise, 90 Husqvarna, 35–36 hybrid sales model, 163 Hyundai, 51 IBM, 12, 56, 90 ID for customers, 26–27, 140–42, 146 Iger, Bob, 13 income statements for subscription economy (See income statements for subscription economy) traditional, 176–79 income statements for subscription economy, 179–82 annual recurring revenue, 179–81 churn, 181 growth costs, 182 recurring costs, 181 recurring profit margins, 182 industrial internet, 105 The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future (Kelly), 111 Information, The, 66 innovation. See continuous innovation insurance industry, 117–18 Intel, 108 international sales, 168–70 Internet of Things (IOT), 101–13 construction industry and, 98–100 data inherent in connected devices, sales of, 109–10 defined, 102 digital twins of physical machinery and, 104–6 efficiency stage of, 102 focusing on outcomes instead of products, 106–11 manufacturing industry and, 103–13 new business models in response to, 112–13 sensors, collection and transmission of data from, 101–2 service-level agreements and, 97–98, 106 Invoca, 172 IOT. See Internet of Things (IOT) iPhone, 3 IT department, 129–30, 189–99 business insights and, 198 evolving IT architecture to meet subscription economy needs, 197–99 financials and, 192 legacy IT architecture, structure of and problems associated with, 189–97 pricing and packaging and, 190–91, 199 renewals and, 191 sales to different customer groups and, 191–92 subscribers/customer metrics and, 190, 198 “It Doesn’t Matter” (Carr), 83 Jankowski, Simona, 26, 27 Janzer, Anne, 130 Jaws (film), 38 JCPenney, 22 Jobs, Steve, 39, 47 Johnny Walker Blue Label, 107 Johnson, Kevin, 33 just in time inventory, 16 Kaplan, 117 Kaplan, Ethan, 30–31 Katzenberg, Jeffrey, 46 Kelly, Kevin, 111 Kern, Mac, 60–61 Kmart, 22 Komatsu, 98–99 Kramer, Kelly, 95–96 Kreisky, Peter, 78 Lah, Thomas, 85–86, 96 Lean Startup method, 48 leasing versus subscription model, for automobiles, 52–53 Lemonade, 118 Lessin, Jessica, 66, 68 Levie, Aaron, 167–68, 198–99 Life of Pablo, The (album), 48, 136–37 linear order-to-cash systems, 192–97 livestreaming, 42 LL Cool J, 101 LO3 Energy, 119 Loot Crate, 28 Lotto, Mark, 75 Lucas, George, 136 Lyft, 3, 54–55 Lynda.com, 31, 117 MacKenzie, Angus, 72 McGraw-Hill, 12–13 McKinsey, 11, 34, 98, 112–13, 165, 173, 218, 221 Macy’s, 14 Magellan Health, 115 Main, Andy, 121–22 malls, 17, 22, 34–35 Manifesto for Agile Software Development, 135–36 manufacturing industry, 100–101, 103–13 digital twins of physical machinery and, 104–6 focusing on outcomes instead of products, 106–11 future of, 111–13 margins, 15 marketing, 130–31, 143–55 experiences, communicating brand through, 145, 149 one-on-one marketing, 145–46 optimizing growth within service itself, 145 place (channels) and, 146, 147–48 pricing and packaging and, 146, 151–54 promotion and, 146, 149–51 subscriber IDs and, 146 Three Rooms mental model of storytelling and, 149–51 traditional role and techniques of, 143–44 Marketo, 190 MarketTools, 171 Marshall, John, 68 Martin-Flickinger, Gerri, 141 Mashable, 66 mass production, 37 media industry, 37–50 community, building, 43 content creation, investment in, 41 continuous innovation and, 136–37 Hollywood, historical business model of, 37–38 livestreaming, 42 mass production of movies in, 37 music industry, historical business model of, 38–39 music streaming services, 46–50 Netflix show, business model for, 41 portfolio effect and, 37, 41 streaming services and, 39–50 subscription video on demand (SVOD), 42–46 Meeker, Mary, 21 Membership Economy, The (Baxter), 29 Merry Christmas (album), 38 Metallica, 39 Metromile, 118 Microsoft, 56, 83, 89 minimum viable product, 48 ModCloth, 23 Moffett, Craig, 45 Molotov, 46 monetizing longtail content business model, 38 Money element, of PADRE operating model, 204 MOOCs (massive open online courses), 117 Mooney, Andy, 31–32 Motor Trend, 72–73, 79 MoviePass, 2 Mukherjee, Subrata, 74 multiple of three factors, for gauging reader engagement, 74 music streaming services, 46–50 BowieNet and, 47 minimum viable product and, 48 Prince’s NPG Music Club and, 47–48, 49–50 virtuous feedback loop, creating, 48–49 My Royal Canin, 118 Napster, 39 NCR, 13 negative option model, 28–30 Nest, 119 net account growth, 211–13 Netflix, 2, 3, 13, 18–19, 39, 40–41, 69, 139–40, 145, 161, 198 Newman, Nic, 69 New Relic, 166–67 newspaper industry, 65–79 ad-based business model, decline of, 66–70 digital subscribers, growth in, 65–66 enthusiast networks, 72–73 freemium model and, 76 multiple of three factors, for gauging reader engagement, 74 New York Times, subscription-first model of, 75–79 pricing agility and, 73–74 print versus digital myths, 70–71 reader’s wants and needs, prioritizing, 70–71 subscription/ad revenue mix, flipping, 75–76 New Yorker, The, 65, 66–67 New York Times, The, 65, 72–73, 75–79 Ngenic, 109–11 Nichols, Jim, 52 Nordstrom, 33 NPG Music Club, 47–48, 49–50 O’Brien, Mike, 51 Okta, 3 One Medical, 115 one-on-one marketing, 145–46 OnStar, 55–56, 148 Oracle, 4, 83, 190 Pacioli, Luca, 176–78 packaging.


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The End of Ownership: Personal Property in the Digital Economy by Aaron Perzanowski, Jason Schultz

3D printing, Airbnb, anti-communist, barriers to entry, bitcoin, blockchain, carbon footprint, cloud computing, conceptual framework, crowdsourcing, cryptocurrency, Donald Trump, Edward Snowden, en.wikipedia.org, endowment effect, Firefox, George Akerlof, Hush-A-Phone, information asymmetry, intangible asset, Internet Archive, Internet of things, Isaac Newton, loss aversion, Marc Andreessen, means of production, minimum wage unemployment, new economy, peer-to-peer, price discrimination, Richard Thaler, ride hailing / ride sharing, rolodex, self-driving car, sharing economy, Silicon Valley, software as a service, software patent, software studies, speech recognition, Steve Jobs, subscription business, telemarketer, The Market for Lemons, transaction costs, winner-take-all economy

Classification: LCC K783 .P47 2016 | DDC 346.04/8—dc23 LC record available at http://lccn.loc.gov/2016013180 ePub Version 1.0 For Clem, who at least gets my record collection—AP For Kate & Elliott, my two favorite booksneaks—JS Table of Contents Series page Title page Copyright page Dedication Acknowledgments 1 Introduction 2 Property and the Exhaustion Principle 3 Copies, Clouds, and Streams 4 Ownership and the Fine Print 5 The “Buy Now” Lie 6 The Promise and Perils of Digital Libraries 7 DRM and the Secret War inside Your Devices 8 The Internet of Things You Don’t Own 9 Patents and the Ordinary Pursuits of Life 10 Ownership’s Uncertain Future Index List of Illustrations Figure 5.1 An example of a MediaShop product page Figure 5.2 Percentage of respondents who believe the “Buy Now” button confers rights Figure 5.3 Percentage of respondents who express a strong or moderate preference for rights Figure 5.4 Examples of MediaShop short notices Figure 5.5 Percentage of respondents who believe the short notice confers rights Acknowledgments This project grew out of a series of our academic articles: “Digital Exhaustion,” UCLA Law Review 58 (2011): 889–946; “Copyright Exhaustion and the Personal Use Dilemma,” Minnesota Law Review 96 (2012): 2067–2143; “Legislating Digital Exhaustion,” Berkeley Technology Law Journal 28 (2015): 1535–1557; and “Reconciling Personal and Intellectual Property,” Notre Dame Law Review 90 (2015): 1213–1263.

From there, we turn our attention from individuals to the implications of the licensing model for an important group of institutional actors, public libraries. Next, we look at how the licensing model, which was largely confined to digital media for decades, has been exported to the world of physical goods. That transition starts with DRM technology and the laws that protect it. But with the emergence of the Internet of Things, the question of our relationship with the devices around us—and sometimes in us—is more pressing than ever. Then we explore another legal avenue for exerting control over how we use the objects we buy—the patent system—and how the ongoing fight over so-called post-sale restrictions threatens ownership. Finally, we will outline an agenda to reconcile stable, reliable personal property rights with our inevitably digital future.

Park & Sons Co. v. Hartman, 153 F. 24, 39 (6th Cir. 1907); Miles Med. Co. v. John D. Park & Sons Co., 220 U.S. 373 (1911); Van Houweling, “The New Servitudes.” But see Glen O. Robinson, “Personal Property Servitudes,” University of Chicago Law Review 71 (Fall 2004): 1449–1523 (arguing in favor of servitudes on personal property). 7. Christina Mulligan, “Personal Property Servitudes on the Internet of Things,” Georgia Law Review (forthcoming). 8. John D. Park & Sons Co. v. Hartman, 153 F. 24, 39 (6th Cir. 1907). 9. J. K. Rowling, Harry Potter and the Deathly Hallows (New York: Arthur A. Levine Books, 2007), 417–418. 10. Exhaustion also plays a role in trademark law, where it permits the resale of authentic goods without the trademark holder’s permission. See generally Yvette Joy Liebesman and Benjamin Wilson, “The Mark of a Resold Good,” George Mason Law Review 20 (Fall 2012): 157–205. 11.


The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

Bayesian statistics, business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, disruptive innovation, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, lifelogging, linked data, longitudinal study, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

Elwood, S. and Leszczynski, A. (2011) ‘Privacy reconsidered: new representations, data practices, and the geoweb’, Geoforum, 42: 6–15. European Commission (2012) Commission Proposes a Comprehensive Reform of the Data Protection Rules, 25 January, http://ec.europa.eu/justice/newsroom/data-protection/news/120125_en.htm (last accessed 6 August 2013). Farber, D. (2013) ‘Counting the Internet of things in real time’, CNet, 30 July, http://news.cnet.com/8301-11386_3-57596162-76/counting-the-internet-of-things-in-real-time/ (last accessed 18 September 2013). Farber, M., Cameron, M., Ellis, C. and Sullivan, J. (2011) Massive Data Analytics and the Cloud: A Revolution in Intelligence Analysis. Booz Allen Hamilton. http://www.boozallen.com/media/file/MassiveData.pdf (last accessed 16 July 2013). Federal Trade Commission (2012) Protecting Consumer Privacy in an Era of Rapid Change, http://www.ftc.gov/os/2012/03/120326privacyreport.pdf (last accessed 14 October 2013).

Rogers, S. (2013) ‘Twitter’s languages of New York mapped’, Guardian, 21 February, http://www.guardian.co.uk/news/datablog/interactive/2013/feb/21/twitter-languages-new-yorkmapped (last accessed 3 April 2013). Rooney, B. (2012) ‘Big data’s big problem: little talent’, Wall Street Journal: Tech Europe, 26 April, http://blogs.wsj.com/tech-europe/2012/04/26/big-datas-big-problem-little-talent/ (last accessed 12 November 2012). Rose, A. (2013) ‘The internet of things has arrived – and so have massive security issues’, Wired, 11 January, http://www.wired.com/opinion/2013/01/securing-the-internet-of-things/ (last accessed 7 August 2013). Rose, N. (1996) Inventing Our Selves: Psychology, Power and Personhood. Cambridge University Press, Cambridge. Rosenberg, D. (2013) ‘Data before the fact’, in L. Gitelman (ed.), ‘Raw Data’ is an Oxymoron. MIT Press, Cambridge, MA, pp. 15–40. Rubenking, N.J. (2013) ‘Privacy is dead. The NSA killed it.

Rather than being scarce and limited in access, the production of data is increasingly becoming a deluge; a wide, deep torrent of timely, varied, resolute and relational data that are relatively low in cost and, outside of business, increasingly open and accessible. A data revolution is underway, one that is already reshaping how knowledge is produced, business conducted, and governance enacted. This revolution is founded on the latest wave of information and communication technologies (ICTs), such as the plethora of digital devices encountered in homes, workplaces and public spaces; mobile, distributed and cloud computing; social media; and the internet of things (internetworked sensors and devices). These new technical media and platforms are leading to ever more aspects of everyday life – work, consumption, travel, communication, leisure – and the worlds we inhabit to be captured as data and mediated through data-driven technologies. Moreover, they are materially and discursively reconfiguring the production, circulation and interpretation of data, producing what has been termed ‘big data’ – vast quantities of dynamic, varied digital data that are easily conjoined, shared and distributed across ICT networks, and analysed by a new generation of data analytics designed to cope with data abundance as opposed to data scarcity.


pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

the Oura ring: See: http://ouraring.com. (Author note: Peter’s VC firm is an investor.) John Romkey: Ryan Nagelhout, Smart Machines and the Internet of Things (Rosen Publishing, 2016). Neil Gross: Neil Gross, “The Earth Will Don an Electronic Skin,”BusinessWeek, August 29, 1999. In 2009, the number of devices connected to the Internet: Dave Evans, “The Internet of Things,” Cisco.com, April 2011. See: https://www.cisco.com/c/dam/en_us/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf. By 2015, all this progress added up to 15 billion: Louis Columbus, “Roundup of Internet of Things Forecasts and Market Estimates, 2016,” Forbes.com, no. 27 (2016). See: https://www.forbes.com/sites/louiscolumbus/2016/11/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2016/#32a1a5ba292d. Nor will we stop there: For a full breakdown of the Accenture report, see: https://newsroom.accenture.com/subjects/management-consulting/industrial-internet-of-things-will-boost-economic-growth-but-greater-government-and-business-action-needed-to-fulfill-its-potential-finds-accenture.htm.

See: https://www.bloomberg.com/news/features/2019-07-18/amazon-s-most-ambitious-research-project-is-a-convenience-store. New York Times describes passing through the store’s turnstiles: Wingfield, “Inside Amazon Go.” McKinsey estimates automated checkout will save retailers: “The Internet of Things: Mapping the Value Beyond the Hype,” McKinsey & Company, June 2015. See: https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/The%20Internet%20of%20Things%20The%20value%20of%20digitizing%20the%20physical%20world/The-Internet-of-things-Mapping-the-value-beyond-the-hype.ashx. the San Francisco startup v7labs: “This AI Startup Wants to Automate Every Store Like Amazon Go,” Fast Company, November 9, 2017. See: https://www.fastcompany.com/40493622/this-ai-startup-wants-to-automate-every-store-like-amazon-go.

In studies conducted by independent labs, this combination of better imaging and higher sampling speed makes the ring 99 percent accurate compared to medical-grade heart rate trackers, and 98 percent accurate for heart rate variability. Twenty years ago, sensors this accurate would have cost millions and required a decent-sized room to house. Today, the Oura costs around $300 and sits on your finger—which is the impact that exponential growth has had on sensors. The street name for this network of sensors is the “Internet of Things” (IoT), the growing network of interconnected smart devices that will soon span the globe. And it’s worth tracing the evolution of this revolution to understand how far we’ve come. In 1989, inventor John Romkey connected a Sunbeam toaster to the internet, making it the very first IoT device. Ten years later, sociologist Neil Gross saw the writing on the wall and made a now famous prediction in the pages of BusinessWeek: “In the next century, planet earth will don an electric skin.


pages: 477 words: 75,408

The Economic Singularity: Artificial Intelligence and the Death of Capitalism by Calum Chace

3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, Douglas Engelbart, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Flynn Effect, full employment, future of work, gender pay gap, gig economy, Google Glasses, Google X / Alphabet X, ImageNet competition, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, lifelogging, lump of labour, Lyft, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, new economy, Occupy movement, Oculus Rift, PageRank, pattern recognition, post scarcity, post-industrial society, post-work, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Sam Altman, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, The Future of Employment, Thomas Malthus, transaction costs, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, universal basic income, Vernor Vinge, working-age population, Y Combinator, young professional

Its full-blooded arrival coincides with the take-off of a series of other technologies. They are all driven at least in part by AI, and they will all impact the way our societies evolve. Because they will all unfold in different ways and at different speeds, it is impossible to predict exactly what the impact of these interlacing technologies will be, other than that it will be profound. The Internet of Things The Internet of Things (IoT) has been talked about for years – the term was coined by British entrepreneur Kevin Ashby back in 1999.[cxxxiii] Indeed it has been around for long enough to have acquired a selection of synonyms. GE calls it the Industrial Internet, Cisco calls it the Internet of Everything, and IBM calls it Smarter Planet. The German government calls it the Industry 4.0[cxxxiv], the other three being the introduction of steam, electricity, and digital technology.

The information revolution does the same, providing farmers with crops that are more resilient in the face of weather, pests and weeds, and allowing them to sow, cultivate and harvest their crops far more accurately with satellite navigation. Along with the uncertainty about the start date of the information revolution, there is disagreement about how distinct it is from the industrial revolution. The Internet of Things (IoT) is a phenomenon of the information revolution which we will look at in more detail in chapter 3.7. Klaus Schwab, founder and executive chairman of the World Economic Forum which hosts the annual meeting of the global elite in Davos, calls the IoT the fourth industrial revolution.[x] This seems to me to under-state the importance of the IoT, and also to separate it from all the other digital revolutions which comprise the information revolution, including, of course, artificial intelligence. 2.3 – The Automation story so far The mechanisation of agriculture The particular aspect of the industrial and information revolutions which concerns us in this book is automation.

There are also numerous smaller players, of which perhaps the most interesting is Viv (from the Latin for “life”), a system developed by the original creators of Siri.[cxli] They span Siri out of a DARPA-funded research project, taking the name from Sigrid, a Scandinavian word meaning both “victory” and “beauty”, and sold it to Steve Jobs in 2011. Artificial intelligences will govern most things in our environment, and something like Siri will be our intermediary, negotiating with and filtering out most of the Internet of Things. Although we may not notice it, this will be a blessed relief. Imagine having to negotiate a world where every AI-enabled device has direct access to you, with every chair and handrail pitching their virtues to you, and every shop screaming at you to buy something. This dystopia was captured in the famous shopping mall scene in the 2002 film “Minority Report”, and more laconically in Douglas Adam's peerless “Hitchhiker's Guide to the Galaxy” series, where the Corporation that produces the eponymous guide has installed talking lifts, known as happy vertical people transporters.


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Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl

Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic trading, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, book scanning, borderless world, call centre, cellular automata, Claude Shannon: information theory, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, drone strike, Elon Musk, Flash crash, friendly AI, game design, global village, Google X / Alphabet X, hive mind, industrial robot, information retrieval, Internet of things, iterative process, Jaron Lanier, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, life extension, Loebner Prize, Marc Andreessen, Mark Zuckerberg, Menlo Park, natural language processing, Norbert Wiener, out of africa, PageRank, pattern recognition, Ray Kurzweil, recommendation engine, remote working, RFID, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, too big to fail, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!

As with many newer smart gadgets, XCoffee was connected to the Web, and was therefore part of the so-called ‘Internet of Things’. But to me it is closer to an example of what hardware geeks would call a ‘hack’ – a term which colloquially refers to a clever solution to a tricky problem. The prerequisite of what we would today think of as a smart device (fondly described by MIT’s Media Lab as a ‘thing that thinks’) is that it exists as a self-governing feedback loop, capable of operating autonomously without a lot of human intervention. The Internet of Things is not simply about ‘things’ connected to the Internet. The traditional Internet was there to allow humans to carry out tasks, such as searching, downloading music, or reading information. The Internet of Things, on the other hand, is designed for non-human entities to communicate, which is why a growing number of people prefer to talk about M2M communication, meaning ‘machine-to-machine’.

., ‘Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos from the World Wide Web’, AAAI, 2015: umiacs.umd.edu/~yzyang/paper/YouCookMani_CameraReady.pdf 15 Rashid, Rick, ‘How Technology Can Bridge Language Gaps’, Microsoft Research, 2012: research.microsoft.com/en-us/research/stories/speech-to-speech.aspx Chapter 3: Intelligence Is all Around Us 1 Warwick, Kevin, ‘Cyborg 1.0’, Wired, 1 February 2000: archive.wired.com/wired/archive/8.02/warwick.html 2 Hutchings, Emma, ‘Lenovo’s Smart Shoes Display Your Mood on Tiny Screen’, PSFK, 1 June 2015: psfk.com/2015/06/lenovo-smart-shoes-lenovo-tech-world.html 3 Dormehl, Luke, ‘Internet of Things: It’s All Coming Together for a Tech Revolution’, Guardian, 8 June 2015: theguardian.com/technology/2014/jun/08/internet-of-things-coming-together-tech-revolution 4 http://americanhistory.si.edu/lighting/19thcent/consq19.htm 5 Stafford-Fraser, Quentin, ‘The Trojan Room Coffee Pot: A (Non-Technical) Biography’: cl.cam.ac.uk/coffee/qsf/coffee.html 6 Woods, Michael and Woods, Mary: Ancient Machines: From Wedges to Waterwheels (Minneapolis: Runestone Press, 2000). 7 Wiener, Norbert, The Human Use of Human Beings (New York: Doubleday, 1954). 8 Freeman, Walter, ‘W.

By 1938, the former US president Franklin Roosevelt, speaking in Barnesville, Georgia, proclaimed electricity ‘a modern necessity of life’. Could we be at the start of a similarly transformative journey for smart devices? Perhaps so. Certainly, the rise of mobile wireless networks means that devices are more portable than ever. The dream of what is sometimes (and quite clumsily) termed the ‘Internet of Things’ is that intelligent hardware will become as much a ‘modern necessity of life’ in the twenty-first century as electricity did 100 years ago. Where once we electrified, now we will cognitise. Right now, hype is so strong around the field of smart devices that analysts at Ericsson predict that there will be in the region of 50 billion smart devices around the world by 2020: a figure that works out as approximately 6.8 per person.


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Places of the Heart: The Psychogeography of Everyday Life by Colin Ellard

augmented reality, Benoit Mandelbrot, Berlin Wall, Broken windows theory, Buckminster Fuller, carbon footprint, commoditize, crowdsourcing, Frank Gehry, Google Glasses, Guggenheim Bilbao, haute couture, Howard Rheingold, Internet of things, Jaron Lanier, mandelbrot fractal, Marshall McLuhan, Masdar, mass immigration, megastructure, more computing power than Apollo, Oculus Rift, Peter Eisenman, RFID, Richard Florida, risk tolerance, sentiment analysis, smart cities, starchitect, the built environment, theory of mind, urban decay, urban planning, urban sprawl, Victor Gruen

Our phones have opened up untold new possibilities for understanding the world, some of them good and others more worrisome, but because the phones are personal, the nodes of this great, connected network of devices still represent individual human beings. The next frontier in the cybernetic transformation of space and place is not just focused on relationships between people, or even between people and the landscapes they inhabit. In the much-vaunted Internet of Things, places themselves are entirely penetrated by devices and sensors, still ostensibly in the service of human beings, but now with the central focus on the things themselves and their connections, rather than the flesh-and-blood actors who animate the scene. Many news media accounts might lead us to believe that what is new about the Internet of Things is that the appliances and gadgets of our lives will begin to talk to one another. Our carbon monoxide detectors will commune with our furnaces, knowing enough to shut things down when a lethal gas is detected in the air in our houses.

It isn’t just the marvel of the modern portable phone that fills the airwaves with data related to our movements and thoughts, though. The built world has become increasingly flooded with sensors. Surveillance cameras have been around for years, but now they can be combined with technology that can measure our facial expressions, our patterns of gaze, our heart and breathing rates, and our body temperature. The burgeoning “Internet of Things”13 joins together every kind of device and structure from the home thermostat to traffic control devices and mass transit ticket systems in a massive electronic skein of information that persistently watches, measures, and adjusts the relationships between people and their everyday settings. The latest iteration of wearable computing, and the kind that is likely to have the most profound impact of all on our everyday relationships with places, comes in the form of devices that we wear in front of our eyes.

But it is also symptomatic of more profound change: we may no longer care nearly as much about what our surroundings look like because we are not paying attention to them as we used to. In a very real sense, we are no longer there as we used to be, and our physical surroundings are no longer as real as they used to be. The trend toward hybridization of real and virtual spaces in urban environments also has ideological roots. Indeed, though some are touting the new trends toward wired cities and the Internet of Things as ushering in the bare beginnings of a new kind of merger between information technologies and architecture, this trend has actually been under way for some time. Just as electronic connectedness enables globalization by discounting the importance of physical space and dimension in many of our everyday dealings with life, the homogenization of architectural design parallels this trend in the arena of bricks, steel, and concrete.


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Age of Context: Mobile, Sensors, Data and the Future of Privacy by Robert Scoble, Shel Israel

Albert Einstein, Apple II, augmented reality, call centre, Chelsea Manning, cloud computing, connected car, Edward Snowden, Edward Thorp, Elon Musk, factory automation, Filter Bubble, G4S, Google Earth, Google Glasses, Internet of things, job automation, John Markoff, Kickstarter, lifelogging, Marc Andreessen, Mars Rover, Menlo Park, Metcalfe’s law, New Urbanism, PageRank, pattern recognition, RFID, ride hailing / ride sharing, Robert Metcalfe, Saturday Night Live, self-driving car, sensor fusion, Silicon Valley, Skype, smart grid, social graph, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Tesla Model S, Tim Cook: Apple, ubercab, urban planning, Zipcar

Soon the smartest operators of supermarkets, dry cleaners and other merchants will Uberize their services as well. Connecting All the Things We’ve talked about the Internet of Things. We believe that a part of it will be households of connected things. Anything in your home that has an on-off switch will be interconnected. All glass objects will be connected as well. Ubiquitous sensors will be a part of it as well, as, of course, will your front door. All of these things will communicate with you wherever you are, through some form of PCA. They will also connect to emergency services, utilities and the entire Internet of Things. Everywhere we looked we found companies that were building little pieces of the new contextual household. Belkin and Philips, for example, are working on getting their many home products to talk with each other and with all your other fixtures and devices.

Not just the mobile phones in our pockets, but different kinds of computers—our watches, our cameras, our cars, our refrigerators, our toothbrushes. Every aspect of our lives is somehow on the network, a wireless network, and in the cloud. This is the third wave of computing. Research firm IDC reports that there will be 3.5 billion networked products by 2015. Compare that to 1.7 billion networked PCs and it’s clear that the “Internet of Things” has arrived. With it, and with everything connected to the network, we enter an amazing new world of possibilities. The big change here is that technology is becoming intuitive. It is starting to understand where you are and where you are likely to be going, and it can help you on your way. Connected technologies make your customers happier and accordingly, your revenues bigger. In the connected world, customers are no longer just a number or account; they are unique human beings with a distinct set of needs.

This device also has access to all of humankind’s collected knowledge. Through the use of many different types of sensors, our mobile devices now emulate three of our five senses. Camera sensors give them eyes, and microphone sensors serve as ears; capacitive sensors enable them to feel our touch on their screens. They can’t yet detect fragrance—but our guess is that such a capability is coming soon. The so-called Internet of Things enables many common appliances, fixtures and devices to communicate with systems due to the availability of radical new low-cost and miniaturized sensors. Microsoft Kinect for Xbox, for example, has a 3D sensor that can see your heartbeat just by looking at your skin. When we talk about “the system knowing about you,” that knowledge depends on machine learning and database computation breakthroughs that couldn’t be imagined when Microsoft researcher Jim Gray turned on Microsoft’s first terabyte database back in December 1997.


pages: 285 words: 58,517

The Network Imperative: How to Survive and Grow in the Age of Digital Business Models by Barry Libert, Megan Beck

active measures, Airbnb, Amazon Web Services, asset allocation, autonomous vehicles, big data - Walmart - Pop Tarts, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, crowdsourcing, disintermediation, diversification, Douglas Engelbart, Douglas Engelbart, future of work, Google Glasses, Google X / Alphabet X, Infrastructure as a Service, intangible asset, Internet of things, invention of writing, inventory management, iterative process, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, late fees, Lyft, Mark Zuckerberg, Oculus Rift, pirate software, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, software as a service, software patent, Steve Jobs, subscription business, TaskRabbit, Travis Kalanick, uber lyft, Wall-E, women in the workforce, Zipcar

Social media and messaging apps keep refugees in touch with family back home and others making the journey. They enable people to share information about the activities of relief agencies and the locations of food, supplies, shelter, and charging stations. Cloud technology helps people access their important information and documents wherever they are. By tracking the best routes between countries via global positioning, smartphones have even become part of the internet of things. This story of refugees and their smartphones contains a key message for business leaders: for most of the world, technology is as essential to life as food and water, and it is changing everything. No industry is untouched by the technical revolution, and technology is transforming the back end, the front end, and everything in between—not only manufacturing, not only resource planning, not only marketing and customer relationships, but also the very business models that companies use to create value.

In business, understanding and using digital technology are as important as understanding how profit and loss work. You can’t expect to build a great business without it. However, even though many leaders are beginning to incorporate technology piecemeal into various parts of their organizations, few are creating business models that take advantage of digital technology such as social, mobile, cloud, big data analytics, and the internet of things. Digitally enabled business models offer many advantages to organizations and those they serve. Here are a few of them. Convenience. When customers are served through digital means, such as online or through an app, they can interact with the organization on their own terms and at their own convenience. The company benefits as well, because it needs fewer physical assets, such as tangible products and property, which depreciate and require maintenance.

The cloud provides centralized data storage and internet-based access to data, resources, and services. It enables people and businesses to improve utilization of resources, scale rapidly (both up and down), and access data and services through multiple channels and devices. Big data analytics. This refers to our ability to capture and analyze enormous sets of data, often in real time. Big data helps companies understand their users and themselves and make better decisions. The internet of things. This web of interconnected, internet-enabled devices lets us collect and use data in order to understand the world, accomplish new tasks, or improve our lives. For example, smart thermostats can learn our daily schedules and make the house toasty warm when we roll out of bed. Each of these technologies has value in its own right. But when organizations bring digital technology into their business models—the core way they deliver value to customers—their business values start multiplying.


pages: 304 words: 80,143

The Autonomous Revolution: Reclaiming the Future We’ve Sold to Machines by William Davidow, Michael Malone

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, agricultural Revolution, Airbnb, American Society of Civil Engineers: Report Card, Automated Insights, autonomous vehicles, basic income, bitcoin, blockchain, blue-collar work, Bob Noyce, business process, call centre, cashless society, citizen journalism, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Francis Fukuyama: the end of history, Geoffrey West, Santa Fe Institute, gig economy, Gini coefficient, Hyperloop, income inequality, industrial robot, Internet of things, invention of agriculture, invention of movable type, invention of the printing press, invisible hand, Jane Jacobs, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, license plate recognition, Lyft, Mark Zuckerberg, mass immigration, Network effects, new economy, peer-to-peer lending, QWERTY keyboard, ransomware, Richard Florida, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Simon Kuznets, Snapchat, speech recognition, Stuxnet, TaskRabbit, The Death and Life of Great American Cities, The Rise and Fall of American Growth, the scientific method, trade route, Turing test, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, urban planning, zero day, zero-sum game, Zipcar

IBM’s revenue increased from less than $2 billion in 1960 to more than $26 billion in 1980, a 14 percent growth rate.9 In the form of the microprocessor, the integrated circuit also spawned industries and applications that had never existed before—including cellular communications, personal computers, tablets, and the Internet of Things.10 New jobs followed. Today, the worldwide market for smartphones is approaching a half-trillion dollars.11 For personal computers and laptops, it’s about $200 billion.12 IHS Markit, a technology consulting firm, forecasts that the installed base of Internet of Things devices will reach 75.4 billion units by 2025, or about ten devices for every person on the planet. Estimates of the potential economic impact of these devices and associated services fall in the wide range of $2.7 to $6.2 trillion.13 Just as remarkable is that the semiconductor industry was able to achieve this mind-boggling level of growth while experiencing precipitous declines in the price per transistor.

“Global Revenue from Smartphone Sales from 2013 to 2018,” Statista, https://www.statista.com/statistics/237505/global-revenue-from-smartphones-since-2008/ (accessed June 26, 2019). 12. “Worldwide PC Spending Forecast,” Statista, https://www.statista.com/statistics/380434/worldwide-pc-spending-forecast/ (accessed June 26, 2019). 13. Louis Columbus, “Roundup of Internet of Things Forecasts and Market Estimates, 2016,” Forbes.com, November 27, 2016, https://www.forbes.com/sites/louiscolumbus/2016/11/27/roundup-of-internet-of-things-forecasts-and-market-estimates-2016/#2c6bdf93292d (accessed June 26, 2019). 14. Rachel Courtland, “How Much Did Early Transistors Cost?,” IEEE Spectrum, April 16, 2015, https://spectrum.ieee.org/tech-talk/semiconductors/devices/how-much-did-early-transistors-cost (accessed June 26, 2019); and “Handel Jones: Cost per Transistor Flat from 28 to 7nm,” AnandTech, June 15, 2016, https://forums.anandtech.com/threads/handel-jones-cost-per-transistor-flat-from-28-to-7nm.2476904/ (accessed June 26, 2019). 15.

In a work studded with arresting insights, few are more unsettling than the following, offered in the context of the authors’ discussion of artificial intelligence, and the “Autonomous Revolution” that is utterly upending the world of work, and therefore education and even human memory: The Autonomous Revolution will embed functional intelligence in autonomous machines. In practice, this means that the systematic development of human knowledge through education and work experience will have less value than it did in the past. Humans may continue to expand their knowledge and skills by accessing databases on the Internet, interfacing directly with the IoT (Internet of Things), or eventually having devices implanted in their bodies that will enhance their physical and mental abilities. But the real repositories of practical knowledge will shift to autonomous devices, which will learn much more quickly than people can. In situation after situation, automatons will substitute for humans. That sobering perspective recalls a story, perhaps apocryphal but nonetheless instructional, about a conversation sometime in the 1950s between Henry Ford II, the CEO of Ford Motor Company, and Walter Reuther, the head of the United Automobile Workers union.


pages: 409 words: 112,055

The Fifth Domain: Defending Our Country, Our Companies, and Ourselves in the Age of Cyber Threats by Richard A. Clarke, Robert K. Knake

A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, Amazon Web Services, autonomous vehicles, barriers to entry, bitcoin, Black Swan, blockchain, borderless world, business cycle, business intelligence, call centre, Cass Sunstein, cloud computing, cognitive bias, commoditize, computer vision, corporate governance, cryptocurrency, data acquisition, DevOps, don't be evil, Donald Trump, Edward Snowden, Exxon Valdez, global village, immigration reform, Infrastructure as a Service, Internet of things, Jeff Bezos, Julian Assange, Kubernetes, Mark Zuckerberg, Metcalfe’s law, MITM: man-in-the-middle, move fast and break things, move fast and break things, Network effects, open borders, platform as a service, Ponzi scheme, ransomware, Richard Thaler, Sand Hill Road, Schrödinger's Cat, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, Snapchat, software as a service, Steven Levy, Stuxnet, technoutopianism, Tim Cook: Apple, undersea cable, WikiLeaks, Y2K, zero day

The professional staff at the Federal Communications Commission was so concerned about the possibility of 5G being susceptible to hacking that they publicly published 132 questions to the communications industry about 5G security. They asked all about 5G security and authentication, encryption, physical security, DDoS attacks, patch management, and risk segmentation. Then they got to 5G and the Internet of Things. The FCC professionals began by noting the obvious: “It is widely expected that 5G networks will be used to connect the myriad devices, sensors and other elements that will form the Internet of Things (IoT). The anticipated diversity and complexity of these networks, how they interconnect, and the sheer number of discrete elements they will comprise raise concerns about the effective management of cyber threats.” They went on to note that “some IoT devices will have limited security features.”

Information Technology (IT): Hardware and software that create, store, retrieve, transmit, and manipulate data. Intercontinental Ballistic Missile (ICBM): A land-based, guided missile capable of traveling in excess of five thousand kilometers to deploy and detonate one or more nuclear weapons on an enemy target(s). Internet of Things (IoT): The expanding network of devices that are internet connected. This includes, but is not limited to, devices such as “smart” appliances, networked health-care equipment, and infrastructure monitoring electronics. In the context of cybersecurity, Internet of Things devices are notoriously insecure, and when used in an enterprise or otherwise sensitive setting, can present a significant security risk to an organization. Islamic State in Syria (ISIS): A name widely used to denote a terrorist organization that calls itself simply Islamic State, and that Arab governments call Daesh.

On the sidewalk there may be what looks like one of those Postal Service relay boxes where the letter carrier picks up the mail to be delivered on her route. The box will not, however, belong to the Postal Service. It will belong to a “phone company.” When this happens, 5G will have arrived near you. So too will a new set of cyber risks. The fifth generation of mobile telephony technology (5G) will supercharge the Internet of Things (IoT), and neither will be secure. If Verizon, AT&T, Sprint, and other carriers move ahead with their plans, they will initially spend a quarter trillion dollars dotting U.S. cities with these new 5G transmitters on poles and accompanying electrical transformers in what look like mailboxes. Globally it may cost as much as $5 trillion to install the 5G infrastructure. This is not going to be like when they shifted your mobile phone from 3G to 4G.


pages: 305 words: 93,091

The Art of Invisibility: The World's Most Famous Hacker Teaches You How to Be Safe in the Age of Big Brother and Big Data by Kevin Mitnick, Mikko Hypponen, Robert Vamosi

4chan, big-box store, bitcoin, blockchain, connected car, crowdsourcing, Edward Snowden, en.wikipedia.org, Firefox, Google Chrome, Google Earth, Internet of things, Kickstarter, license plate recognition, Mark Zuckerberg, MITM: man-in-the-middle, pattern recognition, ransomware, Ross Ulbricht, self-driving car, Silicon Valley, Skype, Snapchat, speech recognition, Tesla Model S, web application, WikiLeaks, zero day, Zimmermann PGP

One of your best defenses is to buy a Dropcam Pro so you can monitor your home when you’re not there.”5 With the advent of the Internet of Things, companies like Google are eager to colonize parts of it—to own the platforms that other products will use. In other words, these companies want devices developed by other companies to connect to their services and not someone else’s. Google owns both Dropcam and Nest, but they want other Internet of Things devices, such as smart lightbulbs and baby monitors, to connect to your Google account as well. The advantage of this, at least to Google, is that they get to collect more raw data about your personal habits (and this applies to any large company—Apple, Samsung, even Honeywell). In talking about the Internet of Things, computer security expert Bruce Schneier concluded in an interview, “This is very much like the computer field in the ’90s.

The culprit was a piece of malware called Mirai, a malicious program that scours the Internet looking for insecure Internet of Things devices, such as CCTV cameras, routers, DVRs, and baby monitors, to hijack and leverage in further attacks. Mirai attempts to take over the device by simple password guessing. If the attack is successful, the device is joined to a botnet where it lies in wait for instructions. Now with a simple one-line command, the botnet operator can instruct every device—hundreds of thousands or millions of them—to send data to a target site and flood it with information, forcing it to go offline. While you cannot stop hackers from launching DDoS attacks against others, you can become invisible to their botnets. The first item of business when deploying an Internet of Things device is to change the password to something hard to guess.

Each packet—or unit of data between source and destination—of voice, text, or data sent over 2G GSM could be decrypted in just a few minutes using the published table of keys.5 This was an extreme example, but the team considered it necessary; when Nohl and others had previously presented their findings to the carriers, their warnings fell on deaf ears. By demonstrating how they could crack 2G GSM encryption, they more or less forced the carriers to make the change. It is important to note that 2G still exists today, and carriers are considering selling access to their old 2G networks for use in Internet of Things devices (devices other than computers that connect to the Internet, such as your TV and refrigerator), which only need occasional data transmission. If this happens, we will need to make sure the devices themselves have end-to-end encryption because we know that 2G will not provide strong enough encryption by itself. Of course eavesdropping existed before mobile devices really took off. For Anita Busch, the nightmare started the morning of June 20, 2002, when she awoke to a neighbor’s urgent knock on her door.


Designing Search: UX Strategies for Ecommerce Success by Greg Nudelman, Pabini Gabriel-Petit

access to a mobile phone, Albert Einstein, AltaVista, augmented reality, barriers to entry, business intelligence, call centre, crowdsourcing, information retrieval, Internet of things, performance metric, QR code, recommendation engine, RFID, search engine result page, semantic web, Silicon Valley, social graph, social web, speech recognition, text mining, the map is not the territory, The Wisdom of Crowds, web application, zero-sum game, Zipcar

We can track spimes’ history of use and interact with them through a mesh of real and virtual worlds created by pervasive RFID and GPS tracking. Mobile picture search is certainly emerging as the input device of choice for connecting the real and the virtual worlds to create the Internet of Things (see sidebar). Internet of Things Internet of Things, also known as Internet of Objects, refers to a self-configuring wireless network connecting regular everyday objects to one another. Internet of things is a term attributed to Auto-ID Center, originally based at Massachusetts Institute of Technology (MIT). Eventually, Internet of things will connect 50-100 trillion of objects and be able to track their movement and state through the use of computers. Companies like Arrayent, Inc. have already developed practical, low-cost solutions that connect everyday things like thermostats to mobile phones and tablets.

On the other hand, a large tablet device such as iPad with an on-board camera or a pair of augmented reality glasses (coming soon to the gadget store near you) might be just the catalyst that will propel mobile near-field computing to the next level. Chapter 17, “Search on Tablet Devices: The Flight of Discovery” discusses some intriguing possibilities offered by the next generation of the tablet devices. In his book Ambient Findability, Peter Morville talks about the sensory overload, trust issues, and bad decisions that are sure to result from interactions with the Internet of things. However, it is hard to elude the siren’s call of such technology. It is now almost possible to use technology similar to that of Like.com to analyze every image and frame of video a mobile phone captures and tag it with text, GPS coordinates, time, and author, while at the same time cross-referencing this image with other images of the same place or similar things along with all the text tags, content, and links the entire world has added to this collection of images.

Customers could more easily find what they want—especially when they don’t know exactly what they want—with the result that they’d likely make more purchases on Amazon. —Pabini Gabriel-Petit References [1] Linden, Greg, Brent Smith, and Jeremy York. “Amazon.com Recommendations: Item-to-Item Collaborative Filtering.” [http://www.win.tue.nl/~laroyo/2L340/resources/Amazon-Recommendations.pdf] IEEE Internet Computing, January-February 2003. References Dodson, Sean. “The Internet of Things.” The Guardian, October 9, 2003. Jung, Carl Gustav. Man and His Symbols. New York: Dell, 1968. Morville, Peter. Ambient Findability. Sebastopol, California: O’Reilly, 2005. Nudelman, Greg. “Making $10,000 a Pixel: Optimizing Thumbnail Images in Search Results.” UXmatters, May 11, 2009. Retrieved July 26, 2009. Riflet, Guillaume. “Semapedia, or How to Link the Real World to Wikipedia.” Webtop Mania, August 26, 2008.


pages: 245 words: 72,893

How Democracy Ends by David Runciman

barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, Capital in the Twenty-First Century by Thomas Piketty, centre right, crowdsourcing, cuban missile crisis, Dominic Cummings, Donald Trump, Edward Snowden, first-past-the-post, Francis Fukuyama: the end of history, full employment, Internet of things, Joseph Schumpeter, Kickstarter, loss aversion, Mahatma Gandhi, Mark Zuckerberg, money: store of value / unit of account / medium of exchange, mutually assured destruction, Network effects, Norman Mailer, Panopticon Jeremy Bentham, Peter Thiel, quantitative easing, self-driving car, Silicon Valley, Steven Pinker, The Wisdom of Crowds, Travis Kalanick, universal basic income, Yogi Berra

It leaves technical governance on one side and direct political action on the other. There is little need for anything in between. This ‘pax technica’ comes after the ‘pax Americana’, when one very powerful state was needed to keep the world at peace. That era seems to be over anyway, thanks to Trump. Howard thinks we will do fine without it. ‘The internet of things,’ he writes, ‘will probably strengthen social cohesion to such a degree that when regular government structures break down or weaken, they can be repaired or substituted. In other words, people will continue using the internet of things to provide governance even when government is absent.’ 86 Libertarian, revolutionary or technocratic, these visions of the future have some features in common. One is their impatience to get there. Peter Thiel, the poster boy for Silicon Valley libertarianism, supported Trump for president because he wanted to shake things up.

Mason thinks we can go much further, towards a world where all the best things in life are free. These are not simply utopian visions. They originate with things that are already happening. Howard, showing the true impatience of someone who has seen the possibility of political transformation, dates the arrival of the politics of the future to around 2020, when the internet of things will kick into gear. That’s pretty much now. Yet Howard recognises this as only one possibility. There are many others. The subtitle of his book is ‘How the Internet of Things May Set Us Free or Lock Us Up’. Contained in the technology that has the power to liberate us are the worst-case scenarios, too, involving vast abuses of power, growing inequality and political paralysis. Putting our faith in the emancipatory potential of machines requires a huge leap of faith. To get to the best possible future we have to run the gauntlet of the worst.

He was writing in 1857. At the same time, Mason believes, he saw it coming. Mason recognises the utopian strain in this way of thinking. The Marx-was-right-after-all rhetoric will put many readers off. Haven’t we heard that one too many times before? But there are non-Marxist variants on the same line of thought. In Pax Technica (2015), a much less bombastic book than Mason’s, Philip N. Howard argues that the ‘internet of things’ – whereby machines come to share vast quantities of data directly with each other – will entirely transform contemporary politics. Once your fridge can talk to your light bulb, we will be in a different political world, whether we like it or not. A lot of decisions will be out of our hands because machines will be taking them for us, in the name of greater efficiency. However, if machines are doing the hard work of connecting us together, that leaves human beings freer to play around.


pages: 411 words: 98,128

Bezonomics: How Amazon Is Changing Our Lives and What the World's Best Companies Are Learning From It by Brian Dumaine

activist fund / activist shareholder / activist investor, AI winter, Airbnb, Amazon Web Services, Atul Gawande, autonomous vehicles, basic income, Bernie Sanders, Black Swan, call centre, Chris Urmson, cloud computing, corporate raider, creative destruction, Danny Hillis, Donald Trump, Elon Musk, Erik Brynjolfsson, future of work, gig economy, Google Glasses, Google X / Alphabet X, income inequality, industrial robot, Internet of things, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Lyft, Marc Andreessen, Mark Zuckerberg, money market fund, natural language processing, pets.com, plutocrats, Plutocrats, race to the bottom, ride hailing / ride sharing, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Snapchat, speech recognition, Steve Jobs, Stewart Brand, supply-chain management, Tim Cook: Apple, too big to fail, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, wealth creators, web application, Whole Earth Catalog

Chapter 8: Warehouses That Run in the Dark Compared to Amazon’s: J. Clement, “Number of Full-Time Facebook Employees from 2007 to 2018,” Statista, August 14, 2019, https://www.statista.com/statistics/273563/number-of-facebook-employees/. By 2022, there will be: “Growth of the Internet of Things and in the Number of Connected Devices Is Driven by Emerging Applications and Business Models, and Supported by Standardization and Falling Device Costs,” Internet of Things Forecast, Ericsson.com, https://www.ericsson.com/en/mobility-report/internet-of-things-forecast. When Henry Ford proved: “Celebrating the Moving Assembly Line in Pictures,” Ford Media Center, September 12, 2013, https://media.ford.com/content/fordmedia/fna/us/en/features/celebrating-the-moving-assembly-line-in-pictures.html. In 1961, a California start-up: David Laws, “Fairchild Semiconductor: The 60th Anniversary of a Silicon Valley Legend,” Computer History Museum, September 19, 2017.

Compared to Amazon’s roughly 650,000 workers, Alphabet, Google’s parent company, employs 98,000, while Facebook employs only 36,000—and many of those jobs are highly skilled, well-paid programming and data scientist jobs. For the most part, Alphabet, Facebook, Baidu, and other big tech firms hire the kind of workers whose jobs are not likely to be threatened by automation. By contrast, Amazon operates not only in cyberspace but also in the realm of the tangible. The company is a leader in the adoption of the Internet of Things—which at its heart is the digitization of much of what we do in the real world. Devices such as cell phones, Amazon Echo smart speakers, Amazon microwaves, earbuds, and thermostats connect to the Internet, making them smarter and easier for us to control. (And as we saw in the previous chapter, easier for the companies that make them to collect data on our buying habits.) In the business arena, warehouse robots, scanners, and self-driving delivery vans also connect to the Internet, thanks to inexpensive sensors and smart algorithms.

The global business world will eventually divide into two camps—those who adopt their own version of Bezonomics, and those who don’t. Alphabet, Facebook, Netflix, Alibaba, JD.com, and Tencent have built huge, powerful businesses based on their ability to collect and analyze data, and keep applying those learnings to make their businesses smarter and their offerings to customers more attractive. In their pursuit of AI-driven technologies such as voice and facial recognition, the Internet of Things, and robotics, they’re creating automated business models that will crush traditional businesses that fail to adapt to this new world. And the emergence of 5G technology, which will replace our current digital networks, will only widen the gap. Experts predict that this next generation of Internet connectivity will be as much as a hundred times faster than today’s web. (On a 5G network, a two-hour movie can be downloaded in seconds.)


pages: 598 words: 134,339

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World by Bruce Schneier

23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, augmented reality, Benjamin Mako Hill, Black Swan, Boris Johnson, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, congestion charging, disintermediation, drone strike, Edward Snowden, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, hindsight bias, informal economy, Internet Archive, Internet of things, Jacob Appelbaum, Jaron Lanier, John Markoff, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, linked data, Lyft, Mark Zuckerberg, moral panic, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, Panopticon Jeremy Bentham, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, recommendation engine, RFID, Ross Ulbricht, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, undersea cable, urban planning, WikiLeaks, zero day

Google Glass is the first wearable device: Jenna Wortham (8 Mar 2013), “Meet Memoto, the lifelogging camera,” New York Times Blogs, http://bits.blogs.nytimes.com/2013/03/08/meet-memoto-the-lifelogging-camera. Internet of Things: Ken Hess (10 Jan 2014), “The Internet of Things outlook for 2014: Everything connected and communicating,” ZDNet, http://www.zdnet.com/the-internet-of-things-outlook-for-2014-everything-connected-and-communicating-7000024930. smart cities: Georgina Stylianou (29 Apr 2013), “Idea to have sensors track everything in city,” Press (Christchurch), http://www.stuff.co.nz/the-press/business/the-rebuild/8606956/Idea-to-have-sensors-track-everything-in-city. Victoria Turk (Jul 2013), “City sensors: the Internet of Things is taking over our cities,” Wired, http://www.wired.co.uk/magazine/archive/2013/07/everything-is-connected/city-sensors. smart toothbrushes: Sam Byford (5 Jan 2014), “Kolibree’s smart toothbrush claims to track and improve your dental hygiene,” Verge, http://www.theverge.com/2014/1/5/5277426/kolibree-smart-toothbrush.

Sandy Clark et al. (6–10 Dec 2010), “Familiarity breeds contempt: The honeymoon effect and the role of legacy code in zero-day vulnerabilities,” 26th Annual Computer Security Applications Conference, Austin, Texas, http://dl.acm.org/citation.cfm?id=1920299. Andy Ozment and Stuart E. Schechter (11 May 2006), “Milk or wine: Does software security improve with age?” MIT Lincoln Laboratory, https://research.microsoft.com/pubs/79177/milkorwine.pdf. economics of software development: This is even worse with embedded devices and the Internet of Things. Bruce Schneier (6 Jan 2014), “The Internet of Things is wildly insecure—and often unpatchable,” Wired, http://www.wired.com/2014/01/theres-no-good-way-to-patch-the-internet-of-things-and-thats-a-huge-problem. how the NSA and GCHQ think: James Ball, Julian Borger, and Glenn Greenwald (5 Sep 2013), “Revealed: How US and UK spy agencies defeat internet privacy and security,” Guardian, http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security. We know the NSA: These four points were made in this document.

Charles Stross (25 Jun 2014), “YAPC::NA 2014 keynote: Programming Perl in 2034,” Charlie’s Diary, http://www.antipope.org/charlie/blog-static/2014/06/yapcna-2014-keynote-programmin.html. smart pill bottles: Valentina Palladino (8 Jan 2014), “AdhereTech’s smart pill bottle knows when you take, and miss, your medication,” Verge, http://www.theverge.com/2014/1/8/5289022/adheretech-smart-pill-bottle. smart clothing: Econocom (19 Sep 2013), “When fashion meets the Internet of Things,” emedia, http://blog.econocom.com/en/blog/when-fashion-meets-the-internet-of-things. Michael Knigge (28 Aug 2014), “Tagging along: Is Adidas tracking soccer fans?” Deutsche Welle, http://www.dw.de/tagging-along-is-adidas-tracking-soccer-fans/a-1788463. because why not?: We’ve seen this trend before. Digital clocks first became popular in the 1970s. Initially they were largely stand-alone devices—alarm clocks and watches—but as their price declined, they became embedded into other things: first your microwave, then your coffeepot, oven, thermostat, VCR, and television.


pages: 159 words: 42,401

Snowden's Box: Trust in the Age of Surveillance by Jessica Bruder, Dale Maharidge

anti-communist, Bay Area Rapid Transit, Berlin Wall, blockchain, Broken windows theory, Burning Man, cashless society, Chelsea Manning, citizen journalism, computer vision, crowdsourcing, Donald Trump, Edward Snowden, Elon Musk, Ferguson, Missouri, Filter Bubble, Firefox, Internet of things, Jeff Bezos, Julian Assange, license plate recognition, Mark Zuckerberg, mass incarceration, medical malpractice, Occupy movement, off grid, pattern recognition, Peter Thiel, Robert Bork, Shoshana Zuboff, Silicon Valley, Skype, social graph, Steven Levy, Tim Cook: Apple, web of trust, WikiLeaks

Exercise tracker data — which can include users’ heart rates, locations, and distances traveled — is showing up in courtrooms as evidence related to charges of sexual assault, personal injury, and homicide. In a Connecticut murder case, prosecutors obtained the victim’s FitBit records to build a case against her husband, who claimed a masked intruder had shot her when the device showed she was still walking around. The internet of things is a gold mine for police. Researchers are working to expand its applications for law enforcement. At Champlain University in Vermont, graduate students dedicated a semester to “Internet of Things Forensics,” studying the Nest thermostat and other devices to see how they could help criminal investigations. A program description praised the “diversity and usefulness” of networked objects — ranging from “routers that connect a laptop to the internet” to “a crockpot (from WEMO) and slippers (from 24eight).”

Since smart speakers’ microphones are always turned on, privacy advocates worry about them becoming wiretaps for law enforcement. That sounds alarmist until you look back at 2006, when federal agents got permission to use a cellphone as a “roving bug.” What would prevent them from making a similar request involving an Amazon Echo or any other smart device with a microphone or sensors? The spread of networked devices — the so-called internet of things — could someday give police easy access to the most private parts of our lives. Law enforcement already has a formidable array of surveillance technologies, ranging from license plate readers to the cell site simulators nicknamed “stingrays” that mimic mobile phone towers to facial recognition and access to credit card transactions — an area of data that is mushrooming as some areas of the country move towards a cashless economy.

Do you use networked appliances: security devices such as doorbell cameras or so-called “smart” speakers, televisions, or thermostats? These gizmos add comfort to our lives, but they also stalk us relentlessly — both online and in the physical world, often without our consciously consenting to this digital home invasion. Read the fine print. Decide how much of your privacy you’re willing to sacrifice in the name of convenience. Keep in mind that the burgeoning field of digital forensics has turned its attention to the internet of things. Nowadays, there are entire college programs dedicated to mining the data gathered by our digital devices. Carry this approach over to social media. Facebook, Twitter, Instagram, and other platforms may keep you virtually connected with friends and family. Their primary purpose, however, is mapping your patterns of consumption and even your political preferences, which may be sold to the highest bidder.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

additive manufacturing, Airbnb, AltaVista, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, Ethereum, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Ross Ulbricht, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, uber lyft, universal basic income, Zipcar

Two contemporary developments illustrate how the same three invariant forces, and thus the same economics, that led to the consumerization of digital may reshape our everyday physical objects: the Internet of Things and the emergence of additive manufacturing. The Internet of Things In the not-so-distant future, every “thing” will have the potential to be digitized and networked. In an iconic example (although perhaps not the most cost-effective), a milk carton nearing or getting close to its expiration date will communicate with your refrigerator, which will in turn communicate with your FreshDirect grocery list. Cartons of fresh milk will subsequently be delivered to your home, allowing you to focus your attention on more important things. This is the Internet of Things—a world where objects of all kinds from milk cartons to household appliances to items of clothing have a little bit of embedded digital intelligence, and are part of the network.

The refrigerator will register this information and add milk to the grocery list at an online delivery service.7 In other words, in the near future, a growing number of quotidian objects will be able to talk to each other over a network. This is not, to be clear, the stuff of science fiction. After all, the Internet of Things does not promise to help us have intelligent conversations with our refrigerators or milk cartons (at least not anytime soon). Elevators imbued with a little intelligence are unlikely, as the humorist Douglas Adams posited, to get bored with their mundane jobs of traveling up and down and take to sulking in building basements. Yet the Internet of Things—though not yet delivering articulate appliances or portending device depression—will inevitably expand crowd-based capitalism. As intelligence, even in the smallest increments, can be embedded more cheaply and readily in physical objects, the ability to track these objects will increase.

Put differently, a physical object will know where it is, how much it is being used, and will be able to arrange automated, digitally enabled transport for itself to its renter without human intervention.8 A physical object becomes, in a sense, like an intelligent iTunes movie file. As a consequence, the “rentability” of objects also expands. On-demand services of all kinds become more viable, more efficient, and more ubiquitous with the Internet of Things. 3-D Printing and Additive Manufacturing Until recently, if you wanted to get into the business of making and selling physical objects, you had to acquire the capabilities of manufacturing and find some way of distributing and selling objects (by connecting, for example, with a wholesaling or retailing network). We are now entering a world where you no longer need a factory or warehouse or distribution network to be engaged in the sale of physical objects.


pages: 158 words: 46,353

Future War: Preparing for the New Global Battlefield by Robert H. Latiff

Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, Berlin Wall, cyber-physical system, Danny Hillis, defense in depth, drone strike, Elon Musk, failed state, friendly fire, Howard Zinn, Internet of things, low earth orbit, Nicholas Carr, orbital mechanics / astrodynamics, self-driving car, South China Sea, Stephen Hawking, Stewart Brand, Stuxnet, Wall-E

The term “information technology” is a broad one, encompassing a range of areas including microelectronic devices such as microprocessors and transistors, the Internet, high-performance computing, algorithms, data collection and storage, data transmission, data mining and analysis, and the “Internet of things”—a term used to describe the growing trend of putting sensors on everything and tying them to the Internet. Computing power and memory have grown astronomically, as has the amount of data generated. The number of transistors that can now be placed on a chip lies in the hundreds of billions. The amount of data now gathered in two days exceeds all of the data created from the dawn of civilization to 2003. The Internet of things has grown enormously, with the number of connected devices worldwide predicted to be almost forty billion in 2020. Appliances, vehicles, and even toys are connected. Unsurprisingly, the military has its own Internet of things. For several years, the Army issued helmets with built-in sensors to help diagnose brain injuries.

For several years, the Army issued helmets with built-in sensors to help diagnose brain injuries. Even individual munitions have Internet addresses. Almost everything—conventional bombs and nuclear weapons, soldier communications and satellites, simple vehicles and advanced armor systems, lasers and navigation systems—depends on computers and their components. The Internet of things and Wi-Fi-enabled devices, with all of their advantages, also come with some serious downsides. Always-on sensors are threats to privacy and civil liberties, and the Internet of things was recently determined to have provided the hardware basis for a massive denial-of-service attack on East Coast Internet service providers. Information technology is central and crucial to military planners. Continued advances in it could render communications security obsolete. So-called quantum computing, if fully realized, will make cryptography impossible, allowing a quantum computer to break any code.


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

"Robert Solow", 3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, disruptive innovation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joi Ito, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Nelson Mandela, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Panopticon Jeremy Bentham, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, plutocrats, Plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Travis Kalanick, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

They fear a world resembling that exhibition at the Venetian in which row after row of nameless, faceless data gatherers wearing all-seeing electronic glasses watch our every move. Big Brother seemed ubiquitous at the Venetian. Reporting about CES, the Guardian’s Dan Gillmor warned that networked televisions that “watch us” are “closing in on Orwell’s nightmarish Big Brother vision.”32 Even industry executives are fearful of the Internet of Things’s impact on privacy, with Martin Winterkorn, the CEO of Volkswagen, warning in March 2014 that the connected car of the future “must not become a data monster.”33 But there is one fundamental difference between the Internet of Things and Erich Mielke’s twentieth-century Big Brother surveillance state, one thing distinguishing today’s networked society from Orwell’s 1984. Mielke wanted to create crystal man against our will; in today’s world of Google Glass and Facebook updates, however, we are choosing to live in a crystal republic where our networked cars, cell phones, refrigerators, and televisions watch us.

And not just everyone, but everything. An Ericsson white paper predicts that, by 2020, there will be 50 billion intelligent devices on the network.4 Homes, cars, roads, offices, consumer products, clothing, health-care devices, electric grids, even those industrial cutting tools once manufactured in the Musto Steam Marble Mill company, will all be connected on what now is being called the Internet of Things. The number of active cellular machine-to-machine devices will grow 3 to 4 times between 2014 and 2019. “The physical world,” a McKinsey report confirms, “is becoming a type of information system.”5 The economics of this networked society are already staggering. Another McKinsey report studying thirteen of the most advanced industrial economies found that $8 trillion is already being spent through e-commerce.

Indeed, the networked fabric business is one of the newest new things in today’s digital economy. Every decade there’s a major revolution in Silicon Valley. In the mid-1990s, it was the original Web 1.0 revolution of free websites like Netscape, Yahoo, and Craigslist. In 2005, it was Tim O’Reilly’s Web 2.0 user-generated-content revolution of Google, Wikipedia, and YouTube. And today, in 2014, it’s the “Internet of Things” revolution of 3-D printing, wearable computing, driverless cars, and intelligent drones. To learn more about today’s revolution, I had returned to the scene of my original disenchantment with the Internet. I’d once again come to the O’Reilly Media offices in Sebastopol, the little town up in Sonoma County, California, some fifty miles north of San Francisco. But rather than spending another annoying weekend at FOO Camp, I had come to meet with Dale Dougherty, the guy who first came up with the “Web 2.0” term.


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Ben Horowitz, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen: Great Stagnation, uber lyft, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

We are rapidly changing the filter through which we deal with the world from a physical, materially-based perspective to an information- and knowledge-based one. And this is just beginning. Ten years ago we had five hundred million Internet-connected devices. Today there are about eight billion. By 2020 there will be fifty billion and a decade later we’ll have a trillion Internet-connected devices as we literally information-enable every aspect of the world in the Internet of Things. The Internet is now the world’s nervous system, with our mobile devices serving as edge points and nodes on that network. Think about that for a second: we’ll be jumping from eight billion Internet-connected devices today to fifty billion by 2025, and to a trillion a mere decade later. We like to think that thirty or forty years into the Information Revolution we are well along in terms of its development.

Similar applications in healthcare, energy and financial services mean that we’re entering a world of Algorithms R Us. As far back as 2005, writer and publisher Tim O’Reilly stated that, “Data is the new Intel Inside.” And that was when there were just a half-billion Internet-connected devices in the world. As we noted in Chapter One, that number is set to grow to a trillion devices as we prepare to embrace the Internet of Things. In the face of that explosion, the need for algorithms has become mission critical. Consider for a moment that the last two years have seen nine times more data created than in the entire history of humanity. Then consider that the Computer Sciences Corporation believes that by 2020 we’ll have created a total 73.5 zettabytes of data—in Stephen Hawking’s phraseology, that’s seventy-three followed by twenty-one zeros.

Each subsequent phase of the Milkmaid’s production, including product design, name, tagline and even price, was crowdsourced as well [Crowd], resulting in a total of 2,530 contributions from the Quirky community for a single product. Although the Milkmaid was just a pilot [Experimentation], the project was deemed a huge success, and in 2013, GE and Quirky announced the next stage of their innovative new partnership: GE gave Quirky’s 900,000 community members open access to GE’s most promising patents and technologies. It also started a co-branded Internet of Things initiative called “Wink: Instantly Connected,” dedicated to building a line of smart home devices. GE, which invested $30 million in Quirky, chose to open up its patents in order to accelerate the creation of new, innovative products—something GE determined the crowd could accomplish more quickly than it could do on its own. That decision is clearly paying off. In addition to the four connected-home products currently available in Quirky’s online store, GE and Quirky expect to release more than 30 more such products over the next few years.


pages: 428 words: 121,717

Warnings by Richard A. Clarke

active measures, Albert Einstein, algorithmic trading, anti-communist, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, Bernie Madoff, cognitive bias, collateralized debt obligation, complexity theory, corporate governance, cuban missile crisis, data acquisition, discovery of penicillin, double helix, Elon Musk, failed state, financial thriller, fixed income, Flash crash, forensic accounting, friendly AI, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Watt: steam engine, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge worker, Maui Hawaii, megacity, Mikhail Gorbachev, money market fund, mouse model, Nate Silver, new economy, Nicholas Carr, nuclear winter, pattern recognition, personalized medicine, phenotype, Ponzi scheme, Ray Kurzweil, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Ronald Reagan, Sam Altman, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, smart grid, statistical model, Stephen Hawking, Stuxnet, technological singularity, The Future of Employment, the scientific method, The Signal and the Noise by Nate Silver, Tunguska event, uranium enrichment, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y2K

“This is about a lot more than just hacking the power grid,” Weiss told us. The same SCADA software used by the Iranians is used in thousands of U.S. manufacturing and operating plants and facilities and is susceptible to the same exploits that the U.S. used to destroy those Iranian centrifuges. This computer network, transparent to most of us, is a critical part of the global infrastructure. It is known as the Internet of Things, the IoT. “The Internet of Things is just a marketing term that somebody thought up long after millions of machines were already networked,” Weiss explained to us. “And most of them are networked in ways that can be accessed, perhaps indirectly, from the public Internet.” It is that understanding, that everything is connected, that keeps Joe Weiss up at night. How many devices are connected? The consensus estimate is that by the end of this decade, worldwide, there will be about fifty billion connected machines comprising the IoT.

Having established this process for developing a Cassandra Coefficient based on past Cassandra Events, we next listen for today’s Cassandras. Who now among us may be accurately warning us of something we are ignoring, perhaps at our own peril? We look at contemporary individuals and their predictions, and examine the ongoing public reaction to them. Our cases here include artificial intelligence, genetic engineering, sea level rise, pandemic disease, a new risk of nuclear winter, the Internet of Things, and asteroid impacts. Finally, we end this volume with some thoughts about how society and government might reduce the frequency of ignoring Cassandras when it comes to some of the major issues of our time. While we will not endorse the predictions of the possible contemporary Cassandras (we leave it to the reader to decide), we will apply our framework to their cases, evaluating each element—the individual, the receiver of the warning, and the threat itself—to determine the Cassandra Coefficient.

The resulting explosion ripped apart the neighborhood, most of whose residents had no idea they lived near a pipeline. Eight people died. Seventeen homes burned down. The utility, PG&E, was hit with a $1.6 billion fine. The accident investigation report blamed the disaster on a substandard segment of pipe and technical errors. There was no suggestion that the software error was intentional, no indication that malicious actors were involved. “But that’s just the point,” Joe Weiss argues. “The Internet of Things introduces new vulnerabilities even without malicious actors.” The problem, Weiss claims, is using Internet software for things that it was never intended to run, like industrial controls, or linking solid industrial control software over Internet communications networks. The icon of the IoT and the darling of Silicon Valley techies and entrepreneurs is a round, wall-mounted gadget called Nest.


pages: 382 words: 105,819

Zucked: Waking Up to the Facebook Catastrophe by Roger McNamee

4chan, Albert Einstein, algorithmic trading, AltaVista, Amazon Web Services, barriers to entry, Bernie Sanders, Boycotts of Israel, Cass Sunstein, cloud computing, computer age, cross-subsidies, data is the new oil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Electric Kool-Aid Acid Test, Elon Musk, Filter Bubble, game design, income inequality, Internet of things, Jaron Lanier, Jeff Bezos, John Markoff, laissez-faire capitalism, Lean Startup, light touch regulation, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, Menlo Park, Metcalfe’s law, minimum viable product, Mother of all demos, move fast and break things, move fast and break things, Network effects, paypal mafia, Peter Thiel, pets.com, post-work, profit maximization, profit motive, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Sand Hill Road, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, The Chicago School, Tim Cook: Apple, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, WikiLeaks, Yom Kippur War

What I have in mind is an independent company that represents the interest of users at login, providing the minimum information required for each transaction. With each new generation of technology, entrepreneurs and engineers have an opportunity to profit from designing products that serve rather than exploit the needs of their users. Virtual reality, artificial intelligence, self-driving cars, and the Internet of Things (IoT)—smart speakers and web-enabled televisions, automobiles, and appliances—all present opportunities to create bicycles for the mind. Unfortunately, I see no evidence yet that the designers in those categories are thinking that way. The term you hear instead is “Big Data,” which is code for extracting value rather than creating it. At the end of the day, the best way to persuade Facebook and Google to adopt human-driven technology is to foster competition and demonstrate value in the marketplace.

It may even be possible to integrate payments—Apple Pay, PayPal, or a credit card—with the same benefits: data would go only to the people who actually need to have it. Platforms and merchants will be unhappy to lose access to data from users who choose private log-in, but that is their own fault. They should not have abused the trust of users. The Next Big Thing would also include smartphones that are less addictive and do not share private data, devices in the Internet of Things that are respectful of data privacy, and applications that are useful and/or fun without causing harm. One way to think about the opportunity for human-driven technology is in terms of decentralization. If antitrust action creates room for competition, the Next Big Thing could see the pendulum of innovation swing back from centralized cloud systems to devices at the edge. There is a human-driven alternative to every product in the market today, as well as many that do not exist yet.

The question I struggle with is whether AI is one thing or a category with several niches. If the latter, there may still be hope for startups. Will the Next Big Thing be the next generation of wireless technology, the standard known as 5G? The magic of 5G is not going to be more bandwidth to phones; it will be in enabling pervasive 4G-level bandwidth at one-tenth the cost. It will power the Internet of Things. The standard has been set, and we should anticipate lots of startup activity. However, IoT already exists, and the early products pose a range of issues that demand attention, including data privacy and security. Critics have expressed alarm about the ability of Amazon’s Alexa and Google Home to snoop on users. With 5G, internet platforms will no longer be confined to PCs and smartphones.


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Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires With Minimum Investment by Sangeet Paul Choudary

3D printing, Airbnb, Amazon Web Services, barriers to entry, bitcoin, blockchain, business process, Chuck Templeton: OpenTable:, Clayton Christensen, collaborative economy, commoditize, crowdsourcing, cryptocurrency, data acquisition, frictionless, game design, hive mind, Internet of things, invisible hand, Kickstarter, Lean Startup, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, means of production, multi-sided market, Network effects, new economy, Paul Graham, recommendation engine, ride hailing / ride sharing, shareholder value, sharing economy, Silicon Valley, Skype, Snapchat, social graph, social software, software as a service, software is eating the world, Spread Networks laid a new fibre optics cable between New York and Chicago, TaskRabbit, the payments system, too big to fail, transport as a service, two-sided market, Uber and Lyft, Uber for X, uber lyft, Wave and Pay

The wearable produces data constantly, and the platform provides analytics back to the user based on the data. Additionally, the platform also pools data from many users to create network-level insights. Wearables benefit from implicit network effects. Platform Stack Figure 6d • Nest Thermostat And The Internet Of Things. The Nest thermostat uses a data platform to aggregate data from multiple thermostats. This aggregation of data enables analytics for thermostat users and powers services to the city’s utilities board. The Internet of Things will give rise to new business models in similar ways through the creation of data platforms. • Industrial Internet. GE’s focus on the industrial Internet is another example of a data platform. Machines embedded with sensors constantly stream activity data into a platform that helps each machine learn from other machines and provides network-wide intelligence.

Platform Scale explains the design of a family of emerging digital business models that enables today’s startups to achieve rapid scale: the platform business model. The many manifestations of the platform business model - social media, the peer economy, cryptocurrencies, APIs and developer ecosystems, the Internet of things, crowdsourcing models, and many others - are becoming increasingly relevant. Yet, most new platform ideas fail because the business design and growth strategies involved in building platforms are not well understood. Platform Scale is a builder’s manual for anyone building a platform business today. It lays out a structured approach to designing and growing a platform business model and addresses the key factors that lead to the success and failure of these businesses.

External developers plug in to the platform and create apps on top of it. Consumers moved to platform phones whose functionality could easily be extended using apps created by external developers. The disruption of Nokia and BlackBerry demonstrates that firms must leverage platforms for innovation. Today, banks, retailers, and businesses across diverse industries are following the Android playbook to use platforms for innovation. d. The intelligent Internet of Things Nest’s thermostats constantly create data, as do GE’s machines and Nike’s shoes. These products aren’t merely physical products anymore; they plug in to platforms. These objects feed data into central platforms, and every individual object connected to the platform learns from the community of other objects connected to the platform. As we move from pipes to platforms, the business model of consumer goods will also move from one centered on product sales to one centered on platform-enabled connected services, where products work as part of an ecosystem.


pages: 742 words: 137,937

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

23andMe, 3D printing, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, full employment, future of work, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, lifelogging, lump of labour, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, optical character recognition, Paul Samuelson, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, Turing test, Watson beat the top human players on Jeopardy!, WikiLeaks, young professional

., ‘Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection’, Cochrane Database of Systematic Reviews, 3 (2012): <doi: 10.1002/14651858.CD009756> (accessed 27 March 2015). 33 Caroline Jones et al., ‘ “Even if You Know Everything You Can Forget”: Health Worker Perceptions of Mobile Phone Text-Messaging to Improve Malaria Case-Management in Kenya’ PLoS ONE, 7: 6 (2012): <doi: 10.1371/journal.pone.0038636> (accessed 27 March 2015). 34 David Rose, Enchanted Objects: Design, Human Desire, and the Internet of Things (2014). It increases drug adherence by 23 percentage points (to 94%) compared with standard vials. See p. 130. 35 ‘Emory University Hospital Explores “Intensive Care Unit of the Future”’, IBM, 4 November 2013 <http://www-03.ibm.com/press/us/en/pressrelease/42362.wss> (accessed 6 March 2015). 36 Nick Bilton, ‘Disruptions: Medicine that Monitors You’, New York Times, 23 June 2013 <http://www.nytimes.com> (accessed 27 March 2015). 37 <http://www.patientslikeme.com> (accessed 27 March 2015). 38 Christina Farr and Alexei Oreskovic, ‘Exclusive: Facebook plots first steps into healthcare’, Reuters, 3 Oct. 2014 <http://www.reuters.com> (accessed 27 March 2015). 39 David Bray et al., ‘Sermo: A Community-Based, Knowledge Ecosystem’ (2008), <http://dx.doi.org/10.2139/ssrn.1016483> and <http://www.sermo.com> (accessed 27 March 2015). 40 <https://secure.quantiamd.com> (accessed 27 March 2015). 41 <https://www.doximity.com> (accessed 27 March 2015). 42 Daniel Gaitan, ‘Crowdsourcing the answers to medical mysteries’, Reuters, 1 Aug. 2014 <http://www.reuters.com> (accessed 27 March 2015). 43 <http://www.innocentive.com>. 44 <https://watsi.org>. 45 Jerome Groopman, ‘Print Thyself: How 3-D Printing is Revolutionizing Medicine’, New Yorker, 24 Nov. 2014. 46 e.g.

There will always be some people with no access to the Internet. But as computing becomes more portable and increasingly affordable in this way, this group will steadily diminish. Already in the United Kingdom and United States, for example, most people now have access to the Internet.75 This avalanche of hand-helds may seem pervasive in its own right. But when we speak of ‘increasingly pervasive devices’, we also include the phenomenon known as the ‘Internet of Things’.76 Alternatively referred to as ‘ubiquitous’ or ‘pervasive’ computing, the idea here is to embed processors, sensors, and Internet connectivity into physical objects.77 It is as if we have tiny connected computers planted inside everyday things: an alarm clock that can check train times online and let its owner sleep longer if there are delays; an umbrella that is able to check online weather forecasts and light up at the front door when rain is predicted; electronic books that can update one another; plant-pots that can monitor moisture in soil and refill as appropriate; refrigerators that can detect when the amount of some foodstuffs has fallen below a prescribed level and reorder accordingly; boilers, lights, and thermostats that can be switched on and adjusted remotely.

Miniaturized circuits can be introduced into flesh and blood, of humans and animals—measuring, monitoring, dispensing, capturing, and transmitting information to specialists, patients, or to other systems. Similar technologies are being used in the corporate world. For example, GE calls this the ‘industrial Internet’—embedding sensors in their machines and sending large bodies of data into the ‘cloud’, and so bringing together the Internet of Things and Big Data.83 This, then, is what we mean by ‘increasingly pervasive devices’. In the first instance, there is a surge in the number of tablets and hand-held machines, meaning that more people can be the beneficiaries of online practical expertise. Secondly, and as dramatically, very small processing and communicating components are being embedded in machinery, buildings, people, animals, clothes, and other everyday objects, and this has application in the work of various professionals (certainly for doctors, dentists, vets, opticians, and architects).


Super Continent: The Logic of Eurasian Integration by Kent E. Calder

3D printing, air freight, Asian financial crisis, Berlin Wall, blockchain, Bretton Woods, business intelligence, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, colonial rule, Credit Default Swap, cuban missile crisis, deindustrialization, demographic transition, Deng Xiaoping, disruptive innovation, Doha Development Round, Donald Trump, energy transition, European colonialism, failed state, Fall of the Berlin Wall, Gini coefficient, housing crisis, income inequality, industrial cluster, industrial robot, interest rate swap, intermodal, Internet of things, invention of movable type, inventory management, John Markoff, liberal world order, Malacca Straits, Mikhail Gorbachev, mittelstand, money market fund, moral hazard, new economy, oil shale / tar sands, oil shock, purchasing power parity, quantitative easing, reserve currency, Ronald Reagan, seigniorage, smart cities, smart grid, South China Sea, sovereign wealth fund, special drawing rights, special economic zone, supply-chain management, Thomas L Friedman, trade liberalization, trade route, transcontinental railway, UNCLOS, UNCLOS, union organizing, Washington Consensus, working-age population, zero-sum game

Such a pattern prevails on only the largest of continents, with Eurasia naturally representing the most extreme case on earth. (3) The techno-political context is distinctive. Technological change, and regulatory adjustment with it, is uncommonly rapid today, in sectors of special relevance to Eurasia’s reintegration such as land transport and telecommunications. The Logistics Revolution, accelerated by digitalization and the Internet of Things, is proceeding at warp speed early in the twenty-first century, with greater implications for Eurasia than for other regions due to that Super Continent’s geography and to the pace of its economic advance. Public policy and private effort, especially China’s Belt and Road Initiative (BRI), together with the efforts of firms like COSCO, Huawei, Ericsson, Alibaba, and Deutsche 6 chapter 1 N Rotterdam Shanghai 0 0 1000 2000 mi 1000 2000 3000 km map 1.1 Land vs. sea routes Bahn, are capitalizing on these long-term trends, with BRI and private efforts complementing one another in synergistic fashion.

Reflecting recent advances in intermodal transport technology and customs clearance, there are important prospective synergies between two distinct elements of the BRI: the overland Belt and the maritime Road. Shifting from rail or road transport to maritime traffic and back again is growing cheaper, faster, and more efficient. These developments, accelerated by cooperative ventures like the China-Singapore Internet of Things project in Chongqing and the rapid evolution of e-commerce, are making transcontinental supply chains in electronics, precision machinery, and fine chemicals increasingly plausible, giving BRI powerful new transcontinental geo-economic stimulus.67 Silk Road Economic Belt 21st-Century Maritime Silk Road Moscow Rotterdam Duisburg Istanbul Samarkand Athens Urumqi Almaty Bishkek Venice Khorgos Dushanbe Lanzhou Tehran Xi’an Fuzhou Kolkata Hanoi Haikou Colombo Kuala Lumpur Nairobi Jakarta 0 0 map 2.2 China’s Belt and Road Initiative 1000 1000 2000 2000 mi 3000 km N 46 chapter 2 Since Xi Jinping unveiled the BRI in general terms, other Chinese leaders and analysts have worked to clarify details of the initiative and to situate the BRI in global context.68 One spectacular demonstration of this effort was the first Belt and Road Forum, convened in May 2017 and attended by leaders of twenty-nine member nations, excluding President Xi, and representatives of fifty-six countries in all, together with their technical advisors.69 Top representatives of all the key global intergovernmental organizations (IGOs), including the World Bank, the International Monetary Fund, the World Trade Organization, and the United Nations, were also in attendance and were pressed to integrate their efforts with those of China, accenting the PRC’s nascent ambitions to transform the BRI into a “parallel structure” of global economic governance.

Containerization transformed shipping into an increasingly standardized process, holding out the promise of major new efficiency advances, especially as digitalization also gained momentum. Some of the related areas for innovation were insurance, customs clearance, freight forwarding, and intermodal transfer. Although containerization was an earlier development, technologies 86 chapter 4 in the latter areas, especially intermodal transfer, have been evolving rapidly over the past decade and promise to evolve still further with the introduction of Internet of Things (IoT) and 5th-Generation (5G) wireless network technology, giving promise of further disruptive innovation in the coming years. IoT allows, for example, the real-time monitoring of goods as well as assets from individual cases to the whole company. It also allows organizations to automate procedures that were previously manual and to optimize how multiple logistics systems work together. Such innovations lead to higher utilization of existing assets, smart inventory management, and high-quality predictive maintenance, as well as accurate end-to-end tracking of high-value goods.


pages: 405 words: 117,219

In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, animal electricity, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, British Empire, business process, carbon-based life, cellular automata, Claude Shannon: information theory, combinatorial explosion, complexity theory, continuous integration, Conway's Game of Life, cosmological principle, dark matter, dematerialisation, double helix, Douglas Hofstadter, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, income inequality, index card, industrial robot, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, Kickstarter, liberal capitalism, lifelogging, millennium bug, Moravec's paradox, natural language processing, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, post-industrial society, prediction markets, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, stem cell, Stephen Hawking, Steven Pinker, strong AI, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

And what about all the smart things with which we are all beginning to furnish our homes: intelligent thermostats, fridges that order food when it runs out, telemedicine devices that monitor our health? The evangelists of the ‘internet of things’ proclaim that our lives will be simpler and more productive when the things we use can take decisions on our behalf. This is happening already, but will explode in the next few years. According to Cisco CEO John Chambers there are some thirteen billion devices connected to the Internet today, a number predicted to grow to fifty billion by 2020, and 500 billion by 2030.30 The Internet of things will result in US$19 trillion in profits and cost savings in the private and public sector, and will be ten to fifteen times larger than the Internet today in terms of number of connections. Things that think, talk and do The ‘Internet of things’ is postmodernism reinventing panpsychism – the idea that all things share a mind, or a soul.

It begins with the formulation of logic by Aristotle, and goes on to show how his ideas were developed further in the nineteenth and early twentieth centuries, until they led to the birth of computer languages and Artificial Intelligence. I will explore how ancient automata evolved into mechanical calculating machines, to Babbage’s Analytical Engine, and all the way to modern supercomputers and the Internet of things; and speculate about futuristic alternative computer architectures that mimic the neural networks of the brain. I will ask how close computers are to achieving self-awareness, and what might happen once they do. This book aspires to incite a fresh look at Artificial Intelligence by bridging the ‘two cultures’ gap, and illustrating the interconnection between literary narratives, philosophy and technology in defining and addressing the two most important scientific questions of all time: whence our minds and can we recreate them?

Although computing machines began – as their name suggests – as contraptions that automated arithmetic operations, they quickly became applied to just about everything. What are the unique characteristics of computers that make them so flexible, adaptable and intrusive? How did the transformation from the physical to the digital come about? Where does it lead us? And, finally, in the age of big data, search engines, social media, mobile apps and the Internet of things, what role is there for Artificial Intelligence? ‘War is the father and king of all’ Daring to complement Heraclitus’ famous quote,2 I would add that ballistics and encryption were the mothers and queens of all computers. The world war of 1939–1945 was fought with aircraft that often had to be shot down from the ground or from a moving ship at sea, and with encoded signals that coordinated sophisticated military movements of naval, land and aerial forces.


pages: 437 words: 113,173

Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance by Ian Goldin, Chris Kutarna

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Airbnb, Albert Einstein, AltaVista, Asian financial crisis, asset-backed security, autonomous vehicles, banking crisis, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, bitcoin, Bonfire of the Vanities, clean water, collective bargaining, Colonization of Mars, Credit Default Swap, crowdsourcing, cryptocurrency, Dava Sobel, demographic dividend, Deng Xiaoping, Doha Development Round, double helix, Edward Snowden, Elon Musk, en.wikipedia.org, epigenetics, experimental economics, failed state, Fall of the Berlin Wall, financial innovation, full employment, Galaxy Zoo, global pandemic, global supply chain, Hyperloop, immigration reform, income inequality, indoor plumbing, industrial cluster, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invention of the printing press, Isaac Newton, Islamic Golden Age, Johannes Kepler, Khan Academy, Kickstarter, low cost airline, low cost carrier, low skilled workers, Lyft, Malacca Straits, mass immigration, megacity, Mikhail Gorbachev, moral hazard, Nelson Mandela, Network effects, New Urbanism, non-tariff barriers, Occupy movement, On the Revolutions of the Heavenly Spheres, open economy, Panamax, Pearl River Delta, personalized medicine, Peter Thiel, post-Panamax, profit motive, rent-seeking, reshoring, Robert Gordon, Robert Metcalfe, Search for Extraterrestrial Intelligence, Second Machine Age, self-driving car, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart grid, Snapchat, special economic zone, spice trade, statistical model, Stephen Hawking, Steve Jobs, Stuxnet, The Future of Employment, too big to fail, trade liberalization, trade route, transaction costs, transatlantic slave trade, uber lyft, undersea cable, uranium enrichment, We are the 99%, We wanted flying cars, instead we got 140 characters, working poor, working-age population, zero day

Together, these new service industries made it possible for even small firms to trade with multiple distant markets.70 Newer ships New technologies are playing the same role today—enabling a greater volume and variety of goods, services and people to circulate. In the sky, aerospace improvements have extended the range that aircraft can fly and lowered their operating and environmental costs. Now, no two cities on the globe are more than a day apart, and more of us can afford to fly between them. In the United States, the cost of flying has fallen by as much as 40 percent over the past 30 years.71 On land, the emerging “Internet of Things”—tagging everything from cars to Coke machines with little chips and computers that can link to data networks—means that more and more objects in the physical world are adopting digital properties. Orchestrated by computers and robots, such objects can start to move about in volumes, at speeds and with efficiency far beyond human capabilities. Today they number 15 billion; by 2020, there will be 50 billion such objects in the world.72 In Seoul, Korea, for example, the entire public transportation system—every bus, taxi, train and public bicycle—is now networked.73 The expectation is that travel times will quicken and road congestion will fall as every user and “device” on the network starts to make computer-aided traffic management choices.

Today they number 15 billion; by 2020, there will be 50 billion such objects in the world.72 In Seoul, Korea, for example, the entire public transportation system—every bus, taxi, train and public bicycle—is now networked.73 The expectation is that travel times will quicken and road congestion will fall as every user and “device” on the network starts to make computer-aided traffic management choices. The Internet of Things will transform the volume and variety of physical flows on land. We know this, because it has already helped to do so at sea. So far, that is where new technologies have done the most to enable new global flows. “Containerization” has digitized shipping by putting everything from cars to crayons into identical, traceable boxes. This revolution began in 1956 with the advent of the container ship, and by the early 1990s, all the world’s major ports had been converted to handle them.

These crimes injure us personally, through the theft and ransom of identities, login information, webcam videos or Snapchat photos. They also use us to injure others, by making us unwitting accomplices in spam, phishing and email attacks, or by using our computers as web servers for malware and child pornography. And as more smart devices, from appliances to automobiles to the locks on our house, connect to the “Internet of Things,” the range of injuries that cyber criminals can cause us will only widen. In July 2015, some 1.4 million Jeeps were recalled when researchers proved they could exploit a bug to hack, and crash, the vehicles remotely over the Internet.81 Cybercrime also steals intellectual property and other secrets from institutions. In 2014, roughly one-half of small businesses, two-thirds of medium-sized companies and four-fifths of large enterprises worldwide were specifically targeted by a cybercrime.82 Keith Alexander, the director of the US National Security Agency until 2014, described cyber espionage activity as the “greatest transfer of wealth in history.”83 In the US alone, where half of all cyber attacks originate and are committed, corporate losses from cyber espionage may range from $300 to $400 billion per year.84 These attacks also harm customers and clients, by exposing their personal data and making them more vulnerable to identity theft.


pages: 587 words: 117,894

Cybersecurity: What Everyone Needs to Know by P. W. Singer, Allan Friedman

4chan, A Declaration of the Independence of Cyberspace, Apple's 1984 Super Bowl advert, barriers to entry, Berlin Wall, bitcoin, blood diamonds, borderless world, Brian Krebs, business continuity plan, Chelsea Manning, cloud computing, crowdsourcing, cuban missile crisis, data acquisition, do-ocracy, drone strike, Edward Snowden, energy security, failed state, Fall of the Berlin Wall, fault tolerance, global supply chain, Google Earth, Internet of things, invention of the telegraph, John Markoff, Julian Assange, Khan Academy, M-Pesa, MITM: man-in-the-middle, mutually assured destruction, Network effects, packet switching, Peace of Westphalia, pre–internet, profit motive, RAND corporation, ransomware, RFC: Request For Comment, risk tolerance, rolodex, Silicon Valley, Skype, smart grid, Steve Jobs, Stuxnet, uranium enrichment, We are Anonymous. We are Legion, web application, WikiLeaks, zero day, zero-sum game

Cyberspace reflects the characteristics and needs of its users, but as we’ve seen, these users also grow to reflect its characteristics and needs. The final trend that will likely have serious cybersecurity implications builds on both cheaper computation and a more mobile world. The future blurring of cyber and physical will come to fruition when digital systems are fully embedded in the real world, also known as the “Internet of Things.” Like so many aspects of cyberspace, the Internet of Things can best be illustrated with a cat. Steve Sande was a man living in Colorado who worried about Ruby, his feline companion, when he was away. His particular concern was that Ruby might get too hot in his home that lacked air conditioning. However, Steve was environmentally conscious (or cheap) and didn’t want to waste power on a fan when it wasn’t needed. So he linked his fan to an Internet-connected device called a WeMo and wrote a script that monitored an online weather website.

So he linked his fan to an Internet-connected device called a WeMo and wrote a script that monitored an online weather website. Whenever the website said the weather was over 85 degrees Fahrenheit, the WeMo switched the fan on. With no direct human instruction, the “things” in Steve’s house worked together via the Internet to keep Ruby the cat cool. More broadly, the Internet of Things is the concept that everything can be linked to a web-enabled device to collect or make use of data. So many physical objects in our lives, from cameras to cars, already have computer chips built in. What happens when they can all “talk” to each other? And then, what happens when literally anything from the wristband you wear to wall of your bathroom to fruit at the grocery store can have tiny cheap chips put on them, and also join the conversation?

In this vision, distributed sensors can detect street traffic, enabling your GPS to route your car home from work, while communicating to your home’s thermostat how far away you are, so that it can power back up the heat from its most efficient setting, determined off its link to the smart power grid; sensors can detect how crowded different restaurants are to make you a reservation, and your exercise bike at the gym will talk to your credit card to find out what you ordered at that restaurant, and decide how long you have to work out the next day to burn that cheesecake off. One of the main obstacles to this vision is interoperability. The Internet exploded because of shared, open standards that anyone could build on. Without the unruly but effective governance structures, however, the many other devices that may be linked into the Internet of Things still lack standardized, open inputs and outputs that share and interpret instructions and data in seamless, automated exchanges. Common formats are required to understand data, and some mechanism is needed to gather and interpret data in the first place, which can be an expensive proposition. And while turning Ruby’s fan on was a simple function of knowing the temperature, not everything is so easy.


pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, Marc Andreessen, Marshall McLuhan, means of production, megacity, Minecraft, Mitch Kapor, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, Whole Earth Review, zero-sum game

The superbrain that predicts the weather accurately will be in a completely different kingdom of mind from the intelligence woven into your clothes. The taxonomy of minds must reflect the different ways in which minds are engineered with these trade-offs. In the short list below I include only those kinds of minds that we might consider superior to us; I’ve omitted the thousands of species of mild machine smartness—like the brains in a calculator—that will cognify the bulk of the internet of things. Some possible new minds: A mind like a human mind, just faster in answering (the easiest AI mind to imagine). A very slow mind, composed primarily of vast storage and memory. A global supermind composed of millions of individual dumb minds in concert. A hive mind made of many very smart minds, but unaware it/they are a hive. A borg supermind composed of many smart minds that are very aware they form a unity.

Or I could ask it to determine the kind of rooms that tend to raise my heart rate. Was it the color, the temperature, the height of the ceilings? Although it seems like wizardry now, this will be considered a very mechanical request in a decade, not very different from asking Google to find something—which would have been magical 20 years ago. Still, the picture is not big enough. We—the internet of people—will track ourselves, much of our lives. But the internet of things is much bigger, and billions of things will track themselves too. In the coming decades nearly every object that is manufactured will contain a small sliver of silicon that is connected to the internet. One consequence of this wide connection is that it will become feasible to track how each thing is used with great precision. For example, every car manufactured since 2006 contains a tiny OBD chip mounted under the dashboard.

The computer manufacturer Cisco estimates that there will be 50 billion devices on the internet by 2020, in addition to tens of billions of screens. The electronics industry expects a billion wearable devices in five years, tracking our activities, feeding data into the stream. We can expect another 13 billion appliances, like the Nest thermostat, animating our smarthomes. There will be 3 billion devices built into connected cars. And 100 billion dumb RFID chips embedded into goods on the shelves of Walmart. This is the internet of things, the emerging dreamland of everything we manufacture that is the new platform for the improbable. It is built with data. Knowledge, which is related, but not identical, to information, is exploding at the same rate as information, doubling every two years. The number of scientific articles published each year has been accelerating even faster than this for decades. Over the last century the annual number of patent applications worldwide has risen in an exponential curve.


pages: 379 words: 109,223

Frenemies: The Epic Disruption of the Ad Business by Ken Auletta

Airbnb, barriers to entry, Bernie Sanders, Boris Johnson, Build a better mousetrap, Burning Man, call centre, carbon footprint, cloud computing, commoditize, connected car, corporate raider, crossover SUV, disintermediation, Donald Trump, Elon Musk, forensic accounting, Google Glasses, Internet of things, Jeff Bezos, Khan Academy, Lyft, Mark Zuckerberg, market design, Menlo Park, move fast and break things, move fast and break things, Naomi Klein, NetJets, Network effects, pattern recognition, pets.com, race to the bottom, Richard Feynman, ride hailing / ride sharing, Saturday Night Live, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Snapchat, Steve Ballmer, Steve Jobs, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, Upton Sinclair, éminence grise

Keith Weed of Unilever, who Kassan says was the first client to ask him to arrange a tour of the exhibition floors, explains why he comes to CES annually: “If you’re going to get to the future, first you better have an idea of the future. . . . If I can stay ahead, it gives me an advantage.” Plus, he adds, “Everyone is here.” Like other clients, Weed told MediaLink what he was most interested in doing at CES. This year he wanted a curated exhibition tour to explore three subjects: artificial intelligence, virtual reality, and the Internet of things. In addition to Unilever, MediaLink had a total of 100 clients attending and would curate 582 floor tours and meetings with advertisers, agencies, and digital companies. A staff of forty was in attendance, each person responsible for accompanying a group of clients—JPMorgan Chase, GE, McDonald’s, NBC, Hearst, Gawker, the New York Times—as well as organizing public session panels for agency clients like Digitas, Publicis’s digital media agency.

In previous years, drones, Google Glass, and 4K TVs had their moment. Writing about CES 2016, Farhad Manjoo of the New York Times observed, “If news from CES feels especially desultory this year, it might not be the show that’s at fault. Instead, blame the tech cycle. We’re at a weird moment in the industry: The best new stuff is not all that cool, and the coolest stuff”—AI, virtual reality, the Internet of things, drones—“isn’t quite ready.” * * * ■ ■ ■ If CES had been a warm bath of relationship building, the American Association of Advertising Agencies conference at the Loews Miami Beach Hotel two months later centered more on conflict. The much-anticipated ANA report on agency kickbacks sparked by Jon Mandel’s speech a year earlier hovered over anxious agency executives. Michael Kassan spoke of the K2/Ebiquity investigation for the ANA and evoked a common fear: “We’re weeks away from Armageddon.”

Because there are so many more platforms on which ads appear, “the need for creativity goes up every single day because you are seeing more ads than you ever saw before.” And with video becoming the principal way for advertisers to reach consumers on mobile devices, and with just the first two to three seconds of that video to win the consumers attention, he concludes, “Creativity becomes more important. So Math Men and Mad Men are joined.” The other potentially disruptive technology is what’s come to be called the Internet of things, or IoT, “smart devices” with Bluetooth connections—refrigerators, light bulbs, watches, thermostats, washing machines, coffeepots, cars, baby pacifiers, and so on. In 2016, Gartner, Inc., a technology research firm, estimated that there were 6.4 billion connected “things,” and this number would jump to 20.8 billion in four years. These smart devices will yield a cornucopia of data. Devices monitor and can alert your store when the milk or ketchup in your refrigerator needs replenishment, when your washing machine needs more soap, when a device on top of your TV monitoring your facial expressions communicates whether you watch a commercial.


pages: 391 words: 71,600

Hit Refresh: The Quest to Rediscover Microsoft's Soul and Imagine a Better Future for Everyone by Satya Nadella, Greg Shaw, Jill Tracie Nichols

"Robert Solow", 3D printing, Amazon Web Services, anti-globalists, artificial general intelligence, augmented reality, autonomous vehicles, basic income, Bretton Woods, business process, cashless society, charter city, cloud computing, complexity theory, computer age, computer vision, corporate social responsibility, crowdsourcing, Deng Xiaoping, Donald Trump, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, equal pay for equal work, everywhere but in the productivity statistics, fault tolerance, Gini coefficient, global supply chain, Google Glasses, Grace Hopper, industrial robot, Internet of things, Jeff Bezos, job automation, John Markoff, John von Neumann, knowledge worker, Mars Rover, Minecraft, Mother of all demos, NP-complete, Oculus Rift, pattern recognition, place-making, Richard Feynman, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, special economic zone, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, telepresence, telerobotics, The Rise and Fall of American Growth, Tim Cook: Apple, trade liberalization, two-sided market, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, young professional, zero-sum game

We will think about customers as “dual users,” people who use technology for their work, their school, and their personal digital life. In the email I inserted the image of a target and in its center appeared the words, “digital work and life experiences,” surrounded by our cloud platform and computer devices. Soon there will be 3 billion people connected to the Internet, sensors, and the Internet of Things (IoT). Yes, PC sales were slowing, and so we needed to convert Nietzsche’s “courage in the face of reality” into “courage in the face of opportunity.” We needed to win the billions of connected devices, not fret about a shrinking market. Employees responded immediately. In just the first twenty-four hours I heard from hundreds of employees in every part of the company and in every part of the world.

And she showed us the importance of getting out of our headquarters at Redmond—away from our insular, comfortable world—and inside that of our partners and customers. In the end, we still had to resolve some of our issues through the courts, but we also continued to show respect. “Microsoft values and respects our partnership,” we wrote in a statement. “Unfortunately, even partners sometimes disagree.” Today Microsoft apps are popular on Samsung smartphones; Windows 10 powers Samsung tablets and its ambitions for the far-flung Internet of Things. Around the same time, we were embroiled in a contentious dispute with Yahoo, which used the Bing search engine as its exclusive search partner. Microsoft and Yahoo shared in the revenue from the searches performed by Bing. But, as with Samsung, our relationship with Yahoo was deteriorating as Yahoo’s business model came under pressure, and lawsuits were being threatened. Yahoo wanted to breach its contract.

To avoid being trapped by the innovator’s dilemma—and to move from always focusing on the urgency of today to considering the important things for tomorrow—we decided to look at our investment strategy across three growth horizons: first, grow today’s core businesses and technologies; second, incubate new ideas and products for the future; and third, invest in long-term breakthroughs. On horizon one, our customers and partners will continue to see quarter-by-quarter, year-by-year innovations in all of our businesses. On horizon two, we’re already investing in some exciting nearer-term platform shifts, such as new user interfaces with speech or digital ink, new applications with personal assistants and bots, and Internet of Things experiences for everything from factories to cars to home appliances. On horizon three, Microsoft is highly focused in areas that only a few years ago sounded distant, but today are frontiers of innovation—mixed reality, artificial intelligence, and quantum computing. Mixed reality will become an essential tool in medicine, education, and manufacturing. AI will help forecast crises like the Zika epidemic and help us focus our time and attention on things that matter most.


pages: 400 words: 88,647

Frugal Innovation: How to Do Better With Less by Jaideep Prabhu Navi Radjou

3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, barriers to entry, Baxter: Rethink Robotics, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cloud computing, collaborative consumption, collaborative economy, Computer Numeric Control, connected car, corporate social responsibility, creative destruction, crowdsourcing, disruptive innovation, Elon Musk, financial exclusion, financial innovation, global supply chain, IKEA effect, income inequality, industrial robot, intangible asset, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, low cost airline, low cost carrier, M-Pesa, Mahatma Gandhi, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, precision agriculture, race to the bottom, reshoring, risk tolerance, Ronald Coase, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, standardized shipping container, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, Travis Kalanick, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar

Unlike concept testing, which requires people explicitly to articulate to researchers what they need and want, immersion labs allow researchers to observe customers as they play with prototypes and infer what needs to be done to improve product design and the user experience. Make use of big data analytics Consumer and industrial products of all kinds are increasingly connected to the internet. Mobile phones and the Internet of Things (identifiers for different physical objects) allow researchers to collect large amounts of detailed data to predict customer needs and respond with tailored solutions. This approach, called predictive analytics, has particular power in industrial contexts. Philips Lighting, which produces commercial lighting systems for large installations, provides a good example of its capabilities. The company fits (with the customer’s permission) each light fixture with sensor switches and motion detectors that gather data, such as hours used and dimming levels, and sends it back to a central information system.

Empowerment approaches provide consumers with the technical tools that can measure, monitor and manage their behaviour over time. They take advantage of the increasing ubiquity of smartphones, sensors in devices, the internet and social media to create apps that enable real-time monitoring and visualisation of behaviour. All this in turn enables consumers to become more aware of the causes and consequences of their behaviour and compare it with that of others. The most significant development here is the “Internet of Things”, that is, the equipping of everyday objects – watches, fridges, cars – with tiny, interconnected identifying devices that allow continuous, unobtrusive measuring, monitoring and regulation of behaviour on the web. Most efforts to shape consumer behaviour use a combination of both approaches, and are becoming increasingly widespread in areas as diverse as energy, education, finance and health.

In other words, customers do not just want sophisticated GE products; they also want personalised services that can help them run their businesses better. Second, the competitive landscape is radically shifting. In the coming years, GE’s toughest competitors will not be other industrial powerhouses such as Siemens or Schneider Electric, but the so-called GAFAs (Google, Apple, Facebook and Amazon). Indeed, as more physical devices – from giant power turbines to modest light bulbs – are connected to the Internet of Things, a torrent of big data will be unleashed on the world. If the GAFAs can gain access to the data generated by GE’s industrial products, they can glean insights from that data to offer value-adding services to GE’s customers. As the saying goes: “Whoever owns the customer’s data owns the customer.” More worryingly, GAFAs and other software firms are rapidly expanding into hardware; for example, Google and Apple are investing in connected consumer products and Amazon is getting into drones and robots.


pages: 165 words: 50,798

Intertwingled: Information Changes Everything by Peter Morville

A Pattern Language, Airbnb, Albert Einstein, Arthur Eddington, augmented reality, Bernie Madoff, Black Swan, business process, Cass Sunstein, cognitive dissonance, collective bargaining, disruptive innovation, index card, information retrieval, Internet of things, Isaac Newton, iterative process, Jane Jacobs, John Markoff, Lean Startup, Lyft, minimum viable product, Mother of all demos, Nelson Mandela, Paul Graham, peer-to-peer, RFID, Richard Thaler, ride hailing / ride sharing, Schrödinger's Cat, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley startup, source of truth, Steve Jobs, Stewart Brand, Ted Nelson, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, theory of mind, uber lyft, urban planning, urban sprawl, Vannevar Bush, zero-sum game

The machine view was so successful during the industrial revolution, we find it astonishingly hard to let go, even as the information age renders it obsolete and counterproductive in a growing set of contexts. It’s not that the old model is all wrong. We’re not about to throw away hierarchy or specialization. But our world is changing, and we must adjust. The information age amplifies connectedness. Each wave of change – web, social, mobile, the Internet of Things – increases the degree and import of connection and accelerates the rate of change. In this context, it’s vital to see our organizations as ecosystems. This is not meant figuratively. Our organizations are ecosystems, literally. And while each community of organisms plus environment may function as a unit, the web of connections and consequences extends beyond its borders. All ecosystems are linked.

In our passion for placemaking we mustn’t lose sight of the information in the architecture. Our strength in structural design must be joined by an aptitude for managing information flows, feedback loops, and motivational metrics. What matters most isn’t what we build but the change we make. That’s why I’m writing this book. I want to study, understand, and clarify the nature of information in systems. In part, it’s about going beyond the Web. Mobile and the Internet of Things are tearing down the walls between physical and digital, creating new information flows and loops. It’s also about seeing old sites with fresh eyes. Our websites aren’t just channels for marketing and communication. They’ve become rich, dynamic places where work gets done. Websites are extensions of the organization that change its nature. To manage them, we must address inputs, outputs, feedback loops, metrics, governance, and culture.

In this story we see the synthesis of embodied and extended cognition. There are more dimensions to architecture than Tetris, so it’s even more vital we use models in the world to shift minds. Planning is making. Maps, sketches, words, and wireframes are still essential, but it’s also vital that we design in the medium of construction. How else will we imagine cross-channel experiences and the Internet of Things into life? Last year, I worked on a responsive redesign for a database publisher. Our team built wireframes and design comps to conduct quick, cheap experiments, and then an HTML prototype to enable new loops of build-measure-learn. Each of these cognition amplifiers is unique. Together they teach us that one way is the wrong way. As architects, designers, and developers, we each bring discrete value to think-do and plan-build.


pages: 293 words: 78,439

Dual Transformation: How to Reposition Today's Business While Creating the Future by Scott D. Anthony, Mark W. Johnson

activist fund / activist shareholder / activist investor, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, autonomous vehicles, barriers to entry, Ben Horowitz, blockchain, business process, business process outsourcing, call centre, Clayton Christensen, cloud computing, commoditize, corporate governance, creative destruction, crowdsourcing, death of newspapers, disintermediation, disruptive innovation, distributed ledger, diversified portfolio, Internet of things, invention of hypertext, inventory management, Jeff Bezos, job automation, job satisfaction, Joseph Schumpeter, Kickstarter, late fees, Lean Startup, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Minecraft, obamacare, Parag Khanna, Paul Graham, peer-to-peer lending, pez dispenser, recommendation engine, self-driving car, shareholder value, side project, Silicon Valley, Skype, software as a service, software is eating the world, Steve Jobs, the market place, the scientific method, Thomas Kuhn: the structure of scientific revolutions, transfer pricing, uber lyft, Watson beat the top human players on Jeopardy!, Y Combinator, Zipcar

Innov8 scoured the globe to find interesting investment opportunities that fit emerging themes around mobile advertising, big data analytics, cyber security, the internet of things, and more. By 2015, Innov8 had invested in more than fifty companies and was well established as a go-to investor in both the region and the industry. One of Innov8’s early investments was in Viki, a video-streaming website based in Singapore that offers on-demand video of TV shows, movies, and music videos from around the world. Rakuten Group of Japan acquired that business for $200 million. In 2014, Innov8 backed Jasper, a hyped company that created a platform to help companies manage services related to the internet of things. In 2016 Cisco Systems acquired Jasper (the name refers to the operating system created by Tony Stark, otherwise known as Iron Man) for $1.4 billion.

Moore’s Law improvement trajectory: The theory, based on an observation by Intel cofounder Gordon Moore in 1965, that the number of transistors on a chip were doubling regularly, holds that computing power doubles every eighteen months. See Investopedia, “Moore’s Law,” http://www.investopedia.com/terms/m/mooreslaw.asp. Nestlé and Samsung partnership: Samsung, “Samsung and Nestlé Collaborate on the Internet of Things and Nutrition to Advance Digital Health,” Samsung.com, July 28, 2016, https://news.samsung.com/global/samsung-and-nestle-collaborate-on-the-internet-of-things-and-nutrition-to-advance-digital-health. TechCrunch on platforms: Tom Goodwin, “The Battle Is For The Customer Interface ,” TechCrunch.com, March 3, 2015, https://techcrunch.com/2015/03/03/in-the-age-of-disintermediation-the-battle-is-all-for-the-customer-interface/. Oxford research on job automation: Aviva Hope Rutkin, “Report Suggests Nearly Half of U.S.

He asked Andy, a twenty-six-year veteran, to lead transformation A, in which Partzelg’s core business would shift from a traditional sales model to a leasing model. Andy’s plan promises to minimize sales declines and dramatically boost profit margins and cash flow. It requires radically reconfiguring the organization, however, and laying off about 30 percent of staff. Bernadette is driving transformation B. After considering several options, she and her team have decided to focus on the internet of things. She has recommended acquiring a sensor company and an analytics company, with the intent of stitching them together to offer unique services based on the data generated by Partzelg’s components. That all sounds sensible, but let’s see what happens when key leaders begin questioning Partzelg’s commitment. the organization still care about A? Is it serious about making B happen? Will it make the tough calls in both cases?


pages: 368 words: 96,825

Bold: How to Go Big, Create Wealth and Impact the World by Peter H. Diamandis, Steven Kotler

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Charles Lindbergh, cloud computing, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, dematerialisation, deskilling, disruptive innovation, Elon Musk, en.wikipedia.org, Exxon Valdez, fear of failure, Firefox, Galaxy Zoo, Google Glasses, Google Hangouts, gravity well, ImageNet competition, industrial robot, Internet of things, Jeff Bezos, John Harrison: Longitude, John Markoff, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, low earth orbit, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mars Rover, meta analysis, meta-analysis, microbiome, minimum viable product, move fast and break things, Narrative Science, Netflix Prize, Network effects, Oculus Rift, optical character recognition, packet switching, PageRank, pattern recognition, performance metric, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, Ray Kurzweil, recommendation engine, Richard Feynman, ride hailing / ride sharing, risk tolerance, rolodex, self-driving car, sentiment analysis, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart grid, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, superconnector, technoutopianism, telepresence, telepresence robot, Turing test, urban renewal, web application, X Prize, Y Combinator, zero-sum game

Chapter Three: Five to Change the World 1 Adrian Kingsley-Hughes, “Mobile gadgets driving massive growth in touch sensors,” ZDNet, June 18, 2013, http://www.zdnet.com/mobile-gadgets-driving-massive-growth-in-touch-sensors-7000016954/. 2 Peter Kelly-Detwiler, “Machine to Machine Connections—The Internet of Things—And Energy,” Forbes, August 6, 2013, http://www.forbes.com/sites/peterdetwiler/2013/08/06/machine-to-machine-connections-the-internet-of-things-and-energy/. 3 See http://www.shotspotter.com. 4 Clive Thompson, “No Longer Vaporware: The Internet of Things Is Finally Talking,” Wired, December 6, 2012, http://www.wired.com/2012/12/20-12-st_thompson/. 5 Brad Templeton, “Cameras or Lasers?,” Templetons, http://www.templetons.com/brad/robocars/cameras-lasers.html. 6 See http://en.wikipedia.org/wiki/Passenger_vehicles_in_the_United_States. 7 Commercial satellite players include: PlanetLabs (already launched), Skybox (launched and acquired by Google), Urthecast (launched), and two still-confidential companies still under development (about which Peter Diamandis has firsthand knowledge). 8 Stanford University, “Need for a Trillion Sensors Roadmap,” Tsensorsummit.org, 2013, http://www.tsensorssummit.org/Resources/Why%20TSensors%20Roadmap.pdf. 9 Rickie Fleming, “The battle of the G networks,” NCDS.com blog, June 28, 2014, http://www.ncds.com/ncds-business-technology-blog/the-battle-of-the-g-networks. 10 AI with Dan Hesse, 2013–14. 11 Unless otherwise noted, all IoT information and Padma Warrior quotes come from an AI with Padma, 2013. 12 Cisco, “2013 IoE Value Index,” Cisco.com, 2013, http://internetofeverything.cisco.com/learn/2013-ioe-value-index-whitepaper. 13 NAVTEQ, “NAVTEQ Traffic Patterns,” Navmart.com, 2008, http://www.navmart.com/pdf/NAVmart_TrafficPatterns.pdf. 14 Juho Erkheikki, “Nokia to Buy Navteq for $8.1 Billion, Take on TomTom (Update 7),” Bloomberg, October 1, 2007, http://www.bloomberg.com/apps/news?

“In 2013,” says Padma Warrior,11 the chief technology and strategy officer of Cisco, “eighty new things were being connected to the Internet every second. That’s nearly 7 million per day, 2.5 billion per year. In 2014, the number reached almost 100 per second. By 2020, it’ll grow to more than 250 per second, or 7.8 billion per year. Add all of these numbers up and that’s more than 50 billion things connected to the Internet by 2020.” And it’s this explosion of connectivity that is building the Internet-of-Things (IoT). A recent study by Cisco estimated that between 2013 and 2020, this uber-network will generate $19 trillion in value (net profit).12 Think about this for a moment. The U.S. economy hovers around $15 trillion a year. Cisco is saying that over the ten-year period, this new net will have an economic impact greater than America’s GDP. Talk about the land of opportunity. Global Internet Device Installed Base Forecast A Trillion Sensor Future Source: http://www.businessinsider.com/decoding-smartphone-industry-jargon-2013-11 “E” refers to “Estimated”, as in estimated size of the market.

From a technological perspective, what makes JARVIS extraordinary is both its pervasiveness in Stark’s life and its ability to understand natural-language instructions, even when the banter is laden with irony or humor. More technically, JARVIS is a software shell that interfaces between Stark’s every desire and the rest of the world, able both to gather data from billions of sensors and to take action through any system or robotic device connected to the AI. In this way, the Internet of Things serves as JARVIS’s eyes, ears, arms, and legs. For sure, JARVIS has dethroned HAL, now holding the title for most recognizable AI in the world, but what makes his dominance more spectacular is that unlike the never-actualized HAL, key elements of JARVIS are starting to come into existence in laboratories and companies around the world. AI expert and Singularity University cofounder/chancellor Ray Kurzweil27 explains: “In the 1960s, when Arthur C.


Autonomous Driving: How the Driverless Revolution Will Change the World by Andreas Herrmann, Walter Brenner, Rupert Stadler

Airbnb, Airbus A320, augmented reality, autonomous vehicles, blockchain, call centre, carbon footprint, cleantech, computer vision, conceptual framework, connected car, crowdsourcing, cyber-physical system, DARPA: Urban Challenge, data acquisition, demand response, digital map, disruptive innovation, Elon Musk, fault tolerance, fear of failure, global supply chain, industrial cluster, intermodal, Internet of things, Jeff Bezos, Lyft, manufacturing employment, market fundamentalism, Mars Rover, Masdar, megacity, Pearl River Delta, peer-to-peer rental, precision agriculture, QWERTY keyboard, RAND corporation, ride hailing / ride sharing, self-driving car, sensor fusion, sharing economy, Silicon Valley, smart cities, smart grid, smart meter, Steve Jobs, Tesla Model S, Tim Cook: Apple, uber lyft, upwardly mobile, urban planning, Zipcar

Chief Executive Officer, ThyssenKrupp, Düsseldorf, Germany Lutz Junge Principal Engineer, Electronics Research Lab, Volkswagen Group of America, San Francisco, California, USA Acknowledgements Kristin Kolodge xi Executive Director, Driver Interaction and Human Machine Interface, J. D. Power, Westlake Village, California, USA Martin Kolmar, Dr. Professor of Economics, University of St. Gallen, Switzerland Hartmut Kremling Engineering Consultant for 5G, Internet of Things and autonomous and connected Driving, Dresden, Germany Brett Lantz Associate Director of Analytics, University of Michigan, Ann Arbor, Michigan, USA Patrick Little Senior Vice President and General Manager, Automotive, Qualcomm Technologies Inc., San Diego, California, USA Jun Ma, Dr. Professor and Director, School of Automotive Studies, Tongji University, Shanghai, China Andreas Meyer Chief Executive Officer, Swiss Railway Corporation, Bern, Switzerland Julian Nida-Rümelin, Professor of Philosophy, Ludwig-Maximilian Dr.

As automation has a positive impact on energy efficiency, increasing vehicle automation will also significantly extend the range of electric vehicles [148]. The essence of autonomous driving is the development of vehicles into cyber-physical systems that comprise a combination of mechanical and electronic components. A vehicle’s hardware and software exchange certain data about the infrastructure (the Internet of Things), and the vehicle is controlled or monitored by a processing unit. In the future, each vehicle will communicate with the infrastructure: parking garages, parking spaces, traffic lights, traffic signs and a traffic control centre (vehicle-to-infrastructure communication or V-to-I). Data on factors such as traffic flow, available parking spaces Autonomous Driving 10 and traffic-light phases, will allow the processing unit in the vehicle to select the best route and decide on a suitable speed.

Figure 12.2. Development of Mobile Communication Networks. Data transfer rate in MBit/s <10 GBit 5G <1 GBit <0.4 MBit <7.2 MBit 2G 3G 3G GSM UMTS HSPA 1996 2004 2006 <0.2 MBit Source: LTE.info. <150 MBit 4G 4G LTE Adv. <42 MBit 3G LTE HPSA+ 2009 2010 2014 2020 The Connected Car 131 Box 12.1. Statement by Hartmut Kremling Hartmut Kremling, Consultant Engineer for 5G, Internet of Things and Autonomous and Connected Driving LTE-V and 5G play a crucial role for the functioning of the ecosystem of the automotive industry consisting of numerous digital services. Building an ecosystem for autonomous driving needs intensive collaboration between the car industry, infrastructure vendors like Ericsson, Huawei, Intel, Nokia and Qualcomm, and telecommunications operators like Vodafone.


The Non-Tinfoil Guide to EMFs by Nicolas Pineault

Albert Einstein, en.wikipedia.org, Ignaz Semmelweis: hand washing, Internet of things, self-driving car, Silicon Valley, Skype, smart cities, smart grid, smart meter

Radiation Nation: The Fallout of Modern Technology — Your Complete Guide to EMF Protection & Safety: The Proven Health Risks of Electromagnetic Radiation (EMF) & What to Do Protect Yourself & Family. Icaro Publishing. huffingtonpost.com antennasearch.com/ The website seems to be down at the time of this writing, unfortunately. rcrwireless.com stopglobalwifi.org © 2017 N&G Media Inc. 15 But why just connect every human being to the Internet? Our new smart electronics need it too! Experts in the development of what’s called the “Internet of Things” (IoT) predict that by 2020, there will be around 50 billion devices, people or sensors connected with each other.27 These include your Bluetooth dimmer switches and home appliances, but also wireless traffic lights, light bulbs, cars (GPS, satellite radio, etc.), FM-emitting posters28 and yes! — even wireless sensors placed on trees to be able to monitor which one needs to be watered.29 Why not?

What I am saying is that if we learned anything from these past mistakes, we should listen to the early warning signs — for example, thousands of studies that show low-level EMFs might be harmful — and then act with precaution. Instead of doing just that, we’re exponentially increasing the amount of EMFs we’re all exposed to, we’re right about to upgrade all networks to 5G which means multiplying the number of cellphone antennas we use tremendously, we’re connecting 50 billion new devices by 2020328 thanks to the “Internet Of Things” and we’re even planning to blast a constant EMF signal to every plant, animal and living thing on the entire planet using satellites or freaking giant balloons. Google’s project Loon: while we figure out whether EMFs can screw up your health or not, let’s blast them on the entire planet! May I innocently suggest none of these sounds like being “cautious”? 328 singularityhub.com © 2017 N&G Media Inc. 97 Choice #2: The Precautionary Principle The Precautionary Principle instructs us that in the face of serious threats, a lack of scientific certainty never justifies inaction. - Yes, Martin Blank, PhD, once again.

© 2017 N&G Media Inc. 148 149 And some people thought I had just Instagrammed a hot potato or a delicious set of PB&J sandwiches. I understand the confusion. © 2017 N&G Media Inc. Sneaky Sources Of Wifi - Level 1 Cheap & Easy Aside from the very sneaky public wifi that’s installed on a third of all private routers, there are a ton of electronics in your home that constantly emit invisible RF signals right under your nose. How rude. As companies continue to push the idea of a smart, hyperconnected home and the Internet of Things (IoT) — where everything ranging from your light switches to your plants will be connected to the Internet — it will become harder and harder to identify these sources of EMFs unless you have a meter like mine, or hire an EMF expert to do a home assessment (always highly recommended). Scrap The Baby Monitor How can I put this bluntly? If you put a baby monitor in your child’s crib, you might as well use a 4G phone instead — because certain monitors are essentially small cellular antennas.


pages: 385 words: 111,113

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, congestion charging, crowdsourcing, cryptocurrency, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, future of work, gig economy, Google Glasses, Google X / Alphabet X, Hans Lippershey, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Network effects, new economy, obamacare, Occupy movement, Oculus Rift, off grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, RFID, ride hailing / ride sharing, Robert Metcalfe, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, TaskRabbit, technological singularity, telemarketer, telepresence, telepresence robot, Tesla Model S, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, Turing complete, Turing test, uber lyft, undersea cable, urban sprawl, V2 rocket, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks

For more than a decade thereafter, people talked about the dominant form of personal computer as “IBM Compatible”. That’s how strong IBM’s branding around “PC” became back then. 7 At the History of Science auction held at Bonhams New York on 22nd October 2014, one of the 50 original Apple-I computers (and one of only about 15 or so that are operational) was sold to The Henry Ford for a staggering US$905,000. 8 Cisco—Internet of Things (IoT) 9 Minecraft is a trademark owned by Mojang/Microsoft. 10 Globally, the term ECG is most common in which the Greek word for “heart” cardia or kardia is central to the acronym (elektro-cardia-graph, literally “electric-heart-writing”). The US common usage is EKG, using the original Greek spelling term rather than the English transliteration (cardio). 11 R.W. White, R. Harpaz, N.H. Shah, W.

Sensors, Wearables, Ingestibles and Feedback Loops As mentioned in chapter 3, heart disease is one of the single most common causes of death in the developed world. As a result, heart health is one of the biggest disciplines in medicine globally today, second only to cancer and cancer research. It is just one of the areas set to be fundamentally changed by the technology of sensors and the Internet of Things. A Parisian doctor named René Théophile Hyacinthe Laënnec (1781–1826) invented the first stethoscope in 1816 to “assist with auscultation”, or listening to a patient’s heartbeat. In 1851, the stethoscope went binaural, and since has had minor adjustments, including even electronic amplification. The next major leap in heart health monitoring, having been used in medicine for more than a century already, was the ECG machine.

There will be very few instances where a human who can give you advice at a future time with inferior data will compete with technologically embedded, contextual advice in real time. Machines Will Be Better at Learning about You Machine learning has been limited in the past by pattern recognition, natural speech and other deficiencies, but machines are beginning to catch up quickly. The advantage that machines connected to the Internet of Things and sensors will have is that they will be able to learn about your behaviour much more efficiently than service organisations today. How do service organisations today learn about your preferences? There are really only four ways: • demographic-based assumptions • surveys, marketing databases and user panels • data you’ve previously entered into the system or on a form • preferences you might input into an app, online portal or other configurator All of these are imprecise ways of measuring your preferences and behaviour, and at a very minimum depend on both your diligence and honesty in answering, and the effectiveness of the organisation in collecting and synthesizing that data.


pages: 380 words: 109,724

Don't Be Evil: How Big Tech Betrayed Its Founding Principles--And All of US by Rana Foroohar

"side hustle", accounting loophole / creative accounting, Airbnb, AltaVista, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, Bernie Sanders, bitcoin, book scanning, Brewster Kahle, Burning Man, call centre, cashless society, cleantech, cloud computing, cognitive dissonance, Colonization of Mars, computer age, corporate governance, creative destruction, Credit Default Swap, cryptocurrency, data is the new oil, death of newspapers, Deng Xiaoping, disintermediation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Etonian, Filter Bubble, future of work, game design, gig economy, global supply chain, Gordon Gekko, greed is good, income inequality, informal economy, information asymmetry, intangible asset, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, Kenneth Rogoff, life extension, light touch regulation, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Menlo Park, move fast and break things, move fast and break things, Network effects, new economy, offshore financial centre, PageRank, patent troll, paypal mafia, Peter Thiel, pets.com, price discrimination, profit maximization, race to the bottom, recommendation engine, ride hailing / ride sharing, Robert Bork, Sand Hill Road, search engine result page, self-driving car, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, smart cities, Snapchat, South China Sea, sovereign wealth fund, Steve Jobs, Steven Levy, subscription business, supply-chain management, TaskRabbit, Telecommunications Act of 1996, The Chicago School, the new new thing, Tim Cook: Apple, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, WikiLeaks, zero-sum game

These apps alone represent a $21 billion industry of snooping, and it’s not only the largest tech companies that benefit (though they certainly do; Google’s Android system has 1,200 apps that do such tracking), but a host of companies that you probably don’t even think about, from Goldman Sachs to the Weather Channel.38 And that’s just the consumer side of things. The old commercial Internet is shifting to an industrial “Internet of things” that will push data harvesting out into the physical world—into design firms, manufacturing plants, insurance companies, financial houses, hospitals, schools, and even our homes. Name any successful company: Starbucks, Johnson & Johnson, Goldman Sachs…and it’s likely that successful data mining plays an important role in their business strategy. Real estate companies use a variety of AI applications to mine the data of potential buyers and sellers, even automating the process of home flipping.39 Other companies crunch data from electronic monitors to evaluate employee performance, and create up-to-the-minute rankings for their bosses.

In March 2017, he threw himself to his death from the twenty-fourth floor of the New York City Sofitel.19 Is This Time Different? I often think about those disastrous years and wonder what has changed in the tech world, and what hasn’t. Today’s tech market is so much more developed, with vastly better infrastructure and truly game-changing innovations. We are only just beginning to move into artificial intelligence, the Internet of things, and other areas that many businesses are counting on to propel revenue growth in the future. Whether they will or not remains to be seen. But it’s a fair bet that machines talking to one another will have a heck of a lot more practical and productive applications than online gossip websites did. Certainly, many of the companies created in the past decade will have more staying power than those of the preceding generation; the Internet itself has simply become the fabric of our economy in a way that creates scale and opportunity.

Net neutrality is one area in which the public debate over an issue that is central to our economy and civic society has been captured. Patents, as I covered extensively in chapter 5, is another. Over the past few years, I’ve heard disparate complaints from a variety of quarters—from start-up biotech firms, semiconductor and electronics firms, clean-tech companies, data analysis groups, universities, and innovators working on the Internet of things, as well as some of the venture capitalists that invest in these areas—that the patent system and the debate about how to structure it has been hijacked by the interests of the largest tech firms in the country. Indeed, the only ones who seem not to be complaining about the current system are Google, Apple, Intel, Cisco, and other Silicon Valley giants. While they all have their own patents to protect, their business models, which involve products that include hundreds or even thousands of bits of intellectual property, tend to do better when there are fewer patents to deal with.


pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson

23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, digital map, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, global pandemic, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Mark Shuttleworth, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

The solution will probably be even more technology, which is not what many people will want to hear, especially anyone familiar with E.M. Forster’s novel The Machine Stops. Perhaps the best way to think about the Internet in the future is to see it as something that you no longer “do,” but as something that simply “is.” When this happens the Internet will seem to have vanished. “The Internet of Things is also triggering new questions on ownership and consumption … we grow into an access-based economy, where IOI makes a pay-what-you-use system possible on an individual level.” Alexander Bassi, Institute for Internet and Society The Internet of things is not quite the same as ubiquitous or pervasive computing, but like most things in the future it’s connected. In the past, information was scarce and tended to be tightly controlled by governments or large corporations. Moreover, the flow was generally in one direction (certainly with media, which was broadcast to relatively passive recipients), and feedback loops (either from bottom upward or from outside to in) were slow and ponderous.

ISBN 978-1-62365-195-4 Distributed in the United States and Canada by Random House Publisher Services c/o Random House, 1745 Broadway New York, NY 10019 www.quercus.com Contents Introduction POLITICS & POWER 01 Ubiquitous surveillance 02 Digital democracy 03 Cyber & drone warfare 04 Water wars 05 Wane of the West ENERGY & ENVIRONMENT 06 Resource depletion 07 Beyond fossil fuels 08 Precision agriculture 09 Population change 10 Geo-engineering THE URBAN LANDSCAPE 11 Megacities 12 Local energy networks 13 Smart cities 14 Next-generation transport 15 Extra-legal & feral slums TECHNOLOGICAL CHANGE 16 An internet of things 17 Quantum & DNA computing 18 Nanotechnology 19 Gamification 20 Artificial Intelligence HEALTH & WELL-BEING 21 Personalized genomics 22 Regenerative medicine 23 Remote monitoring 24 User-generated medicine 25 Medical data mining SOCIAL & ECONOMIC DIMENSIONS 26 Living alone 27 Dematerialization 28 Income polarization 29 What (& where) is work? 30 The pursuit of happiness TOWARD A POSTHUMAN SOCIETY 31 Human beings version 2.0 32 Brain–machine interfaces 33 Avatar assistants 34 Uncanny Valley 35 Transhumanism SPACE: THE FINAL FRONTIER 36 Alt.Space & space tourism 37 Solar energy from space 38 Moon mining 39 Space elevators 40 Alien intelligence DOOMSDAY SCENARIOS 41 Cell phone radiation 42 Biohazards & plagues 43 Nuclear terrorism 44 Volcanoes & quakes 45 The sixth mass extinction UNANSWERED QUESTIONS 46 The Singularity 47 Me or we?

the condensed idea Slums the size of cities timeline 2012 Parents hire private security guards to escort teenagers in London 2014 25 percent more helipads in São Paulo than New York due to no-go areas 2022 CEO of General Electric visits outskirts of Nairobi to learn about recycling 2026 Indian rubbish pricing and distribution system copied in USA 2030 Soldiers outnumber police on some city streets 2070 After the collapse of the mines, Western Australia becomes a prison colony 16 An internet of things According to Cisco Systems, there will be 50 billion “things” connected to the Internet by 2020. That’s seven for every man, woman and child on the planet. So what are some of these “things” and what are the consequences of an Internet that’s increasingly made up of physical objects embedded with sensors? In the future your socks will have an IP address and your sock drawer will know how many pairs you’ve got and what color they are.


pages: 49 words: 12,968

Industrial Internet by Jon Bruner

autonomous vehicles, barriers to entry, commoditize, computer vision, data acquisition, demand response, en.wikipedia.org, factory automation, Google X / Alphabet X, industrial robot, Internet of things, job automation, loose coupling, natural language processing, performance metric, Silicon Valley, slashdot, smart grid, smart meter, statistical model, web application

Something similar is coming to the interfaces between software and the big machines that power the world around us. With a network connection and an open interface that masks its underlying complexity, a machine becomes a Web service, ready to be coupled to software intelligence that can ingest broad context and optimize entire systems of machines. The industrial internet is this union of software and big machines — what you might think of as the enterprise Internet of Things, operating under the demanding requirements of systems that have lives and expensive equipment at stake. It promises to bring the key characteristics of the Web — modularity, abstraction, software above the level of a single device — to demanding physical settings, letting innovators break down big problems, solve them in small pieces, and then stitch together their solutions. The foundational technologies of the industrial internet are available now to anyone from big industrial firms to garage inventors.

The inherent scalability of software means that a single exploit can propagate fast; once discovered, an exploit can be used against lots of machines. Think of a car’s odometer: the move to digital mileage counts, stored in software, makes it more difficult to tamper with the readout, but it expands the prospective target of an exploit from just one car (for mechanical odometers) to every car that uses the same software. Tools like Shodan[9], a search engine for the Internet of Things, and Digital Bond’s Basecamp[10], a database of industrial control exploits, illustrate the scale of the industrial internet and its vulnerabilities. Shodan is a search engine for Internet-connected devices, including some industrial control systems and Internet switches. Here it reveals several computers that return a default password field in their HTTP responses. Industrial-control security is a fast-growing discipline with many parallels to the early PC security industry, but also some crucial advantages: connected infrastructure generally operates within tightly-defined networks, with consistent transmission and control patterns.


Mastering Blockchain, Second Edition by Imran Bashir

3D printing, altcoin, augmented reality, autonomous vehicles, bitcoin, blockchain, business process, carbon footprint, centralized clearinghouse, cloud computing, connected car, cryptocurrency, data acquisition, Debian, disintermediation, disruptive innovation, distributed ledger, domain-specific language, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, Firefox, full stack developer, general-purpose programming language, gravity well, interest rate swap, Internet of things, litecoin, loose coupling, MITM: man-in-the-middle, MVC pattern, Network effects, new economy, node package manager, Oculus Rift, peer-to-peer, platform as a service, prediction markets, QR code, RAND corporation, Real Time Gross Settlement, reversible computing, RFC: Request For Comment, RFID, ride hailing / ride sharing, Satoshi Nakamoto, single page application, smart cities, smart contracts, smart grid, smart meter, supply-chain management, transaction costs, Turing complete, Turing machine, web application, x509 certificate

Since then many use cases of blockchain technology in various industries have been proposed, including but not limited to finance, the Internet of Things, digital rights management, government, and law. In this chapter, four main industries namely the Internet of Things, government, health, and finance, have been selected, with the aid of use cases, for discussion. In 2010, discussion started regarding BitDNS, a decentralized naming system for domains on the internet. Then Namecoin (https://wiki.namecoin.org/index.php?title=History) started in April 2011 with a different vision as compared to Bitcoin whose sole purpose is to provision electronic cash. This can be considered first example of blockchain usage other than purely cryptocurrencies. After this by 2013, many ideas emerged. Since 2013 this trend is growing exponentially. Internet of Things The Internet of Things (IoT) for short has recently gained much traction due to its potential for transforming business applications and everyday life.

PacktPub.com Contributors About the author About the reviewer Packt is searching for authors like you Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews Blockchain 101 The growth of blockchain technology Distributed systems The history of blockchain and Bitcoin Electronic cash Blockchain Blockchain defined Peer-to-peer Distributed ledger Cryptographically-secure Append-only Updateable via consensus Generic elements of a blockchain How blockchain works How blockchain accumulates blocks Benefits and limitations of blockchain Tiers of blockchain technology Features of a blockchain Types of blockchain Distributed ledgers Distributed Ledger Technology Public blockchains Private blockchains Semiprivate blockchains Sidechains Permissioned ledger Shared ledger Fully private and proprietary blockchains Tokenized blockchains Tokenless blockchains Consensus Consensus mechanism Types of consensus mechanisms Consensus in blockchain CAP theorem and blockchain Summary Decentralization Decentralization using blockchain Methods of decentralization Disintermediation Contest-driven decentralization Routes to decentralization How to decentralize The decentralization framework example Blockchain and full ecosystem decentralization Storage Communication Computing power and decentralization Smart contracts Decentralized Organizations Decentralized Autonomous Organizations Decentralized Autonomous Corporations Decentralized Autonomous Societies Decentralized Applications (DApps) Requirements of a Decentralized Application Operations of a DApp DApp examples KYC-Chain OpenBazaar Lazooz Platforms for decentralization Ethereum MaidSafe Lisk Summary Symmetric Cryptography Working with the OpenSSL command line Introduction Mathematics Set Group Field A finite field Order An abelian group Prime fields Ring A cyclic group Modular arithmetic Cryptography Confidentiality Integrity Authentication Entity authentication Data origin authentication Non-repudiation Accountability Cryptographic primitives Symmetric cryptography Stream ciphers Block ciphers Block encryption mode Electronic Code Book Cipher Block Chaining Counter mode Keystream generation mode Message authentication mode Cryptographic hash mode Data Encryption Standard Advanced Encryption Standard How AES works Summary Public Key Cryptography Asymmetric cryptography Integer factorization Discrete logarithm Elliptic curves Public and private keys RSA Encryption and decryption using RSA Elliptic Curve Cryptography Mathematics behind ECC Point addition Point doubling Discrete logarithm problem in ECC RSA using OpenSSL RSA public and private key pair Private key Public key Exploring the public key Encryption and decryption Encryption Decryption ECC using OpenSSL ECC private and public key pair Private key Private key generation Hash functions Compression of arbitrary messages into fixed-length digest Easy to compute Preimage resistance Second preimage resistance Collision resistance Message Digest Secure Hash Algorithms Design of Secure Hash Algorithms Design of SHA-256 Design of SHA-3 (Keccak) OpenSSL example of hash functions Message Authentication Codes MACs using block ciphers Hash-based MACs Merkle trees Patricia trees Distributed Hash Tables Digital signatures RSA digital signature algorithm Sign then encrypt Encrypt then sign Elliptic Curve Digital Signature Algorithm How to generate a digital signature using OpenSSL ECDSA using OpenSSL Homomorphic encryption Signcryption Zero-Knowledge Proofs Blind signatures Encoding schemes Financial markets and trading Trading Exchanges Orders and order properties Order management and routing systems Components of a trade The underlying instrument General attributes Economics Sales Counterparty Trade life cycle Order anticipators Market manipulation Summary Introducing Bitcoin Bitcoin Bitcoin definition Bitcoin&#xA0;&#x2013; a bird's-eye view Sending a payment to someone Digital keys and addresses Private keys in Bitcoin Public keys in Bitcoin Addresses in Bitcoin Base58Check encoding Vanity addresses Multisignature addresses Transactions The transaction life cycle Transaction fee Transaction pools The transaction data structure Metadata Inputs Outputs Verification The script language Commonly used opcodes Types of transactions Coinbase transactions Contracts Transaction veri&#xFB01;cation Transaction malleability Blockchain The structure of a block The structure of a block header The genesis block Mining Tasks of the miners Mining rewards Proof of Work (PoW) The mining algorithm The hash rate Mining systems CPU GPU FPGA ASICs Mining pools Summary Bitcoin Network and Payments The Bitcoin network Wallets Non-deterministic wallets Deterministic wallets Hierarchical Deterministic wallets Brain wallets Paper wallets Hardware wallets Online wallets Mobile wallets Bitcoin payments Innovation in Bitcoin Bitcoin Improvement Proposals (BIPs) Advanced protocols Segregated Witness (SegWit) Bitcoin Cash Bitcoin Unlimited Bitcoin Gold Bitcoin investment and buying and selling bitcoins Summary Bitcoin Clients and APIs Bitcoin installation Types of Bitcoin Core clients Bitcoind Bitcoin-cli Bitcoin-qt Setting up a Bitcoin node Setting up the source code Setting up bitcoin.conf Starting up a node in testnet Starting up a node in regtest Experimenting with Bitcoin-cli Bitcoin programming and the command-line interface Summary Alternative Coins Theoretical foundations Alternatives to Proof of Work Proof of Storage Proof of Stake (PoS) Various stake types Proof of coinage Proof of Deposit (PoD) Proof of Burn Proof of Activity (PoA) Nonoutsourceable puzzles Difficulty adjustment and retargeting algorithms Kimoto Gravity Well Dark Gravity Wave DigiShield MIDAS Bitcoin limitations Privacy and anonymity Mixing protocols Third-party mixing protocols Inherent anonymity Extended protocols on top of Bitcoin Colored coins Counterparty Development of altcoins Consensus algorithms Hashing algorithms Difficulty adjustment algorithms Inter-block time Block rewards Reward halving rate Block size and transaction size Interest rate Coinage Total supply of coins Namecoin Trading Namecoins Obtaining Namecoins Generating Namecoin records Litecoin Primecoin Trading Primecoin Mining guide Zcash Trading Zcash Mining guide Address generation GPU mining Downloading and compiling nheqminer Initial Coin Offerings (ICOs) ERC20 tokens Summary Smart Contracts History Definition Ricardian contracts Smart contract templates Oracles Smart Oracles Deploying smart contracts on a blockchain The DAO Summary Ethereum 101 Introduction The yellow paper Useful mathematical symbols Ethereum blockchain Ethereum &#x2013; bird's eye view The Ethereum network Mainnet Testnet Private net Components of the Ethereum ecosystem Keys and addresses Accounts Types of accounts Transactions and messages Contract creation transaction Message call transaction Messages Calls Transaction validation and execution The transaction substate State storage in the Ethereum blockchain The world state The account state Transaction receipts Ether cryptocurrency / tokens (ETC and ETH) The Ethereum Virtual Machine (EVM) Execution environment Machine state The iterator function Smart contracts Native contracts Summary Further Ethereum Programming languages Runtime bytecode Opcodes and their meaning Arithmetic operations Logical operations Cryptographic operations Environmental information Block information Stack, memory, storage, and &#xFB02;ow operations Push operations Duplication operations Exchange operations Logging operations System operations Blocks and blockchain The genesis block The block validation mechanism Block finalization Block difficulty Gas Fee schedule Forks in the blockchain Nodes and miners The consensus mechanism Ethash CPU mining GPU mining Benchmarking Mining rigs Mining pools Wallets and client software Geth Eth Pyethapp Parity Light clients Installation Eth installation Mist browser Geth The geth console Funding the account with bitcoin Parity installation Creating accounts using the parity command line APIs, tools, and DApps Applications (DApps and DAOs) developed on Ethereum Tools Supporting protocols Whisper Swarm Scalability, security, and other challenges Trading and investment Summary Ethereum Development Environment Test networks Setting up a private net Network ID The genesis file Data directory Flags and their meaning Static nodes Starting up the private network Running Mist on private net Deploying contracts using Mist Block explorer for private net / local Ethereum block explorer Summary Development Tools and Frameworks Languages Compilers Solidity compiler (solc) Installation on Linux Installation on macOS Integrated Development Environments (IDEs) Remix Tools and libraries Node version 7 EthereumJS Ganache MetaMask Truffle Installation Contract development and deployment Writing Testing Solidity language Types Value types Boolean Integers Address Literals Integer literals String literals Hexadecimal literals Enums Function types Internal functions External functions Reference types Arrays Structs Data location Mappings Global variables Control structures Events&#xA0; Inheritance Libraries Functions Layout of a Solidity source code &#xFB01;le Version pragma Import Comments Summary Introducing Web3 Web3 Contract deployment POST requests The HTML and JavaScript frontend Installing web3.js Example Creating a web3 object Checking availability by calling any web3 method Contract functions Development frameworks Truffle Initializing Truffle Interaction with the contract Another example An example project&#xA0;&#x2013; Proof of Idea Oracles Deployment on decentralized storage using IPFS Installing IPFS Distributed ledgers Summary Hyperledger Projects under Hyperledger Fabric Sawtooth Lake Iroha Burrow Indy Explorer Cello Composer Quilt Hyperledger as a protocol The reference architecture Requirements and design goals of Hyperledger Fabric The modular approach Privacy and confidentiality Scalability Deterministic transactions Identity Auditability Interoperability Portability Rich data queries Fabric Hyperledger Fabric Membership services Blockchain services Consensus services Distributed ledger The peer to peer protocol Ledger storage Chaincode services Components of the fabric Peers Orderer nodes Clients Channels World state database Transactions Membership Service Provider (MSP) Smart contracts Crypto service provider Applications on blockchain Chaincode implementation The application model Consensus in Hyperledger Fabric The transaction life cycle in Hyperledger Fabric Sawtooth Lake PoET Transaction families Consensus in Sawtooth The development environment&#xA0;&#x2013; Sawtooth Lake Corda Architecture State objects Transactions Consensus Flows Components Nodes The permissioning service Network map service Notary service Oracle service Transactions Vaults CorDapp The development environment&#xA0;&#x2013; Corda Summary Alternative Blockchains Blockchains Kadena Ripple Transactions Payments related Order related Account and security-related Interledger Application layer Transport layer Interledger layer Ledger layer Stellar Rootstock Sidechain Drivechain Quorum Transaction manager Crypto Enclave QuorumChain Network manager Tezos Storj MaidSafe BigchainDB MultiChain Tendermint Tendermint Core Tendermint Socket Protocol (TMSP) Platforms and frameworks Eris Summary Blockchain &#x2013; Outside of Currencies Internet of Things Physical object layer Device layer Network layer Management layer Application layer IoT blockchain experiment First node setup Raspberry Pi node setup Installing Node.js Circuit Government Border control Voting Citizen identification (ID cards) Miscellaneous Health Finance Insurance Post-trade settlement Financial crime prevention Media Summary Scalability and Other Challenges Scalability Network plane Consensus plane Storage plane View plane Block size increase Block interval reduction Invertible Bloom Lookup Tables Sharding State channels Private blockchain Proof of Stake Sidechains Subchains Tree chains (trees) Block propagation Bitcoin-NG Plasma Privacy Indistinguishability Obfuscation Homomorphic encryption Zero-Knowledge Proofs State channels Secure multiparty computation Usage of hardware to provide confidentiality CoinJoin Confidential transactions MimbleWimble Security Smart contract security Formal verification and analysis Oyente tool Summary Current Landscape and What&#x27;s Next Emerging trends Application-specific blockchains (ASBCs) Enterprise-grade blockchains Private blockchains Start-ups Strong research interest Standardization Enhancements Real-world implementations Consortia Answers to technical challenges Convergence Education of blockchain technology Employment Cryptoeconomics Research in cryptography New programming languages Hardware research and development Research in formal methods and security Alternatives to blockchains Interoperability efforts Blockchain as a Service Efforts to reduce electricity consumption Other challenges Regulation Dark side Blockchain research Smart contracts Centralization issues Limitations in cryptographic functions Consensus algorithms Scalability Code obfuscation Notable projects Zcash on Ethereum CollCo Cello Qtum Bitcoin-NG Solidus Hawk Town-Crier SETLCoin TEEChan Falcon Bletchley Casper Miscellaneous tools Solidity extension for Microsoft Visual Studio MetaMask Stratis Embark DAPPLE Meteor uPort INFURA Convergence with other industries Future Summary Another Book You May Enjoy Leave a review&#xA0;&#x2013; let other readers know what you think Preface This book has one goal, to introduce theoretical and practical aspects of the blockchain technology.

Chapter 15, Hyperledger, presents a discussion about the Hyperledger project from the Linux Foundation, which includes different blockchain projects introduced by its members. Chapter 16, Alternative Blockchains, introduces alternative blockchain solutions and platforms. It provides technical details and features of alternative blockchains and relevant platforms. Chapter 17, Blockchain – Outside of Currencies, provides a practical and detailed introduction to applications of blockchain technology in fields others than cryptocurrencies, including Internet of Things, government, media, and finance. Chapter 18, Scalability and Other Challenges, is dedicated to a discussion of the challenges faced by blockchain technology and how to address them. Chapter 19, Current Landscape and What's Next, is aimed at providing information about the current landscape, projects, and research efforts related to blockchain technology. Also, some predictions based on the current state of blockchain technology have also been made.


pages: 144 words: 43,356

Surviving AI: The Promise and Peril of Artificial Intelligence by Calum Chace

"Robert Solow", 3D printing, Ada Lovelace, AI winter, Airbnb, artificial general intelligence, augmented reality, barriers to entry, basic income, bitcoin, blockchain, brain emulation, Buckminster Fuller, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, dematerialisation, discovery of the americas, disintermediation, don't be evil, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Google Glasses, hedonic treadmill, industrial robot, Internet of things, invention of agriculture, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, life extension, low skilled workers, Mahatma Gandhi, means of production, mutually assured destruction, Nicholas Carr, pattern recognition, peer-to-peer, peer-to-peer model, Peter Thiel, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, South Sea Bubble, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Jobs, strong AI, technological singularity, The Future of Employment, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E, zero-sum game

Happy in the full possession of her vegetables, she drove home, humming along to Joni Mitchell. 2.2 – Converting information into knowledge – at different speeds The science fiction writer William Gibson is reported as saying that “The future is already here – it’s just not evenly distributed.” (13) Most of the things mentioned in the short story above are already available in prototype and early incarnations, and the rest is firmly under development – some of it as part of the so-called “internet of things”. It could take anywhere from five to fifteen years for you to have working versions of all of them. Some people will think the life described above is frightening, perhaps de-humanised. It is likely that more people will welcome the assistance, and of course generations to come will simply take it for granted. As Douglas Adams said, anything invented after you’re thirty-five is against the natural order of things, anything invented between when you’re fifteen and thirty-five is new and exciting, and anything that is in the world when you’re born is just a natural part of the way the world works. (14) Of course there is no guarantee that the future will work out this way – in fact the details are bound to be different.

As Douglas Adams said, anything invented after you’re thirty-five is against the natural order of things, anything invented between when you’re fifteen and thirty-five is new and exciting, and anything that is in the world when you’re born is just a natural part of the way the world works. (14) Of course there is no guarantee that the future will work out this way – in fact the details are bound to be different. For example we don’t yet know whether the myriad devices connecting up to the Internet of Things will communicate with us directly, or via personal digital assistants like Hermione. Will you be reminded to take your pill in the morning because its bottle starts glowing, or will Hermione alert you? No doubt the outcome will seem obvious in hindsight. It has been said that all industries are now part of the information industry – or heading that way. Much of the cost of developing a modern car – and much of the quality of its performance – lies in the software that controls it.

Creating an AGI is very hard. But serious consideration of exponential growth makes very hard problems seem more tractable. Buckminster Fuller estimated that at the start of the twentieth century the sum of human knowledge was doubling every century, and that by the end of the second world war that had reduced to twenty-five years. (40) Now it takes 13 months and in 2006 IBM estimated that when the internet of things becomes a reality the rate would be every 12 hours. (41) The football stadium thought experiment illustrates how progress at exponential rate can take you by surprise – even when you are looking for it. Many sensible people become suspicious when they hear the phrase exponential growth: they fear it used as a cover for wishful (or so-called “magical”) thinking. Others question how long Moore’s Law can continue.


pages: 602 words: 177,874

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations by Thomas L. Friedman

3D printing, additive manufacturing, affirmative action, Airbnb, AltaVista, Amazon Web Services, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Bob Noyce, business cycle, business process, call centre, centre right, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, corporate social responsibility, creative destruction, crowdsourcing, David Brooks, demand response, demographic dividend, demographic transition, Deng Xiaoping, Donald Trump, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Ferguson, Missouri, first square of the chessboard / second half of the chessboard, Flash crash, game design, gig economy, global pandemic, global supply chain, illegal immigration, immigration reform, income inequality, indoor plumbing, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the steam engine, inventory management, Irwin Jacobs: Qualcomm, Jeff Bezos, job automation, John Markoff, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, Live Aid, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Nelson Mandela, pattern recognition, planetary scale, pull request, Ralph Waldo Emerson, ransomware, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, South China Sea, Steve Jobs, supercomputer in your pocket, TaskRabbit, The Rise and Fall of American Growth, Thomas L Friedman, transaction costs, Transnistria, uber lyft, undersea cable, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra, zero-sum game

GE, thanks in large part to its accelerating ability to put sensors all over its industrial equipment, is becoming more of a software company, with a big base now in Silicon Valley. Forget about washing machines—think intelligent machines. GE’s ability to install sensors everywhere is helping to make possible the “industrial Internet,” also known as the “Internet of Things” (IoT), by enabling every “thing” to carry a sensor that broadcasts how it is feeling at any moment, thus allowing its performance to be immediately adjusted or predicted in response. This Internet of Things, Ruh explained, “is creating a nervous system that will allow humans to keep up with the pace of change, make the information load more usable,” and basically “make every thing intelligent.” General Electric itself gathers data from more than 150,000 GE medical devices, 36,000 GE jet engines, 21,500 GE locomotives, 23,000 GE wind turbines, 3,900 gas turbines, and 20,700 pieces of oil and gas equipment, all of which wirelessly report to GE how they are feeling every minute.

IBM ice sheets; shrinking of identity, proof of IEDs (improvised explosive devices) IEX illiteracy Ilulissat, Greenland Immelt, Jeff immigrants, immigration; diversity and; as entrepreneurs; into Europe; integration of; policy reform for imperialism, fading of inclusion, ethos of India; connectivity in Indian Institute of Technology Indonesia Industrial Revolution; Second inflection points; age of accelerations; year 2000; year 2007 information technology revolution infrastructure; in weak states innovation: in geopolitics; global flows and; in India; lag between consequences and; in Mexico; in post–post–Cold War geopolitics; as response to change; in social technologies; supernova and; see also education, innovation in; ethics, innovation in; politics, innovation in; software innovation; technological change; workforce, innovation in Institute for the Future integrated circuits; Moore’s law and Intel intelligent algorithms intelligent assistance; AT&T and; skill sets and intelligent assistants; education and; job seekers and; workforce and interdependence; in ecosystems; in financial flow; in geopolitics; healthy vs. unhealthy; of natural systems International Commission on Stratigraphy International Institute for Strategic Studies International Journal of Business, Humanities, and Technology International Organization for Migration International Rescue Committee Internet; cloud and, see supernova (cloud computing); digital divide and; GDP and; government policy on; mobile phones and; weak states and Internet of Things Internet of Things Foundry intuition, and detection of weak signals Invictus (film) Iorio, Luana iOS iPhones; AT&T’s gamble on Iran Iraq Iraq War Isbin, Sharon Islam Islamic State (ISIS); videos by Islamists Islamist terrorism isolation, as disease Israel Israeli-Palestinian War (1982) Istanbul Itasca Project Ixigo.com Jabr, Jumana Jacklin, Tony Jackson, Wes Jacobs, Irwin Jacobs, Jeff Jacobs, Lawrence Jacobs, Paul Japan Japanese Americans Jennings, Ken Jennings, Peter Jeopardy!

By expanding its business model from mailing DVDs to selling subscriptions for online streaming, Netflix has dramatically broadened its international reach to more than 190 countries. While media, music, books, and games represent the first wave of digital trade, 3-D printing could eventually expand digital commerce to many more product categories. And forget the fact that so many “friends” are connecting on Facebook. How about all the “things” getting to know one another? You want to see flows—wait until the “Internet of Things” gets to scale and machines start talking to machines everywhere and always! “Only 0.6 percent of things are connected today,” Plamen Nedeltchev, distinguished IT engineer at Cisco, wrote on Cisco.com in an essay entitled “It is inevitable. It is here. Are we ready?” on September 29, 2015. “There were 1,000 Internet-connected devices in 1984,” said the article, a million in 1992, and ten billion in 2008.


pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, disruptive innovation, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, global pandemic, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joi Ito, Khan Academy, knowledge worker, labor-force participation, lifelogging, longitudinal study, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, social intelligence, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

By now, heavy use of embedded analytics, or operational analytics, has given rise to what Tom has elsewhere called “Analytics 3.0,” a new era in which data drive the workings of organizations at dramatically greater speed and scale.5 Gartner, the IT market research firm, recognized “advanced, pervasive, and invisible analytics” as one of its “ten strategic technologies for 2015.”6 Bill Franks, the chief analytics officer of Teradata, is referring to the same transformation in his book on operational analytics called The Analytics Revolution. If you are already weary of the buzzwords “big data” and “the Internet of things,” this is why; both represent fire hoses of data that become extremely valuable when the computing power is in place to find patterns and make decisions to capitalize on them. Already today, the Internet connects more smart objects than people (and has thus become an Internet of things); by 2020, Cisco estimates, the number of devices connected to the Internet will rise to 50 billion.7 As they transmit data in near-real time, fast computers are able to make frequent decisions based on continuous analysis. Sensors in a jet engine, for example, collect and transmit data on heat, vibration, and other conditions, allowing a smart machine to schedule service as needed, or to advise a pilot to shut it down as soon as possible.

The most sophisticated underwriting systems generate literally millions of different pricing cells and do so easily, because it is only a matter of following logical rules and equations. Computer systems gain an even greater advantage as devices with sensors—cars, trucks, boilers, and other types of equipment—start reporting regularly on their own performance and usage. With such massive amounts of data to consider, humans are truly out of their league. Dealing with the “Internet of things” is something computers are capable of. Humans, not so much. Yet that doesn’t have to be the end of the story. Underwriters who can learn to focus on other strengths they bring to the job can survive this capture of its core, and even come out better for it—perhaps never regretting that forgone career as pro baseball player, ballerina, or astronaut. The Underwriter Who Steps Up One way to respond to a computer encroaching on your work is to see it as that extremely competent assistant that allows you to step up—which, in the realm of underwriting, might mean taking responsibility for “portfolio management.”

At the Baylor College of Medicine in Dallas, they used it to read through more than 70,000 scientific articles, looking for accounts of any protein that could modify p53, a protein that regulates cancer growth. Most scientists would struggle to identify one such protein in a year; Watson took only a few weeks to find six (although, to be fair, it took several years to prepare Watson to do this).6 Other organizations are using similar technologies to glean insights from natural-language content that exists in enormous volume. Or think about the “Internet of things”—the ability to place small sensors on objects in the physical world and have them communicate readings in real time. The rise of this technology has been governed by the rise of computers with the processing power to deal with the immense amounts of data produced; unaided humans could not conceivably monitor and control the vast sensor networks used to, for example, detect if a tsunami is brewing far offshore.


pages: 340 words: 97,723

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

Ada Lovelace, AI winter, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, Asilomar, autonomous vehicles, Bayesian statistics, Bernie Sanders, bioinformatics, blockchain, Bretton Woods, business intelligence, Cass Sunstein, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Deng Xiaoping, distributed ledger, don't be evil, Donald Trump, Elon Musk, Filter Bubble, Flynn Effect, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, Mark Zuckerberg, Menlo Park, move fast and break things, move fast and break things, natural language processing, New Urbanism, one-China policy, optical character recognition, packet switching, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Sand Hill Road, Second Machine Age, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

The Annotated Turing: A Guided Tour Through Alan Turing’s Historic Paper on Computability and the Turing Machine. Indianapolis, IN: Wiley Publishing, 2008. Pylyshyn, Z. W., ed. The Robot’s Dilemma: The Frame Problem in Artificial Intelligence. Norwood, NJ: Ablex, 1987. Riedl, M. O. “The Lovelace 2.0 Test of Artificial Creativity and Intelligence.” https://arxiv.org/pdf/1410.6142.pdf. Schneier, B. “The Internet of Things Is Wildly Insecure—and Often Unpatchable.” Wired, January 6, 2014. https://www.wired.com/2014/01/theres-no-good-way-to-patch-the-Internet-of-things-and-thats-a-huge-problem/. Shannon, C., and W. Weaver. The Mathematical Theory of Communication. Urbana: University of Illinois Press, 1963. Singer, P. Wired for War: The Robotics Revolution and Conflict in the 21st Century. London: Penguin Press, 2009. Stanford University. “One Hundred Year Study on Artificial Intelligence (AI100).” https://ai100.stanford.edu/.

As AI systems advance and more of everyday life gets automated, the less control we actually have over the decisions being made about and for us. This, in turn, has a compounding effect on the future of many other technologies adjacent to or directly intersecting with AI: autonomous vehicles, CRISPR and genomic editing, precision medicine, home robotics, automated medical diagnoses, green- and geoengineering technologies, space travel, cryptocurrencies and blockchain, smart farms and agricultural technologies, the Internet of Things, autonomous factories, stock-trading algorithms, search engines, facial and voice recognition, banking technologies, fraud and risk detection, policing and judicial technologies… I could make a list that spans dozens of pages. There isn’t a facet of your personal or professional life that won’t be impacted by AI. What if, in a rush to get products to market or to please certain government officials, your values aren’t reflected not just in AI but in all of the systems it touches?

You, along with tens of thousands of consumers report outages, and each time the G-MAFIA dedicates a few product managers to research what’s going wrong. Tech journalists attribute the glitches to the “spooky ways” in which “AI acts weird sometimes.” At first, the attacks seem novel and random. So we all blame Google, Apple, and Amazon for faulty products and crappy customer service. Then cybersecurity experts are gobsmacked to discover all the glitches are actually linked. It is a new kind of “Internet of Things” attack originating in China and enabled by machine learning. The Chinese have a name for it: , or bèi kùn, which translates to “trapped.” The hackers, backed by the Chinese government, thought it was clever to launch “bacon” attacks during breakfast hours in America and to effectively trap our food, drinks, and eating utensils in our AI-powered appliances. Their purpose is singular and sophisticated: to seed mistrust in the G-MAFIA.


pages: 238 words: 73,824

Makers by Chris Anderson

3D printing, Airbnb, Any sufficiently advanced technology is indistinguishable from magic, Apple II, autonomous vehicles, barriers to entry, Buckminster Fuller, Build a better mousetrap, business process, commoditize, Computer Numeric Control, crowdsourcing, dark matter, David Ricardo: comparative advantage, death of newspapers, dematerialisation, Elon Musk, factory automation, Firefox, future of work, global supply chain, global village, IKEA effect, industrial robot, interchangeable parts, Internet of things, inventory management, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, Lean Startup, manufacturing employment, Mark Zuckerberg, means of production, Menlo Park, Network effects, private space industry, profit maximization, QR code, race to the bottom, Richard Feynman, Ronald Coase, Rubik’s Cube, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, South of Market, San Francisco, spinning jenny, Startup school, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, transaction costs, trickle-down economics, Whole Earth Catalog, X Prize, Y Combinator

This construction—“atoms” versus “bits”—originated with the work of a number of thinkers from the MIT Media Lab, starting with its founder, Nicholas Negroponte, and today most prominently exemplified by Neal Gershenfeld and the MIT Center for Bits and Atoms. It is shorthand for the distinction between software and hardware, or information technology and Everything Else. Today the two are increasingly blurring as more everyday objects contain electronics and are connected to other objects, the so-called Internet of Things. That’s part of what we’ll be talking about here. But even more, we’ll look at how it’s changing manufacturing, otherwise known as the flippin’ Engine of the World Economy. The idea of a “factory” is, in a word, changing. Just as the Web democratized innovation in bits, a new class of “rapid prototyping” technologies, from 3-D printers to laser cutters, is democratizing innovation in atoms.

This is often called “physical computing” or “embedded computing,” and you see examples of it all around you. Practically every electronic device in your home works this way, from your thermostat to your alarm clocks, stereos, microwave oven, and portable music players. Your car has dozens of embedded computers. The difference is that they are all closed and proprietary, while Arduino is designed to be easy for anyone to use and modify. Much of the emerging “Internet of Things” movement is built on Arduino-based devices connected to the Web, from coffeemakers that tweet their status to pet feeders you can control from your phone, wherever you are. So, because I knew it best, I decided to base the sprinkler controller on Arduino. That meant it could tap into a huge community of people who are using Arduino for all sorts of other purposes, and who had already solved most of the problems of connecting it to the Internet and any sensor you can imagine.

Then they asked for Bluetooth 4.0, with its lower power consumption, rather than the original Bluetooth 2.0 (or Sony’s 3.0). So the team, emboldened by its flood of orders, went looking for the right 4.0 modules and were able to source them, giving the watch better battery life and making it more future-proof. Finally, other Kickstarter projects joined the parade and announced that they would be writing apps to run on Pebble, including Twine, an “Internet of Things” device that could let Pebble do things like tell you when someone’s knocking at your door. As of this writing, Pebble has not yet shipped its watches (they’re due in September 2012), and perhaps production glitches will mar or delay the launch. But even before that, it’s not hard to see in Pebble a superior model: a small team using crowdfunding to move more quickly in all ways—R&D, finance, and marketing—than a lumbering electronics giant.


pages: 588 words: 131,025

The Patient Will See You Now: The Future of Medicine Is in Your Hands by Eric Topol

23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, commoditize, computer vision, conceptual framework, connected car, correlation does not imply causation, creative destruction, crowdsourcing, dark matter, data acquisition, disintermediation, disruptive innovation, don't be evil, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, job automation, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta analysis, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, RAND corporation, randomized controlled trial, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, X Prize

When patients with like conditions can connect with and learn from each other, without the constraints of time or place as they would have with a doctor’s visit, yet another critical dimension of democratized medicine is discernible. FIGURE 1.3: The rise in connected devices on the Internet of Things from 2003 to 2020, projected. Source: D. Evans, “The Internet of Things: How the Next Evolution of the Internet is Changing Everything,” Cisco Internet Business Solutions Group, April 2011, http://www.cisco.com/web/about/ac79/docs/innov/IoT_IBSG_0411FINAL.pdf. Courtesy of Cisco Systems, Inc. Unauthorized use not permitted. August 1, 2014. The marked connectivity is taken further when one considers the Internet of Things (IoT). That is the unbridled growth of not only people but also devices that are wirelessly connected via the Internet. The projections range from twenty-eight to fifty billion connected devices by 2020,28 and the implications are profound.

It is inextricably linked to the democratization of medicine. The prospect here would not be possible without exquisite tracking of individuals by themselves—recall the double entendre of the term “individualized medicine.”6 Picking up a signal long before there are any symptoms relies on one’s GIS, not an annual visit with the doctor. With the little wireless devices that we carry and the Internet of Things, we’re developing the capability of continuous, critical, real-time surveillance of our bodies. When that gets fully developed, as it ultimately will, The Economist’s predictions for the next thirty years in medicine don’t seem as far-fetched. FIGURE 13.1: Increase in life expectancy and projection for most diseases “cured.” Source: Adapted from “A Survey of the Future of Medicine,” The Economist, March 19, 1994, http://www.highbeam.com/doc/1G1–15236568.html.

The Framing of Physical Activity Biases Subsequent Snacking,” Marketing Letters, May 27, 2014, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2442383. 60a. E. Topol, The Creative Destruction of Medicine (New York, NY: Basic Books, 2012), 126–127. 60b. N. Gohring, “This Company Saved $300k on Insurance by Giving Employees Fitbits,” Cite World, July 7, 2014: http://www.citeworld.com/article/2450823/internet-of-things/appirio-fitbit-experiment.html. 60c. P. Olson, “Wearable Tech Is Plugging into Health Insurance,” Forbes, June 19, 2014, http://www.forbes.com/sites/parmyolson/2014/06/19/wearable-tech-health-insurance/. 61. S. Lohr, “Salesforce Takes Its Cloud Model to Health Care,” New York Times, June 26, 2014, http://bits.blogs.nytimes.com/2014/06/26/salesforce-takes-its-cloud-model-to-health-care/. 62.


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Postcapitalism: A Guide to Our Future by Paul Mason

Alfred Russel Wallace, bank run, banking crisis, banks create money, Basel III, basic income, Bernie Madoff, Bill Gates: Altair 8800, bitcoin, Branko Milanovic, Bretton Woods, BRICs, British Empire, business cycle, business process, butterfly effect, call centre, capital controls, Cesare Marchetti: Marchetti’s constant, Claude Shannon: information theory, collaborative economy, collective bargaining, Corn Laws, corporate social responsibility, creative destruction, credit crunch, currency manipulation / currency intervention, currency peg, David Graeber, deglobalization, deindustrialization, deskilling, discovery of the americas, Downton Abbey, drone strike, en.wikipedia.org, energy security, eurozone crisis, factory automation, financial repression, Firefox, Fractional reserve banking, Frederick Winslow Taylor, full employment, future of work, game design, income inequality, inflation targeting, informal economy, information asymmetry, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, low skilled workers, market clearing, means of production, Metcalfe's law, microservices, money: store of value / unit of account / medium of exchange, mortgage debt, Network effects, new economy, Norbert Wiener, Occupy movement, oil shale / tar sands, oil shock, Paul Samuelson, payday loans, Pearl River Delta, post-industrial society, precariat, price mechanism, profit motive, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, RFID, Richard Stallman, Robert Gordon, Robert Metcalfe, secular stagnation, sharing economy, Stewart Brand, structural adjustment programs, supply-chain management, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, Transnistria, union organizing, universal basic income, urban decay, urban planning, Vilfredo Pareto, wages for housework, WikiLeaks, women in the workforce

Soon the information will be flowing from ‘smart’ electricity meters, public transport passes and computer-controlled cars. The aggregated data of our lives – which will soon include our driving speed, our weekly diet, our body mass and heart rate – could be a hugely powerful ‘social technology’ in itself. Once the Internet of Things is rolled out, we are at the real takeoff point of the information economy. From then on, the key principle is to create democratic social control over aggregated information, and to prevent its monopolization or misuse by states and corporations. The Internet of Things will complete a vast social ‘machine’. Its analytical power alone could optimize resources on a scale that significantly reduces the use of carbon, raw materials and labour. Making the energy grid, the road network and the tax system ‘intelligent’ are just the most obvious things on the task list.

In terms of data storage, 2002 was the year in which the volume of digital information in the world overtook the amount of analog information. Between 2006 and 2012 humanity’s annual information output grew tenfold.25 It’s hard to tell exactly where you are in a tech revolution but my hunch is the simultaneous arrival of tablets, streaming video and music and the takeoff of social media between 2009 and 2014 will be seen as the key moment of synergy. The rollout of billions of machine-to-machine connections, known as the ‘Internet of Things’, in the next ten years will then populate the global information network with more intelligent devices than there are people on earth. To live through all this was exhilarating enough. Even more exhilarating now is to watch a kid get their first smartphone and find it all – Bluetooth, GPS, 3G, wifi, streaming video, hi-res photography and heart-rate monitor – as if it had always been there.

Jeremy Rifkin, an influential management consultant, came closest to describing current reality in his 2014 book The Zero Marginal Cost Society.53 Rifkin argues that peer-production and capitalism are two different systems; currently they coexist and even gain energy from each other, but ultimately peer-production will reduce the capitalist sector of the economy to a few niches. Rifkin’s most radical insight was to understand the potential of the Internet of Things. The most enthusiastic consultancies – for example McKinsey – have valued the impact of this process as up to $6 trillion a year, mainly in healthcare and manufacturing. But the vast majority of that $6 trillion is in reduced cost and increased efficiency: that is, it contributes to reducing the marginal cost of physical goods and services in the same way as copy and paste reduces the cost of information goods.


pages: 343 words: 102,846

Trees on Mars: Our Obsession With the Future by Hal Niedzviecki

"Robert Solow", Ada Lovelace, agricultural Revolution, Airbnb, Albert Einstein, anti-communist, big data - Walmart - Pop Tarts, big-box store, business intelligence, Colonization of Mars, computer age, crowdsourcing, David Brooks, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Flynn Effect, Google Glasses, hive mind, Howard Zinn, if you build it, they will come, income inequality, Internet of things, invention of movable type, Jaron Lanier, Jeff Bezos, job automation, John von Neumann, knowledge economy, Kodak vs Instagram, life extension, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Peter H. Diamandis: Planetary Resources, Peter Thiel, Pierre-Simon Laplace, Ponzi scheme, precariat, prediction markets, Ralph Nader, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, rising living standards, Ronald Reagan, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, TaskRabbit, technological singularity, technoutopianism, Ted Kaczynski, Thomas L Friedman, Uber and Lyft, uber lyft, working poor

IT is what allows, as the Race Against the Machine authors put it, “digital technologies” to execute “mental tasks that had been the exclusive domain of humans in the past.”37 An MIT Sloan School of Management study revealed that companies that had invested in some form of “data-driven decision-making” had their productivity go up by as much as 6 percent compared to similar firms.38 The obvious conclusion was that more and more companies would be putting in place these systems. They have and continue to do so. This can be seen particularly in what has come to be called “the Internet of things,” essentially the move to connect everyday devices from toothbrushes to thermostats to ovens to the Internet. Writes social theorist Jeremy Rifkin: “Cisco forecasts that by 2022, private-sector productivity gains wrought by the Internet of Things will exceed $14 trillion. A General Electric study estimates that productivity advances from the Internet of Things could affect half the global economy by 2025.”39 The systems are working. Productivity is skyrocketing. Efficiency is impressive. Money is pouring into the coffers. IT doesn’t need health benefits, doesn’t go on maternity leave, and doesn’t get a pension.

Thompson cites the ever-increasing trail of data we leave behind while we go about our lives as the great shift that makes all this possible: “Cell phone, CRM [customer relationship management] systems, point of sale,” but also, he notes, “check in on places like Foursquare or searches on Yelp, some of it is social media, tweets, some of it is really in the stream—all these devices are monitored in real time so your presence and location can be captured.” The much-touted and vaunted move to mobile technologies—primarily phones that operate via cellular signal but also an evolving array of eyeglasses, watches, and other objects gradually joining the Internet of things—are used to triangulate position (collectively or individually). With the position of just about everybody moving through a metropolis now reliably charted for the first time in human history, patterns and trends can be discerned. “Geography delivers context and understanding,” says Thompson. “Who are the people and where do they come from? How do different things interconnect?” The same approach is increasingly being used in the rise of what has come to be called predictive policing.

Though we’re inarguably now living in a state of permanent anxiety and stress, we are still gamely trying to make it work, trying to bring the imperative of change at all costs into our lives, trying to make our hearts beat in time to the relentless thrum of the future. If anything, as the levels of technological adoption of everything from the techniques of factory farming to smart phones to the Internet of things suggests, we have proven ourselves all too amenable to change. We eagerly bring new technologies into our lives with very little consideration for how each highly hyped, supposed innovation is going to alter our day-to-day. From traffic jams to TV dinners in front of the TV to drunk texting, the story of technology is littered with unintended consequences that we do our best to just shrug off.


pages: 170 words: 49,193

The People vs Tech: How the Internet Is Killing Democracy (And How We Save It) by Jamie Bartlett

Ada Lovelace, Airbnb, Amazon Mechanical Turk, Andrew Keen, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, Boris Johnson, central bank independence, Chelsea Manning, cloud computing, computer vision, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, Dominic Cummings, Donald Trump, Edward Snowden, Elon Musk, Filter Bubble, future of work, gig economy, global village, Google bus, hive mind, Howard Rheingold, information retrieval, Internet of things, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, Julian Assange, manufacturing employment, Mark Zuckerberg, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, mittelstand, move fast and break things, move fast and break things, Network effects, Nicholas Carr, off grid, Panopticon Jeremy Bentham, payday loans, Peter Thiel, prediction markets, QR code, ransomware, Ray Kurzweil, recommendation engine, Renaissance Technologies, ride hailing / ride sharing, Robert Mercer, Ross Ulbricht, Sam Altman, Satoshi Nakamoto, Second Machine Age, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, smart cities, smart contracts, smart meter, Snapchat, Stanford prison experiment, Steve Jobs, Steven Levy, strong AI, TaskRabbit, technological singularity, technoutopianism, Ted Kaczynski, the medium is the message, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, ultimatum game, universal basic income, WikiLeaks, World Values Survey, Y Combinator

I understand why people get nervous about psychographics, because the idea feels extremely manipulative. And of course it matters that data is harvested and used legally and ethically. But in one sense this is a distraction. The bigger picture is the way that companies like Cambridge Analytica understand our inner thoughts, rather than a distinct technique.* After all, just imagine what personality targeting will be possible with ‘the internet of things’. There are lots of stories these days about how internet-enabled devices present a security risk – like your fridge or baby monitor getting hacked. But think about what the explosion of everyday life data will do for political campaigns. Consider it: within a decade your fridge data will know what time you eat, your car will know where you’ve been, and your home assistant device will work out your approximate anger levels by the tone of your voice.

Being able to instantly send money to anywhere in the world with no fees, charges or banks will be especially liberating for people in countries with an over-leveraged banking sector run by corrupt politicians. It might even provide a secure digital payment option for the millions who are still excluded from the formal banking system. These are not trivial benefits. The economic boon of blockchain is potentially staggering – especially if twinned with the internet of things. Imagine a bridge with embedded sensors which could detect minor faults and necessary repairs. It could also track which vehicles have used it. Once a threshold of faults is reached, a smart contract could be automatically initiated, with every user charged immediately proportionate to their use. This could even have big benefits for how government works. The British Government hopes these immutable databases will create opportunities for a ‘greater transparency of transactions between government agencies and citizens’.

The reason this is so important is because I suspect future technology will increase further the ability of small groups of individuals to do great harm, which means the authorities will need greater power, not less. For reasons still not entirely clear to me, humanity is currently embarked on a quixotic quest to connect everything to everything else. Within a decade, your TV, dog, house, car, fridge and clothing, will be part of the invisible internet of things network, all chipped and communicating with each other. Sometimes they will be lifesaving: a smart fire alarm might immediately turn on your phone alarm, unlock your door and contact the fire brigade. But they will also be vulnerable, because the security standards for these ‘IoT’ devices are notoriously bad. There have already been high-profile examples of cardiac devices, cars, a baby monitor and home webcams being hacked.


pages: 83 words: 23,805

City 2.0: The Habitat of the Future and How to Get There by Ted Books

active transport: walking or cycling, Airbnb, Albert Einstein, big-box store, carbon footprint, cleantech, collaborative consumption, crowdsourcing, demand response, housing crisis, Induced demand, Internet of things, Jane Jacobs, jitney, Kibera, Kickstarter, Kitchen Debate, McMansion, megacity, New Urbanism, openstreetmap, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, smart cities, smart grid, the built environment, The Death and Life of Great American Cities, urban planning, urban renewal, urban sprawl, walkable city, Zipcar

Some of it will be collected and broadcast by our phones with little more than our permission. Ideally, we’ll get to choose how much data we share, with whom we share it, and how it will be used. Ultimately, it won’t be just our phones collecting and interfacing with the information around us. Data sensors will be embedded in streets, buildings, and even in cars and transit vehicles. Building such a network could bring about what many have called the Internet of Things — a concept that foresees the ability of physical objects and people to communicate and share information. A water pipe could tell a central computer that it’s about to fracture. A road could communicate with a streetlight to tell it that, after hours of sitting dark, it will need to illuminate for a car heading in its direction. An apartment building could determine that an oven is still on after the resident leaves for work and could switch it off.

For starters, there’s the persistent issue of technologies improving and becoming obsolete. It won’t be practical to invest millions of dollars implanting sensors across a city if they’re incompatible with new systems that will emerge a few years later. This is why it’s incredibly useful to have sensors embedded within the tools and objects we swap out frequently, like our phones and cars. In fact, much of the progress being made toward the Internet of Things has occurred in transportation. In the very near future, cars will communicate with other cars to improve the safety and flow of traffic. Google’s self-driving car is one high-profile example, but another project, run by the U.S. National Highway Traffic Safety Administration (NHTSA), is a more likely predictor of where this concept could go. The NHTSA recently launched a yearlong test enabling 2,800 cars in Ann Arbor, Mich., to effectively communicate directly with one another.


Digital Transformation at Scale: Why the Strategy Is Delivery by Andrew Greenway,Ben Terrett,Mike Bracken,Tom Loosemore

Airbnb, bitcoin, blockchain, butterfly effect, call centre, chief data officer, choice architecture, cognitive dissonance, cryptocurrency, Diane Coyle, en.wikipedia.org, G4S, Internet of things, Kevin Kelly, Kickstarter, loose coupling, M-Pesa, minimum viable product, nudge unit, performance metric, ransomware, Silicon Valley, social web, the market place, The Wisdom of Crowds

It becomes even easier for a large business or government administration to ignore hard yet necessary tasks if they can find something else that has the characteristics of work, while being much more comfortable to sink time into. Fortunately, the technology hype cycle is ready to provide a stream of distractions. All too often, the word digital is conflated with whatever technology fad has made it into the colour supplements this month. Blockchain. Artificial intelligence. The Internet of Things and connected devices. Robotic Process Automation. The captains of industry, ministers and senior officials who read colour supplements during their brief periods of down time see these exciting things and commission policy papers to unpick their potential effect on the organisations they run. The papers are good. But there is a gap – sometimes a huge gap – between policy or business school smarts and technological literacy.

You’ve annoyed people on the way of course – that’s a pity – so they think that perhaps now is the moment to consolidate the success and slow things down. If the digital team is all too tired to keep going, those keen to go back to an easy life will push back. Resisting the hype Every business strategy presentation for the last two years (and the next three) will have a slide that says something like: ‘AI, blockchain, Internet of Things – what should we do?’ For most organisations, this discussion is a little premature. Even allowing for the fact these technology breakthroughs are near the top of their hype cycle at the time of writing, we are not saying that they are unimportant for large organisations, public or private. Far from it. We’re confident that artificial intelligence, connected devices and advances in cryptography will change the world, in predictable and unexpected ways.

We have partnered with organisations in more than 20 countries, and worked in collaboration with several multilateral organisations, including the European Union and the ­Inter-American Development Bank. Andrew Greenway worked in five government departments, including the Government Digital Service, where he led the team that delivered the UK’s digital service standard. He also led a government review into applications of the Internet of Things, commissioned from Government’s Chief Scientific Advisor by the UK Prime Minister in 2014. He now writes for several UK and international publications on government and institutional reform. Ben Terrett was Director of Design at the Government Digital Service, where he led the multidisciplinary design team for GOV.UK which won the Design of the Year award in 2013. Before working in government, Ben was Design Director at Wieden + Kennedy and co-founder of The Newspaper Club.


pages: 346 words: 89,180

Capitalism Without Capital: The Rise of the Intangible Economy by Jonathan Haskel, Stian Westlake

"Robert Solow", 23andMe, activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, Andrei Shleifer, bank run, banking crisis, Bernie Sanders, business climate, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, cognitive bias, computer age, corporate governance, corporate raider, correlation does not imply causation, creative destruction, dark matter, Diane Coyle, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Glaeser, Elon Musk, endogenous growth, Erik Brynjolfsson, everywhere but in the productivity statistics, Fellow of the Royal Society, financial innovation, full employment, fundamental attribution error, future of work, Gini coefficient, Hernando de Soto, hiring and firing, income inequality, index card, indoor plumbing, intangible asset, Internet of things, Jane Jacobs, Jaron Lanier, job automation, Kenneth Arrow, Kickstarter, knowledge economy, knowledge worker, laissez-faire capitalism, liquidity trap, low skilled workers, Marc Andreessen, Mother of all demos, Network effects, new economy, open economy, patent troll, paypal mafia, Peter Thiel, pets.com, place-making, post-industrial society, Productivity paradox, quantitative hedge fund, rent-seeking, revision control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Sand Hill Road, Second Machine Age, secular stagnation, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, software patent, sovereign wealth fund, spinning jenny, Steve Jobs, survivorship bias, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, total factor productivity, Tyler Cowen: Great Stagnation, urban planning, Vanguard fund, walkable city, X Prize, zero-sum game

Meanwhile, in his masterful work on the Industrial Revolution, the economic historian Joel Mokyr divides “knowledge” into propositional and prescriptive (Mokyr 2002). How does all this fit together? Let’s start with data. Define two kinds of data: raw records and transformed data. Raw records are raw data not yet cleaned up, formatted, or transformed—not ready for analysis. They can include, for instance, data scraped from the web, data generated by transactions between agents, data generated by sensors embedded in machines or equipment (the “Internet of Things”), or data generated as a by-product of some other business operation or process. Transformed data has been cleaned up, formatted, combined, and/or structured such that it is suitable for some form of data analytics. Turning to information, we can think of information as synonymous with transformed data: for example, analyzable data on, say, sales of hurricane lamps and weather, constitutes information.

The microwave oven was a success not just because of the radical leap from military communications to cooking, but also because lots of researchers from Amana, Litton, and their Japanese competitors worked on the design and improved the technology of the magnetron. Sometimes this coordination happens spontaneously. But we can also think of things that help it along. Prizes, like the eighteenth-century Longitude Prize or the twenty-first-century Ansari-X Prize for private spaceflight, can help crowd investment into a neglected area. No doubt, part of the reason the technology press hypes new technologies, like the Internet of Things or solar energy, is not only because it makes for more exciting stories, but because it also has a functional role of drawing attention to up-and-coming areas and encouraging coordinated investment. Perhaps the hype is misplaced; but the role of encouraging coordination is important nevertheless. Finally, the synergies between intangibles can be a valuable competitive tactic for individual companies.

There are any number of firms experimenting with new ways of Internet-enabled collaboration, in fields from healthcare research (such as Patientslikeme or 23andMe) to brokering intellectual property among companies (such as Nathan Myhrvold’s Intellectual Ventures) to data analytics (such as Kaggle, recently acquired by Google). It is easy to laugh when technology advocates make predictions that don’t come to pass. Where is the paperless office? Where is the Internet of Things? But the fact that widespread effective teleworking has not seriously reduced the importance of face-to-face communication may be a sign not that it will never happen, but rather that it is a complicated type of change and takes time. So telecoms infrastructure will matter more in an intangible economy as a way to build connections and make the most of spillovers. But the fiber, routers, processors, and base stations may not be the most important aspect of this infrastructure—what will really make them valuable is the development of new tools and habits of using them to connect and work together.


pages: 413 words: 119,587

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots by John Markoff

"Robert Solow", A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, basic income, Baxter: Rethink Robotics, Bill Duvall, bioinformatics, Brewster Kahle, Burning Man, call centre, cellular automata, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, collective bargaining, computer age, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deskilling, don't be evil, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, factory automation, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, Google Glasses, Google X / Alphabet X, Grace Hopper, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, haute couture, hive mind, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, Mitch Kapor, Mother of all demos, natural language processing, new economy, Norbert Wiener, PageRank, pattern recognition, pre–internet, RAND corporation, Ray Kurzweil, Richard Stallman, Robert Gordon, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, shareholder value, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, skunkworks, Skype, social software, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Nelson, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Turing test, Vannevar Bush, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, William Shockley: the traitorous eight, zero-sum game

Although few people encountered the hulking mainframe computers of the 1950s and 1960s, there was a prevailing sense that these machines exerted some sinister measure of control over their lives. Then in the 1970s personal computing arrived and the computer became something much friendlier—because people could touch these computers, they began to feel that they were now in control. Today, an “Internet of Things” is emerging and computers have once again started to “disappear,” this time blending into everyday objects that have as a result acquired seemingly magical powers—our smoke detectors speak and listen to us. Our phones, music players, and tablets have more computing power than the supercomputers of just a few decades ago. With the arrival of “ubiquitous computing,” we have entered a new age of smart machines.

Every footstep and every utterance is now tracked and collected, if not by Big Brother then by a growing array of commercial “Little Brothers.” The Internet has become an intimate technology that touches every facet of our culture. Today our smartphones, laptops, and desktop computers listen to us, supposedly at our command, and cameras gaze from their screens as well, perhaps benignly. The impending Internet of Things is now introducing unobtrusive, always-on, and supposedly helpful countertop robots, like the Amazon Echo and Cynthia Breazeal’s Jibo, to homes across the country. Will a world that is watched over by what sixties poet Richard Brautigan described as “machines of loving grace” be a free world? Free, that is, in the sense of “freedom of speech,” rather than “free beer.”1 The best way to answer questions about control in a world full of smart machines is by understanding the values of those who are actually building these systems.

The debate took place a decade and a half before Apple unveiled Siri, which successfully added an entirely artificial human element to human-computer interaction. Years later Shneiderman would acknowledge that there were some cases in which using speech and voice recognition might be appropriate. He did, however, remain a staunch critic of the basic idea of software agents, and pointed out that aircraft cockpit designers had for decades tried and failed to use speech recognition to control airplanes. When Siri was introduced in 2010, the “Internet of Things” was approaching the peak in the hype cycle. This had originally been Xerox PARC’s next big idea after personal computing. In the late 1980s PARC computer scientist Mark Weiser had predicted that as microprocessor cost, size, and power collapsed, it would be possible to discreetly integrate computer intelligence into everyday objects. He called this “UbiComp” or ubiquitous computing. Computing would disappear into the woodwork, he argued, just as electric motors, pulleys, and belts are now “invisible.”


pages: 433 words: 127,171

The Grid: The Fraying Wires Between Americans and Our Energy Future by Gretchen Bakke

addicted to oil, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, back-to-the-land, big-box store, Buckminster Fuller, demand response, dematerialisation, distributed generation, energy security, energy transition, full employment, illegal immigration, indoor plumbing, Internet of things, Kickstarter, laissez-faire capitalism, Menlo Park, Negawatt, new economy, off grid, post-oil, profit motive, Ronald Reagan, self-driving car, Silicon Valley, smart grid, smart meter, the built environment, too big to fail, washing machines reduced drudgery, Whole Earth Catalog

Whatever they thought about the SmartGridCity, what made them really angry was the utility’s unwillingness to integrate more wind power. Val, however, has different concerns. She wants her house to manage itself. She wants it to make electricity, store it, and use it without her having to do much more than punch into her smart phone, DISHES WASHED BY 5 P.M. and MAKE SURE THE CAR IS CHARGED BY 7. The coming “Internet of Things,” of which smart phones, smart appliances, smart meters, and electric cars are all integral parts (it is coming, by the way, it just hasn’t quite arrived yet), is in many ways the continuation of an emancipation project that began in the 1930s to free women from the drudgery of household work by electrifying common appliances. The laundry line became the electric clothes dryer, the washboard became the electric washing machine, the icebox became the refrigerator, the kettle on the stove for the weekly bath became the electric hot water heater, the mangle became the electric iron, and so on and so forth.

In short, we’d like our grid to whisper away, to be less devastating in its effects, and to work without deputizing us to the process. We’ll keep electricity, thank you. In fact, the further we proceed into the age of information the more electricity becomes the base for all that we do, from banking, to reading, to collaborative thinking. The future promises an even more thorough integration of electricity into our lives, more data (which is after all, just electricity), more “smart” things (coming to populate the Internet of Things), and the elimination of fuel from cars, necessary if we’d like to stop global warming before it exceeds the 2-degrees-Celsius disaster line. Most important, we’d like this means of “being electric” to come from nothing, to be transmitted by nothing, to cause no damage, and to work always and wherever. This abiding cultural attachment to electricity only makes the unwieldy ways in which we have to move in order to access it all the more salient.

If we are smart enough, it might also be a chance to capture the cutting edge of technological innovation and cultural imagination and concretize it in the grid itself. All the visions of ubiquitous technology, sentient cities, chips everywhere could well take their alpha form in the electric grid. It is, after all, as Nicola Tesla pointed out, not only a system for powering the world but also essential to the lines of communication that weave our economies, our labor, and our imaginations together. If we are going to bring the Internet of Things into our daily lives, then why not start with the biggest thing of all? The grid, tick-bright and aglow with promise. Afterword Contemplating Death in the Afternoon As I write this, the power is out. It’s below freezing outside, though it’s midafternoon on a sunny day in early spring. I have a couple of hours of battery power left in my computer. I was using it for most of the morning without having plugged it in, though there was an outlet less than a cord’s length away.


pages: 360 words: 100,991

Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence by Richard Yonck

3D printing, AI winter, artificial general intelligence, Asperger Syndrome, augmented reality, Berlin Wall, brain emulation, Buckminster Fuller, call centre, cognitive bias, cognitive dissonance, computer age, computer vision, crowdsourcing, Elon Musk, en.wikipedia.org, epigenetics, friendly AI, ghettoisation, industrial robot, Internet of things, invention of writing, Jacques de Vaucanson, job automation, John von Neumann, Kevin Kelly, Law of Accelerating Returns, Loebner Prize, Menlo Park, meta analysis, meta-analysis, Metcalfe’s law, neurotypical, Oculus Rift, old age dependency ratio, pattern recognition, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Skype, social intelligence, software as a service, Stephen Hawking, Steven Pinker, superintelligent machines, technological singularity, telepresence, telepresence robot, The Future of Employment, the scientific method, theory of mind, Turing test, twin studies, undersea cable, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Review, working-age population, zero day

A second ad is quickly sent to her glasses showing her avatar wearing the jacket, along with a thirty-minute flash coupon. The entire interchange has occurred in the space of a few dozen paces. Despite her best efforts, the woman’s expression briefly indicates she’s very interested in the jacket. Moments later, she steps into the store and the transaction is quickly made. ———— The increasing use of sensors in our daily environment, commonly known as the Internet of Things, combined with the predictive power of big data analytics is altering our relationship with the world, not all of it in good ways. Issues of privacy, autonomy, and even self-determination have been raised when discussing these intrusive technologies. As disturbing as all this sounds, it becomes vastly more so when combined with the ability to rapidly read, interpret, and react to our emotional responses.

This will be especially true in the coming decades as we see the development of more and more new affective computing applications and devices. The next twenty to thirty years are going to see a veritable explosion of technologies and capabilities. As computer processing continues to grow in power, even as it shrinks in size, we’ll see more and more aspects of our world acquire new ways of interacting with us through digital means. Sensors in the environment, smart appliances, programmable matter—the world of the Internet of Things, or IoT, is becoming a reality, and as it does it will totally change the way we interact with our world and with each other. Similarly and closely interlinked, big data (the accumulation of vast data sets from which patterns and insights can be mined using powerful computing, sophisticated analytics tools, and visualization methods) is becoming increasingly prevalent. Combined with artificial emotionally intelligent machines, big data could provide highly accurate profiles of user psychology and anticipated behaviors.

Safeguards can of course be built, and of course these will be circumvented. Where do the liabilities and responsibility lie? It’s a question that will no doubt keep ethicists, lawyers, and legal analysts arguing for a very long time. This is the emotionally connected world we might expect to find ourselves in twenty or thirty years from now. Sensors scattered throughout the urban and natural environment, in what has come to be called the Internet of Things, will be able to readily and accurately detect our emotional states at every turn. Depending on the choices we make about the access we give to our emotional lives, we may find ourselves dealing with all kinds of strange and challenging situations. It may sound odd to contemplate, but that’s often the case when viewing the future from a vantage point of the past. For instance, many people of the mid-twentieth century would find our current attitudes about sharing our personal lives via social media unfathomable.


pages: 372 words: 101,678

Lessons from the Titans: What Companies in the New Economy Can Learn from the Great Industrial Giants to Drive Sustainable Success by Scott Davis, Carter Copeland, Rob Wertheimer

3D printing, activist fund / activist shareholder / activist investor, additive manufacturing, Airbnb, airport security, barriers to entry, business cycle, business process, clean water, commoditize, coronavirus, corporate governance, COVID-19, Covid-19, disruptive innovation, Elon Musk, factory automation, global pandemic, hydraulic fracturing, Internet of things, iterative process, low cost airline, low cost carrier, Marc Andreessen, megacity, Network effects, new economy, Ponzi scheme, profit maximization, random walk, RFID, ride hailing / ride sharing, risk tolerance, shareholder value, Silicon Valley, six sigma, skunkworks, software is eating the world, strikebreaker, Toyota Production System, Uber for X, winner-take-all economy

The turnaround was multidimensional and required time and patience: fix the factories, seed a culture of continuous improvement, creatively address a portfolio that was stale and well past its expiration date, aggressively manage liabilities, and play offense by rolling out cost-advantaged new products. Honeywell pivoted and reenergized around big themes: energy efficiency, productivity, and connectivity—more popularly known as the industrial internet of things (IIoT), with the high-margin software businesses that have accompanied the strategy. Today, it has become the envy of much of the industrial world. The modern Honeywell story began on February 19, 2002, the start date of an unlikely corporate savior: CEO Dave Cote (pronounced “Cody”). He led a turnaround against tremendous odds—a broken company trying to survive an economic downturn with an unproven, unconventional CEO.

The Cote turnaround was complete, and stakeholders rode a steady, predictable, and impressive company upward. POSTMORTEM Cote’s final act at Honeywell, on the eve of his retirement in 2017, was to convince the board to promote Darius Adamczyk as his successor. Rather than a Cote clone, Adamczyk is a far different breed. Where Cote had less interest in (or time for) advanced technology, the kind usually reserved for West Coast high-flyers, the new CEO has invested heavily in the industrial internet of things. It’s an important pivot for the company. Adamczyk’s vision of software, digital connectivity, and emerging technologies like quantum computing is edgier than that of his predecessor, but it’s better suited to Honeywell’s strong current position. The company can afford to play offense now. That’s how a company sustains growth over time: Combine a clear vision with systems to keep people focused on delivering value every day.

SBD is also working to bring advanced manufacturing into its factories, thereby lowering costs, localizing production, and accelerating product development. The industrial world has an ongoing movement called Industry 4.0, which aims to bring manufacturing into the digital age. There are 30 or so advanced technologies in that broad concept, and SBD is aggressively pursuing several. The first phase is deploying the industrial internet of things at scale. There’s been lots of talk around IIOT for the past few years, and it’s not always clear what it means or who benefits. Put simply, added sensors and technology on production lines bring an increase in visibility and the ability to respond to changes in volume or what’s being made. On top of that, SBD is deploying industrial apps built internally and leveraging what’s been built by others.


pages: 245 words: 64,288

Robots Will Steal Your Job, But That's OK: How to Survive the Economic Collapse and Be Happy by Pistono, Federico

3D printing, Albert Einstein, autonomous vehicles, bioinformatics, Buckminster Fuller, cloud computing, computer vision, correlation does not imply causation, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Firefox, future of work, George Santayana, global village, Google Chrome, happiness index / gross national happiness, hedonic treadmill, illegal immigration, income inequality, information retrieval, Internet of things, invention of the printing press, jimmy wales, job automation, John Markoff, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, labor-force participation, Lao Tzu, Law of Accelerating Returns, life extension, Loebner Prize, longitudinal study, means of production, Narrative Science, natural language processing, new economy, Occupy movement, patent troll, pattern recognition, peak oil, post scarcity, QR code, race to the bottom, Ray Kurzweil, recommendation engine, RFID, Rodney Brooks, selection bias, self-driving car, slashdot, smart cities, software as a service, software is eating the world, speech recognition, Steven Pinker, strong AI, technological singularity, Turing test, Vernor Vinge, women in the workforce

http://yro.slashdot.org/story/12/04/27/0029256/will-ibm-watson-be-your-next-mayor 89 Computers to Acquire Control of the Physical World, P. Magrassi, A. Panarella, N. Deighton, G. Johnson, 2001. Gartner research report. T-14-0301. 90 A World of Smart Objects, P. Magrassi, T. Berg, 2002. Gartner research report. R-17-2243. http://www.gartner.com/DisplayDocument?id=366151 91 The Internet of Things. Wikipedia. http://en.wikipedia.org/wiki/Internet_of_Things 92 Study: Intelligent Cars Could Boost Highway Capacity by 273%, 2012. Institute of Electrical and Electronics Engineers. http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/intelligent-cars-could-boost-highway-capacity-by-273 93 INTERNET USAGE STATISTICS. The Internet Big Picture. World Internet Users and Population Stats. http://www.internetworldstats.com/stats.htm 94 Freedom on the Net 2011 – A Global Assessment of Internet and Digital Media Freedom, 2011.

IBM and Nuance Communications Inc. are partnering for the research project to develop a commercial product during the next 18 to 24 months that will exploit Watson’s capabilities as a clinical decision support system to aid the diagnosis and treatment of patients.86 Recall the example of automated radiologists we mentioned earlier. Watson could be fully capable of performing this task if there was ever the intention of doing so, and even then we would be using only a tiny fraction of its immense power. This is just the beginning. Watson-like technologies could be used for virtually anything: legal advice, city planning (IBM and Cisco are already working on smart cities),87 and why not policy-making?88 The Internet of Things is coming, and we had better be ready. Technology is becoming so cheap and so powerful it will be integrated into everyday objects, which will help us make better decisions. With all objects in the world equipped with minuscule identifying devices, daily life on Earth would undergo a transformation.89 Companies would not run out of stock or waste products, as involved parties would know which products are required and consumed.90 Mislaid and stolen items would be easily tracked and located, as would the people who use them.


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American Legislative Exchange Council, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, commoditize, creative destruction, crony capitalism, crowdsourcing, data is the new oil, David Brooks, David Graeber, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, future of journalism, future of work, George Akerlof, George Gilder, Google bus, Hacker Ethic, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, life extension, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Mother of all demos, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, pre–internet, Ray Kurzweil, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Ross Ulbricht, Sam Altman, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, smart grid, Snapchat, software is eating the world, Steve Jobs, Stewart Brand, technoutopianism, The Chicago School, The Market for Lemons, The Rise and Fall of American Growth, Tim Cook: Apple, trade route, transfer pricing, Travis Kalanick, trickle-down economics, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator

In reality, hacking just means building something quickly or testing the boundaries of what can be done.” This emphasis on speed and subversion is embraced by much of the technology community. The problem, of course, especially as we move to the Internet of Things—the 6.4 billion Internet-connected sensors and devices—is that security is often an afterthought in building the latest shiny new object of our desire. In a preview of our future, the massive Internet outages experienced in October of 2016 were triggered by (possibly Russian) hackers using the unsecured Internet of Things. As the New York Times reported, “in a troubling development, the attack appears to have relied on hundreds of thousands of internet-connected devices like cameras, baby monitors and home routers that have been infected—without their owners’ knowledge—with software that allows hackers to command them to flood a target with overwhelming traffic.”

As the New York Times reported, “in a troubling development, the attack appears to have relied on hundreds of thousands of internet-connected devices like cameras, baby monitors and home routers that have been infected—without their owners’ knowledge—with software that allows hackers to command them to flood a target with overwhelming traffic.” As the Sun Microsystems CEO, Scott McNealy, said more than fifteen years ago, “You have zero privacy anyway. Get over it.” Beyond the feelings of paranoia brought on by Russian hackers, the Internet of Things will bring new privacy and security worries. In 2015 more than 40 percent of the thermostats sold in the United States will be “smart thermostats,” many of them sold by Google’s subsidiary Nest. Most buyers of a Nest device don’t realize it’s capable of more than just lowering the temperature when you leave the house. The Nest is just the next step in Google’s data collection efforts. When the Pew Research Center asked Americans about their privacy concerns, they found “a scenario involving the use of a ‘smart thermostat’ in people’s homes that might save energy costs in return for insight about people’s comings and goings was deemed ‘acceptable’ by only 27% of adults, while 55% saw it as ‘not acceptable.’”


Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport

Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, commoditize, data acquisition, disruptive innovation, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, lifelogging, Mark Zuckerberg, move fast and break things, move fast and break things, Narrative Science, natural language processing, Netflix Prize, New Journalism, recommendation engine, RFID, self-driving car, sentiment analysis, Silicon Valley, smart grid, smart meter, social graph, sorting algorithm, statistical model, Tesla Model S, text mining, Thomas Davenport

I don’t know if all of these data forms will remain; the normal pattern is for the functions performed by these tools to be incorporated into broader applications. The data generated by them and the insights they reveal about their authors, however, are not going away. In general, however, sensor data is here to stay. The number of networked devices overtook the global population of humans in 2011. ­Analysts estimate that fifty billion sensors will be connected to the ­internet by 2025 (“the Internet of Things”), and each one can ­produce a passel of data. While early prognostications suggested that internet-connected sensors would primarily be used in consumer ­ devices, there has been only limited progress in that regard. Our ­refrigerators may not be connected to the internet anytime soon (if they were, they could, for example, automatically order fresh milk to be delivered when we run low), but our TVs, security systems, and thermostats are increasingly networked.

HunchWorks is also described as “a mechanism to make the membranes between silos of knowledge both inside and outside of the UN more permeable.” An important aspect of big data is that it is Chapter_01.indd 20 03/12/13 3:24 AM Why Big Data Is Important to You and Your Organization   21 often external to the organization using it. Whether one is addressing internet data, human genome data, social media data, the Internet of Things, or some other source, chances are good that it doesn’t come from your company’s internal transaction systems. The exceptions to this pattern—which I’ll describe in chapter 2—are most likely to be in the telecommunications and financial services industries, which are blessed with massive amounts of internally generated data to analyze. Even there, however, internal data can often be profitably supplemented with external data.

See also Apache Impala industrial products and services, 13, 16, 25–26, 65, 75, 185, 197 industrial products firms, 42t, 43, 47, 83 informatics, 66, 156 information technology impact of big data on, 55–56 See also architecture; technology; and specific processes and products 03/12/13 2:04 PM Index  223 Ingenix, 155–156 in-memory analytics, 114t, 116, 124, 199 innovation, focus on, 147 Insight Data Science Fellows Program, 104 insurance industry, 34, 42, 42t, 67, 77, 137, 142, 162, 202 integration, 126–128, 127f, 199–200 Intel, 47 Intel Hadoop, 115 intellectual property (IP), 161 Intermountain Healthcare, 156. See also Home Warner Center for Informatics Research International Institute for Analytics, 135 Internet of Things, 11, 21 internship programs, 103 Intuit, 141–142 iPod, 12 J.R. Simplot, 11 Java language, 89, 123 Jimenez, Joe, 66 job growth for data scientists, 111, 111f, 184–185 John Deere, 47 Johnson & Johnson, 54 Kaplan Inc., 16, 41, 66 Karu, Zoher, 143 Keeping Up with the Quants (Davenport and Kim), 93 Klamka, Jake, 104 Kyruus, 161, 162, 168 large companies action plan for Analytics 3.0 for ­managers in, 204 automating existing processes in, 190–193 big data objectives in, 178–180 big data’s value proposition in, 187 big data used in, 175–176 chief analytics officer role in, 202 company case studies in, 178, 181, 183, 186–187, 187–188, 192, 196, 198 data scientists and teams in, 201 historical context for analytics and big data in, 194–197 Index.indd 223 integrated and embedded models in, 199–200 hybrid technology models in, 200–201 integrating organizational structures and skills in, 182–185 managers’ views of big data in, 176–177 multiple data types in, 197–199 prescriptive analytics used in, 202–203 return on investment in, 188–189, 190f speed of technologies and methods in, 199 leadership, 139–143, 151 Library of Congress, 1 life-cycle management, 129 LinkedIn, 16, 65, 82, 83, 92, 104, 127, 146, 148, 153, 155, 157, 158–159, 160–161, 164, 165 People You May Know (PYMK) ­feature of, 23–24, 140–141, 148, 158 Lockheed Martin, 78 Louisiana State University, 102 machine learning, 4t, 29, 88, 96, 102, 110–111, 113, 114t, 118, 124, 183, 199 Macy’s, 63–64, 179, 183 Macys.com, 63, 182, 183 management big data technology perspective of, 15–18 big data usage and changes in, 27–28 leadership in big data initiatives and, 139–143, 151 new roles in, 141–143 managers action plans for, 30, 57, 84, 112, 134, 151–152, 173, 204 big data skills for, 106–110 in large companies, 176–177 retraining of, 112 visual analytics and, 109 manufacturing, 8t, 52–53, 56, 77, 193, 197 MapReduce framework, 29, 89, 114t, 116, 122, 123, 127f, 132, 148, 157, 199 marketing automated narrative for, 126 banking and, 44, 49, 55, 109 big data strategy and, 5, 8t, 66, 69, 71, 193 B2B firms and, 45–46 Caesars Entertainment and, 179 03/12/13 2:04 PM 224 Index marketing (continued) data-based products and services for, 75, 79, 92, 163, 171, 182 LinkedIn’s use of, 158–159 managerial roles for, 141–142 organizational structure and, 15, 18 retail and, 37–38, 63, 71, 183, 192 sources of data for, 50–51 targeting offers to, 27, 55, 63–64, 65, 67, 72, 79, 107, 108–109, 128, 142, 144, 179, 180, 197 Massachusetts Institute of Technology (MIT), 102, 142, 202, 206 massively parallel processing (MPP), 189, 195, 208 Matters Corp, 69 Mayer, Marissa, 166 Mayo Clinic, 181 McAfee, Andy, 27, 206 McGraw-Hill, 143 McKinsey, 185 media and entertainment firms, 5, 42, 44, 48–49, 54, 179–180 medical record systems, 9, 43, 44–45, 72, 121–122, 156, 181 MetaScale, 192 Me-trics, 13 Microsoft, 14, 37, 163 Microsoft Hadoop, 115 Microsoft Windows Azure, 163.


pages: 281 words: 69,107

Belt and Road: A Chinese World Order by Bruno Maçães

active measures, Admiral Zheng, autonomous vehicles, Branko Milanovic, BRICs, cloud computing, deindustrialization, demographic dividend, Deng Xiaoping, different worldview, Donald Trump, energy security, European colonialism, eurozone crisis, Francis Fukuyama: the end of history, global supply chain, global value chain, industrial cluster, industrial robot, Internet of things, Kenneth Rogoff, land reform, liberal world order, Malacca Straits, one-China policy, Pearl River Delta, smart cities, South China Sea, sovereign wealth fund, special economic zone, trade liberalization, trade route, zero-sum game

“We both agree that Chinese companies should be united and must not be provoked by outsiders,” he added, before speaking about his company’s efforts over the past thirty years and expressing zero tolerance for any questioning of the loyalty of the “national brand.” The dispute highlights how much national champions are expected to benefit from the definition of which technologies will be used to power the coming revolution in autonomous cars and the internet of things. * * * Because Germany’s top firms have become so dependent on the Chinese market, the government in Berlin has avoided confronting China head-on.16 The United States took longer to react, but when it finally did the response was considerably more aggressive. The ongoing dispute was initially centered around the country’s trade deficit with China but quickly turned to Made in China 2025.

And since one of the most immediate and ineluctable results of a tariffs war is a decline in China’s exports and foreign exchange income, an initiative as ambitious as the Belt and Road will become increasingly hard to finance.18 * * * No doubt China could have access to commodities extracted in developing countries or the technology from developed nations without the Belt and Road, but the process would be subject to the normal operation of market mechanisms. What the Belt and Road does is increase China’s control over the way value chains are organized and grant it the power to reorganize them on better terms. To give the most obvious example, the Chinese economy still has to rely on a steady supply of foreign-made semiconductors, the heartbeat of the internet of things and the industrial factories of the future, a fragility made evident when the giant electronics company ZTE was taken to the brink of extinction after the Trump administration temporarily banned it from buying US-made components such as chips. In a speech two years earlier, Xi Jinping had berated China’s dependence on foreign suppliers for critical components and key technologies. The concept of power is central to the global value chain approach.

INDEX Abbasi, Zafar Mahmood, 126 Abe, Shinzo, 118, 137 Addis Ababa, Ethiopia, 68 Aden Gulf, 72 Adil, Umer, 60 Advancing the Development of the One Belt, One Road Leading Group, 39 aerospace, 88, 103 Afghanistan, 53, 107, 127, 128, 129, 135, 172 Africa, 3, 8, 25, 44, 124, 163 Djibouti, 4, 12, 46, 63, 67–8, 101, 117 Ethiopia, 46, 68, 154, 170, 186 manufacturing, 68, 77 Maritime Silk Road, 23, 26, 45, 62 oil, 64 Partnership for Quality Infrastructure, 138 piracy, 72 telecommunications, 101, 170–71 aging population, 75 Agricultural Bank of China, 48 agriculture, 11, 61, 76, 99–100, 103 Ahmedabad, Gujarat, 138 aircraft, 81, 91, 103 Akto, Xinjiang, 60 Aktogay, East Kazakhstan, 103 Alibaba, 44 Allison, Graham, 7–8 Alps, 189 aluminum, 17, 20, 88 Andalusia, Spain, 189 Andijan, Uzbekistan, 54 anti-dumping, 92, 113 Antwerp, Flanders, 65 Apollo program, 9 aquaculture, 71 Arabian Sea, 72, 106 Arctic, 4, 62, 66, 188 artificial intelligence (AI), 44, 75, 88 Arunachal Pradesh, India, 111 Asian Development Bank, 45, 137 Asian Financial Forum, 49 Asian Infrastructure Investment Bank, 48 Association of Southeast Asian Nations (ASEAN), 122 Astana International Exchange, 56 Astana, Kazakhstan, 25–6, 39, 56, 58 asteroids, 187 Athens, 8 Atlantic Ocean, 3, 115, 119, 138, 139 Atushi, Xinjiang, 60 Australia, 5, 12, 25, 119, 121, 122, 132–3, 135 automated vehicles, 88, 90, 186, 187, 190 automobile industry, 74, 81, 86, 90–91, 97, 104 Autor, David, 177 aviation, 81, 91, 103 Azad Jammu and Kashmir (AJK), 60 Azerbaijan, 186 Badakhshan, Afghanistan, 128 Baidu, 188 Baldwin, Richard, 74, 80 Balkans, 8, 12, 140 Balochistan, Pakistan, 60, 105 Gwadar port, 46, 59, 61–2, 63, 64, 99–100, 101, 105–7, 117 separatism and terrorism, 106, 127, 128 Baltic Sea, 51 Bangkok, Thailand, 65, 136–7 Bangladesh, 48, 53, 64, 109, 134, 136, 138, 150, 189 Bangladesh-China-India-Myanmar Economic Corridor (BCIM-EC), 52, 62 Bank of China, 48 banking, 46–51 bargaining theory, 152–3 Bay of Bengal, 22, 64, 72, 119 Beijing, China, 20, 28, 48, 126, 165 Beijing University, 183, 188 Belgium, 56, 65 Belgrade, Serbia, 143 Belt, see Silk Road Economic Belt Belt and Road Advancing the Development of the One Belt, One Road Leading Group, 39 backlash against, 12, 108, 121–4, 130–46, 155 bridges, 40, 54, 156, 173, 186 Buddhism, 112 cities, 11, 43, 44, 48, 149–52, 187–8 ‘community of shared destiny’, 26–9, 33, 36, 43, 45, 170 connectivity (wu tong), 42, 43, 52–3, 127, 158, 167 currency integration, 26 data, 44 debt, 12, 46, 47, 108, 109, 124, 126, 130, 132, 153–62 digital infrastructure, 43–4, 59, 86 e-commerce, 44, 59 economic corridors, 2, 11, 51–4, 55, 62 economic policy coordination, 28 energy, 11, 17, 19, 20–23, 40, 46, 48, 49, 52, 61, 64, 86, 92, 188 financing, 11, 36, 46–51, 54, 108–9, 124, 126, 130, 132, 138, 141, 153–64 Forum for International Cooperation (2017), 12, 108, 143, 152 impatience, 152–3 inauguration (2013), 11, 17, 23 industrial capacity cooperation, 85–8 industrial parks, 10, 43, 55, 61, 67, 99, 102 infrastructure, see infrastructure internal discontent, 163 international court, 28, 190 loans, 11, 36, 46–7, 54, 108–9, 124, 126, 130, 132, 138, 141, 153–62, 163 maps, 2–6, 24, 41, 64, 69 Maritime Silk Road, 24, 26, 28, 39, 41 market integration, 41 military bases, 12, 67, 71, 72, 101, 117, 126–7 overcapacity, 19 ports, see ports railways, 9–10, 11, 12, 18, 43, 46, 52, 53–4, 68, 86, 122, 130 roads, 9, 19, 40, 43, 52, 54 security, 127–9 Silk Road, 2, 9–10, 23–6, 45, 82, 138 Silk Road Economic Belt, 24, 25–6, 28, 39, 51–62, 83 success, definition of, 164, 174 telecommunications, 43–4, 52, 86, 101, 170–71 timeline, 10 TIR Convention, 55 transnational industrial policy, 81, 84 transport infrastructure, 9–10, 11, 18, 19, 25, 26, 40, 48, 49, 53–4, 83 urban development, 11, 43, 44, 48, 149–52 Vision and Actions document (2015), 40, 41, 45, 49, 50, 52, 62, 67, 78 Vision for Maritime Cooperation (2017), 62 Bering Strait, 66 Bharatiya Janata Party (BJP), 110 Bhat, Vinayak, 107 Bhutan, 107–8 big data, 44 Bishkek, Kyrgyzstan, 127 Blackwater, 128 blue economic passage, 62 Boao Forum for Asia (2015), 27, 32 Brahmaputra river, 136 Brazil, 174 Brewster, David, 63 BRIC (Brazil, Russia, India and China), 19, 174 bridges, 40, 54, 156, 173, 186 British Broadcasting Corporation (BBC), 188 Budapest, Hungary, 143 Buddhism, 111–12 Bush, George Walker, 169 California, United States, 64 Cambodia, 52, 54, 70, 129, 132, 155 Cameroon, 68, 187 Canada, 136 car industry, see automobile industry Caribbean, 25 Carr, Robert ‘Bob’, 122 Cartagena, Spain, 92 Caspian Sea, 186 Caucasus, 20, 129 CDMA (code-division multiple access), 89 cement, 17, 49–50, 83 Center for Strategic and International Studies, 19, 123 center of gravity, 115 Central African Republic, 186 Central Asia, 9, 20, 25, 51, 52, 82–3, 188 energy, 22, 106 Eurasian Economic Union (EEU), 57–9 India, trade with, 107 industrial capacity cooperation, 104 Islamism, 127 Russia, relations with, 57–9, 129, 133 steel industry, 82–3 terrorism, 127 textile industry, 101 transport infrastructure, 9, 54 Central Huijin Investment, 49, 50 Central Military Commission, 166 century of humiliation (1839–1949), 165, 186 Chabahar, Sistan-Baluchistan, 106–7 Chalay Thay Saath, 60 Chao Phraya River, 65 ChemChina, 48 Chengdu Economic Daily, 129 China Abbasi’s visit (2018), 126 Academy of Information and Communications Technology, 44 aging population, 75 Banking and Insurance Regulatory Commission, 50 Bishkek Embassy bombing (2016), 127 Boao Forum for Asia (2015), 27, 32 Buddhism, 111–12 century of humiliation (1839–1949), 165, 186 Doklam plateau dispute, 107–8, 113 energy, see energy EU-China summit (2015), 138 five-year plan (2016–20), 41 Food and Drug Administration, 114 Foreign Policy Center of the Central Party School, 7 Gants Mod crossing closure (2016), 36 General Navigation Office, 69 ‘Going Out’ strategy, 86 Guangxi Nonferrous Metals Group bankruptcy (2016), 16 Guiding Opinion on Promoting International Industrial Capacity (2015), 86 Guiding Opinion on Standardizing the Direction of Overseas Investment (2017), 86 incremental approach, 7 Indian Dilemma, 21 Institute of International Studies, 92 International Trust and Investment Corporation, 132 Investment Corporation, 48 keeping a low profile (tao guang yang hui), 15, 18, 32 labour shortages, 75 Macron’s visit (2018), 146–7 Made in China 2025 strategy, 85, 87, 90–92, 93 Malacca Dilemma, 21–2, 64, 131 Merchants, 68–9 middle-income trap, 75–7, 85 migrant workers, 75 military, 12, 13, 59, 67, 71, 72, 101, 117, 126–7 minimum wage, 75 Ministry of Commerce, 21, 40, 93 Ministry of Communications, 69 Ministry of Finance, 49 Ministry of Foreign Affairs, 40 Ministry of Industry and Information Technology, 19 Ministry of Transportation, 14 Modi–Xi summit (2018), 135 National Bureau of Statistics, 75 National Congress, 28, 29, 44, 165, 181 National Cybersecurity Work Conference (2018), 84 National Development and Reform Commission, 40, 98 National Health Commission, 114 Opium War, First (1839–1842), 165 overcapacity, 16, 19–20, 88 Overseas Chinese Affairs Office, 19 Overseas Investment Industrial Guiding Policy, 86 People’s Navigation Company, 69 Ports-Park-City model, 67 presidential term limits repeal (2018), 164, 174 real estate market, 16, 75 reform and opening up, 13–15, 73 renminbi, 22–3, 159 responsible stakeholder, 169 shipbuilding, 14, 17 soft power, 111, 170 Soviet Union, relations with, 13, 14, 15 State Administration of Foreign Exchange, 48 State Council, 19, 39, 40, 49, 66, 86 state-owned companies, 42, 153, 160–61, 189 steel industry, 16–17, 18, 20, 82–4, 86, 88 striving for achievement, 18 Swaraj’s visit (2018), 135 Taiwan, relations with, 14, 26, 142 technology transfers, 85–92, 97, 177–8 Thucydides’ trap, 8 Tianxia, 26–7, 29, 31–5, 78, 79, 192–3 TIR Convention, 55 Trump’s visit (2017), 124 ‘two heads abroad’ (liangtou zai haiwai), 17 United States, relations with, see Sino–US relations Working Conference on Neighborhood Policy (2013), 17–18 China Construction Bank, 48 China Development Bank, 16, 48, 49, 97, 98, 99, 103, 160 China Export & Credit Insurance Corp, 104 China Export-Import Bank, 46, 47, 48, 49, 103, 154 China Fantasy, The (Mann), 177 China Global Television Network, 188 China Nonferrous Metals Industry Group, 103 China Three Gorges Corp, 48 China-Indian Ocean-Africa-Mediterranean Sea Blue Economic Passage, 62 China-Indochina Peninsula Economic Corridor, 51, 52, 54, 62 China-Oceania-South Pacific, 62 China-Pakistan Economic Corridor (CPEC), 52, 59, 60, 62, 105–7, 108 Chinese Communist Party Advancing the Development of the One Belt, One Road Leading Group, 39 and Australia, 133 Constitution, 41, 164 founding of (1921), 165 National Congress, 18th (2012), 28 National Congress, 19th (2017), 29, 44, 165, 181 and New Zealand, 132 Politburo, 39, 40, 165 reform and opening up, 13–15 and steel industry, 16 Third Plenum of the 18th Party Central Committee (2013), 39 Chongyang Institute for Financial Studies, 106 Christianity, 128 Churchill, Winston, 183 cities, 11, 43, 44, 48, 149–52, 187–8 climate change, 4, 66, 85, 171 Clinton, William ‘Bill’, 177 cloud computing, 44 CloudWalk Technology, 44 Club Med, 189 CNN, 188 cobalt, 81, 104 Cold War, 2, 14, 21–2, 36, 40, 125, 171 Colombo, Sri Lanka, 156, 162 colonialism, 120, 162 ‘community of shared destiny’, 26–9, 33, 36, 43, 45, 135, 170 Confucianism, 31, 34 Congo, Democratic Republic of, 81, 104 connectivity, 42, 43, 52–3, 109, 122, 127, 146, 158, 167 Connectivity Platform, 139 construction, 18, 75, 86, 98 convergence, 4, 14, 166, 167, 169, 174, 177 copper, 103, 104 corridors, see economic corridors corruption, 133, 155–6, 158, 187 cosmopolitan neighborhoods, 4 Country Garden, 151 Cowboys and Indians, 188 cultural exchanges, 42, 43, 56–7 currency, 22–3, 26, 159–60 customs cooperation, 55, 57, 59, 63 Cyprus, 140 Dalai Lama, 36, 112 Dalian, Liaoning, 55, 93 Daming Palace, Xi’an, 147 Dangal, 111 data, 44 Davidson, Phillip, 125–6 Davos, Switzerland, 168 Dawn of Eurasia, The (Maçães), 185, 191 Dawood, Abdul Razak, 158 debt, 12, 16, 46, 47, 108, 109, 124, 126, 130, 132, 153–62 democracy, 125, 133, 166, 171, 172, 174, 175, 176, 181–3 Democratic Republic of Congo, 81, 104 Deng Xiaoping, 13–15, 18, 31, 32, 69, 73, 183 Diaoyu Islands, 187 digital infrastructure, 43–4 division of labor, 53, 78, 79, 80 Djibouti, 4, 12, 46, 63, 67–8, 101, 117, 186 Doklam plateau, 107–8, 113 Doraleh, Djibouti, 63, 67–8 DP World, 68 dry ports, 57 Dubai, UAE, 62, 68, 160 Dudher Zinc project, 127 Duterte, Rodrigo, 156 DVD (digital versatile disc), 89 e-commerce, 44, 59 East China Sea, 118 economic corridors, 2, 11, 51–4, 55 economic nationalism, 102 economic policy coordination, 28 Economist, The, 190 Egypt, 101 electric cars, 81, 104 electricity, 40, 46, 49, 52, 61, 98, 156, 188 end of history, 36 energy, 4, 11, 17, 19, 20–23, 48, 49, 82, 86, 92, 188 electricity, 40, 46, 49, 52, 61, 98, 156, 188 gas, 21, 22, 40, 52, 64, 72, 106 hydropower, 48 oil, 21, 22, 23, 40, 52, 64, 72, 106 renewable, 21, 187, 188 English language, 111, 188 Enhanced Mobile Broadband coding scheme, 89 Enlightenment, 193 environmental sustainability, 75 Erenhot, Inner Mongolia, 55 Ethiopia, 46, 68, 154, 170, 186 Eurasia, 1–5, 11, 20, 26, 45, 52, 57, 63, 120, 121, 138 Eurasian Economic Union (EEU), 57–9 Eurasian Resources Group, 103 European Commission, 143, 145 European empires, 120–21 European Union (EU), 5, 29, 57, 58, 138–47, 159, 176, 179 and Belt and Road, 10, 12, 30, 138–47 Connecting Europe and Asia strategy (2018), 145–6 and Djibouti, 67 economic policy coordination, 28 5G mobile networks, 43 immigration, 187 steel industry, 17 tariffs, 83 technology transfers, 87–8, 178 transnational framework, 81 Turkey, relations with, 4 Export-Import Bank of China, 46, 47, 48, 49, 103, 154 exports, 15, 17, 19, 79 Facebook, 188 facial recognition, 44, 190 fashion industry, 101 fate, 34 Fergana Valley, 54 fertilizers, 19 fibre-optic connectivity, 101 fifth generation (5G) mobile networks, 43–4, 89 finance, 11, 36, 46–51, 54, 126, 138, 141, 153–64 Financial Times, 10, 63, 143, 154, 157, 158, 159 five-year plan (2016–20), 41 Folding Beijing (Hao), 150 food imports, 76 foreign direct investment, 46, 144–6 foreign exchange, 16, 94, 153 Forest City, Johor, 149–51, 155 France, 11, 96, 129, 141, 144, 146–7, 189 free and open order, 125 free-trade zones, 11, 42, 55–6, 71 freedoms of speech, 172, 189 French Foreign Legion, 129 French, Howard, 13 Frontier Services Group, 128–9 Fu Chen, 129 Fu Ying, 140 Fukuyama, Francis, 184–5 Gabon, 96 Gabriel, Sigmar, 142 Gang of Four, 14 Gants Mod crossing closure (2016), 36 gas, 21, 22, 40, 52, 64, 72, 106 General Navigation Office, 69 generic drugs, 114 Genghis Khan, 2, 25 Georgia, 58 Germany, 11, 65, 80, 87–8, 90, 100, 141–2, 144, 189 ghost ships, 186 Gibraltar, 92 Gilgit-Baltistan, Pakistan, 54, 60, 108 Gland Pharma, 113 glass, 17, 83 Global Energy Interconnection, 188 global financial crisis (2008), 16–17, 85, 161, 178 Global Infrastructure Center, 190 Global Times, 67, 109, 131 global value chain revolution, 74 global warming, 4, 66, 85 globalization, 19, 28, 66, 78, 102, 124, 144, 168, 174, 192 ‘Going Out’ strategy, 86 good governance, 183–4 Google, 152, 188 Goubet, Djibouti, 67 government procurement, 12, 59 Grand Palace, Bangkok, 65 Grand Trunk Road, 53 Greece, 30, 31, 65, 140, 141, 142 GSM (Global System for Mobile communications), 89 Guangdong, China, 28, 75, 151 Guangxi Beibu Gulf International Port Group, 67 Guangxi Nonferrous Metals Group, 16 Guiding Opinion on Promoting International Industrial Capacity (2015), 86 Guiding Opinion on Standardizing the Direction of Overseas Investment (2017), 86 Guo Chu, 33 Gwadar, Balochistan, 46, 59, 61–2, 63, 64, 99–100, 101, 105–7, 117 Hainan, China, 71 Hambantota, Sri Lanka, 46–7, 63, 64, 68, 117, 162 Hamburg, Germany, 65 Hamilton, Clive, 133 Han Empire (206 BC–220 AD), 25 Hao Jingfang, 150 ‘harmonious world’, 33, 36 Havelian, Khyber Pakhtunkhwa, 54 He Yafei, 19, 168 heavy industry, 75, 82 Hebei, China, 83 Heilongjiang, China, 55 Hesteel, 83 high-speed railways, 18, 53–4, 83, 89, 98, 122, 130, 137, 138, 143, 186–7 highways, see roads Hillman, Jonathan, 8 Hobbes, Thomas, 27 Holslag, Jonathan, 189 Hong Kong, 49, 103 Hongshi Holding Group, 49 Horgos, Xinjiang, 55, 55–6, 57 Horn of Africa, 3 Hu Huaibang, 49, 97 Hu Jintao, 21, 33, 70 Hu Xiaolian, 154 Huang Libin, 19 Huangyan Island, 187 Huawei, 89–90, 101, 171 Hub, Balochistan, 127 hukou (household registration), 76 human rights, 141–2, 170, 171, 189 Hun Sen, 155 Hungary, 30, 140, 141, 142, 143, 144 Huntington, Samuel, 184 Hussain, Chaudhry Fawad, 157 hydropower, 48 Ibrahim Ismail, Sultan of Johor, 151 immigration, 187 impatience, 152–3 imports, 17, 19, 22, 79–84 India and the Indian Ocean (Panikkar), 118 India, 3, 5, 64, 105–25, 134–6, 174, 179 Bangladesh Liberation War (1971), 109 and Belt and Road, 11, 12, 52, 72, 105–15, 130, 133 Belt and Road Forum for International Cooperation (2017), 12, 108 British Raj (1858–1947), 107 Buddhism, 111–12 cosmopolitan neighborhoods, 4 cultural mission to China (1952), 113 Doklam plateau dispute, 107–8, 113 economic autarchy, 110, 117 free and open order, 125 Grand Trunk Road, 53 imports, 113–14 and Indian Ocean, 3, 116–19 Indo-Pacific, 116–23, 125 Japan, relations with, 118 Kashmir dispute, 108–9, 117 Malabar naval exercises (2018), 135 and maritime hegemony, 72 migrant workers, 150 military bases, 3, 131 Modi–Xi summit (2018), 135 Mumbai-Ahmedabad high-speed railway, 138 nuclear tests (1998), 109 Pakistan, relations with, 105–7, 108–9, 117, 134 pharmaceuticals, 113, 114 Quadrilateral Security Dialogue, 121–2 Research and Analysis Wing (R&AW), 105–6 and Sabang Island, 131 Siliguri Corridor, 107–8 Southeast Asia, 113, 117–18 Swaraj’s visit to China (2018), 135 Tibet, relations with, 111–12, 117, 136 United States, relations with, 119, 121–2, 134, 135 Indian Dilemma, 21 Indian Ocean, 3, 8, 9, 26, 51, 62, 63, 66, 68, 71–2, 116–19 Indo-Pacific, 116–23, 125, 126 and Japan, 4 Kra Isthmus canal proposal, 65, 186 meticulous selection, 72 Myanmar oil and gas pipeline, 64, 72 oil, 21, 64 and Pakistan, 59, 61, 64 individualism, 27, 189 Indo-Pacific, 116–23, 125, 126 Indo-Pacific Business Forum, 122 Indo-Pacific Command, US, 126 Indochina, 51, 52, 54, 62 Indonesia, 2, 5, 18, 26, 39, 48, 83, 117, 131 Industrial and Commercial Bank of China, 48, 49, 103 industrial capacity cooperation, 85–8, 98, 102–4 industrial internet, 44 industrial parks, 10, 43, 55, 61, 67, 99, 102 Industrial Revolution, 84 information technology, 43–4, 74, 81, 86, 90, 94, 111, 170–71, 190 infrastructure, 3, 23, 26, 30, 40–45, 48, 50, 55, 58, 63, 86, 88, 124, 139, 141, 162, 167, 186 Afghanistan, 135 communications, 81, 118 digital, 43–4 European Union, 10, 141, 145 India, 64, 118, 135 Japan, 4, 136–8 Maritime Silk Road, 66, 67 Mediterranean, 65 Pakistan, 54, 62, 99, 105 Quadrilateral Security Dialogue, 121–2 Southeast Asia, 18–19, 70, 117, 130, 132 steel industry, 18 transportation, see transportation value chains, 96 Xinjiang, 20, 54 Inner Mongolia, China, 55 innovation, 76 Institute for International Finance, 153 intellectual property, 59, 88–9, 91, 97, 180, 190 international courts, 28, 190 international industrial capacity cooperation, 85–8, 98, 102–4 International Monetary Fund (IMF), 15, 156–7, 158–9, 172 Internet, 43–4, 86, 170–71 internet of things, 90, 94 Iran, 4, 22, 105–6 Iraq, 24 Irkeshtam, Xinjiang, 55 iron, 17 Islamabad, Pakistan, 60, 99, 101, 127, 157 Islamic State, 128 Islamism, 127–9 Istanbul, Turkey, 4, 24, 65 Italy, 48, 65, 140, 189 Izumi, Hiroto, 137 Jadhav, Kulbhushan, 105–6 Jakarta, Indonesia, 2, 5, 26, 39 Japan, 1, 5, 22, 123, 133, 136–8, 145, 165, 166, 169, 189 Buddhism, 111 Cold War, 21–2 India, relations with, 118 Indian Ocean, 4 infrastructure development, 4, 136–8 Quadrilateral Security Dialogue, 121–2 Second World War (1937–45), 119, 165 Javaid, Nadeem, 46 Jiang Qing, 14 Jiang Shigong, 183–4 Jiang Zemin, 15 Jiangsu Delong, 83 Jin Qi, 98 Jinnah Town, Quetta, 128 Johor, Malaysia, 149–51 Joint Statement on Cooperation on EEU and Silk Road Projects (2015), 57–8 joint ventures, 97 Journey to the West, 186, 188 Juncker, Jean-Claude, 138 Kaeser, Joe 170 Karachi, Sindh, 59, 100, 105, 106, 127 Karakoram Highway, 54, 60, 64 Kashgar, Xinjiang, 54, 59, 60, 64, 101 Kashmir, 60, 108–9, 117 Katanga, Democratic Republic of Congo, 104 Kaz Minerals 103 Kazakhstan, 8, 55–9, 129, 189 Astana International Exchange, 56 China–EEU free-trade agreement signing (2018), 58 and Eurasian Economic Union, 57 gateway to Europe, 56 Horgos International Cooperation Center, 55–6 industrial capacity cooperation, 103–4 railways, 54 Xi’s speech (2013), 23, 25–6, 39 Kazakhstan Aluminum, 103 keeping a low profile (tao guang yang hui), 15, 18, 32 Kenya, 101, 138, 171 Khan, Imran, 157–8 Khawar, Hasaan, 53 Khunjerab Pass, 101 Khyber Pakhtunkhwa, Pakistan, 54, 60, 100 Kizilsu Kirghiz, Xinjiang, 60 knowledge, 74, 76, 87 Kolkata, West Bengal, 64 Kortunov, Andrey, 135 kowtow, 35 Kra Isthmus, Thailand, 65, 186 Kuala Linggi Port, Malacca, 63 Kuala Lumpur, Malaysia, 130 Kuantan, Pahang, 63, 67 Kudaibergen, Dimash, 57 Kunming, Yunnan, 188 Kyaukpyu, Rakhine, 63, 64, 132, 154 Kyrgyzstan, 53, 54, 55, 103, 127 labor costs, 74, 83, 85, 99 labor shortages, 75 Lagarde, Christine, 158–9 Lahore, Punjab, 100, 157 Laos, 50, 52, 54, 129, 132 Latin America, 25, 187, 188 Leifeld Metal Spinning AG, 88 Lenin, Vladimir, 6, 78 Lenovo, 89–90 Li Hongzhang, 69 Li Keqiang, 44 Li Ruogu, 47 Liaoning, China, 55 liberal values, 123, 125, 133, 170 liberal world order, 141, 144, 167–86, 190, 192 Lighthizer, Robert, 91 lignite, 61 liquefied natural gas (LNG), 48, 66 Lisbon, Portugal, 2, 5 lithium-ion batteries, 81 Liu Chuanzhi, 89–90 Liu He, 92 loans, 11, 36, 46–7, 54, 108–9, 124, 126, 130, 132, 138, 141, 153–63, 190 London, England, 65, 160 Lord of the Rings, The (Tolkien), 1 Lou Jiwei, 76 Luo Jianbo, 7 Machiavelli, Niccolò, 31–4 machinery, 81, 90, 98, 156 Mackinder, Halford, 120 Macron, Emmanuel, 146–7 Made in China 2025 strategy, 85, 87, 90–92, 93 Mahan, Alfred, 120 Mahathir Mohamad, 130–31, 151, 155 Malabar naval exercises (2018), 135 Malacca, Malaysia, 3, 63 Malacca Strait, 21–2, 64, 65, 72, 117, 131 Malay Mail, 155 Malaysia, 3, 70, 117, 130–31, 154 debt, 154 Forest City, 149–51, 155 high-speed railways, 54, 130 Mahathir government (2018–), 130–31, 151, 155 1Malaysia Development Berhad scandal (2015–), 155 ports, 63, 67 Maldives, 134, 155 Mali, 129 Malik, Ashok, 109 Malta, 140 Mandarin, 107, 149, 188 Manila, Philippines, 122 Mann, James, 177 manufacturing, 11, 19, 68, 77, 85, 99 outsourcing, 68, 99 value chains, 3, 43, 64, 73–4, 79–82, 84–5, 94–104, 141 Manzhouli, Inner Mongolia, 55 Mao Zedong, 13–14, 31, 183 maps, 2–6, 24, 41, 64, 69 Maritime Silk Road, 24, 26, 28, 39, 41, 53, 62–72, 117 market integration, 41 Mars, 187 Marshall Plan, 40 Marx, Karl, 6 Marxism, 78 Massachusetts Institute of Technology (MIT), 177 Matarbari port, Bangladesh, 138 matchmaking services, 11 Mattis, James, 124 McMahon Line, 111 Mediterranean Sea, 4, 51, 62, 65, 119 Mei Xinyu, 21 Mekong Delta, 8 mergers and acquisitions, 42 Merkel, Angela, 88, 141, 144 meticulous selection, 72 Middle East, 4, 6, 22, 64, 120, 129, 163, 171 middle-income trap, 75–7, 85 migrant workers, 75 Milanovic, Branko, 173 military, 3, 12, 67, 71, 72, 101, 117, 126–7 Ming Empire (1368–1644), 163 Ming Hao, 30 minimum wage, 75 Ministry of Commerce, 21, 40, 93 Ministry of Communications, 69 Ministry of Finance, 49 Ministry of Foreign Affairs, 40 Ministry of Industry and Information Technology, 19 Ministry of Transportation, 14 Minmetals International Trust Co, 16 mobile payments, 193 Modi, Narendra, 106, 135–6 Mohan, Raja, 3, 121 Mombasa, Kenya, 138 Mongol Empire (1206–1368), 2, 25 Mongolia, 8, 36, 52, 55, 111 Moon, 187 Moraes, Frank, 112–13 Moscow, Russia, 4 Most Favored Nation status, 15 Mozambique, 138 multinationals, 74, 88–9 multipolar world system, 179 Mumbai, Maharashtra, 4, 105, 138 Myanmar, 52, 54, 63, 64, 72, 129, 132, 138, 154 Nacala, Nampula, 138 narcotics trade, 127 Nathan, Andrew, 159 National Aeronautics and Space Administration (NASA), 9 National Bureau of Statistics, 75 National Congress 18th (2012), 28 19th (2017), 29 National Cybersecurity Work Conference (2018), 84 National Development and Reform Commission, 40, 98 National Health Commission, 114 National League for Democracy, Myanmar, 132 National Museum of China, Beijing, 165, 166 National Party of New Zealand, 132 National People’s Congress, 44 National Rescue Party of Cambodia, 155 Nazarbayev University, 25–6 Nehru, Jawaharlal, 113 Nepal, 134, 135, 150 Netherlands, 56, 65 New Zealand, 132–3 Nigeria, 68 Ning Jizhe, 137 Nordin, Astrid, 42 Northern Sea Route, 66 Northwest Passage, 66 NPK fertilizer, 99 nuclear power/weapons, 21, 83, 88, 109, 166, 187 oil, 21, 22, 23, 40, 52, 64, 72, 106 1Malaysia Development Berhad scandal (2015–), 155 One China policy, 142 Open Times, 183 Opium War, First (1839–1842), 165 Organisation for Economic Co-operation and Development (OECD), 79 Osh, Kyrgyzstan, 54 overcapacity, 16, 19–20, 88 Overseas Chinese Affairs Office, 19 Overseas Investment Industrial Guiding Policy, 86 Pacific Command, US, 125–6 Pacific Journal, 71 Pacific Ocean, 3, 5, 9, 26, 45, 62, 116, 117, 125–6, 139 Indo-Pacific, 116–23, 125, 126 Pakistan, 12, 20, 46, 48, 52, 59–62, 64, 98–102, 105, 126–9, 133–4, 155, 156–8 Abbasi’s Beijing visit (2018), 126 agriculture, 99–100 balance of payments crisis, 156–8 Economic Corridor, 52, 59, 60, 62, 105, 108, 156–8 electricity production, 61 fibre-optic connectivity, 101 gateway to the Indian Ocean, 59 Grand Trunk Road, 53 Gwadar port, 46, 59, 61–2, 63, 64, 99–100, 101, 105–7, 117 hydropower, 48 IMF loans, 156–7 India, relations with, 105–7, 108–9, 117, 134 investment, 48 Jadhav arrest (2016), 105–6 Karakoram Highway, 54, 60, 64 Kashmir dispute, 108–9 loans, 46, 54, 156–8 manufacturing, 99 safe city project, 101 Tehreek-e-Insaf, 157–8 television, 101 terrorism, 106, 127–8, 135 textiles, 100 Thar desert, 61 value chains, 98–102 Pakistan-East Africa Cable Express, 101 Pandjaitan, Luhut, 131 Panikkar, Kavalam Madhava, 118 Pantucci, Raffaello, 134 Partnership for Quality Infrastructure, 137–8 patents, 88–9, 190 Pavlodar, Kazakhstan, 103 Peak Pegasus, 93 Pearl River Delta, China, 152 Peking University, 183, 188 Penang, Malaysia, 63 People’s Daily, 57 People’s Liberation Army (PLA), 32, 169 People’s Navigation Company, 69 Pericles, 8 Persian Gulf, 51, 64, 72 Peshawar, Khyber Pakhtunkhwa, 100 petcoke, 103 Petrochina, 103 pharmaceuticals, 113, 114 Phaya Thai Station, Bangkok, 137 Philippines, 19, 70, 117, 122, 156 philosophy, 40, 183 Phnom Penh, Cambodia, 70 phosphate, 19 piracy, 72 Piraeus, Greece, 65 Pirelli, 48 Plato, 150 Poland, 58, 140 Polar Silk Road, 66 Politburo, 39, 40, 165 political correctness, 182 Polo, Marco, 2, 10 Polonnaruwa, Sri Lanka, 156 Pompeo, Michael, 122–3, 157 ports, 9, 10, 12, 19, 36, 40, 46–7, 57, 63–5, 67–9, 96 Chabahar, Iran, 106–7 Doraleh, Djibouti, 63, 67–8 Gwadar, Pakistan, 46, 59, 61–2, 63, 64, 99–100, 101, 117 Hambantota, Sri Lanka, 46–7, 63, 64, 68, 117, 162 Kuala Linggi, Malaysia, 63 Kuantan, Malaysia, 63, 67 Kyaukpyu, Myanmar, 63, 64, 132, 154 Mediterranean, 65 Mombasa, Kenya, 138 Nacala, Mozambique, 138 Penang, Malaysia, 63 Ports-Park-City model, 67 Portugal, 2, 3, 5, 140, 163 power, see energy Prince, Erik, 128–9 property bubbles, 75 protectionism, 102, 114 public procurement, 12, 59 Punjab, Pakistan, 60, 99, 100, 157 Putin, Vladimir, 3, 57 Pyrenees, 189 Qing Empire (1636–1912), 107, 178 Quadrilateral Security Dialogue, 121–2 Qualcomm, 89 Quetta, Balochistan, 128 Raikot, Gilgit-Baltistan, 54 railways, 9–10, 11, 12, 18, 43, 52, 53–4, 57, 68, 83, 86, 89, 98, 100, 135 Addis Ababa–Djibouti, 46, 68 Bangkok–Chiang Mai, 137 Belgrade–Budapest, 143 Djibouti–Yaoundé, 68, 186–7 Islamabad–Gwadar, 60 Kashgar–Andijan, 54 Kuala Lumpur–Singapore, 130 Lahore overhead, 157 Mumbai–Ahmedabad, 138 United States, 122 Yunnan–Southeast Asia, 54 Rawat, Bipin, 108 RB Eden, 92 real estate market, 16, 75 reciprocity, 178–80 Red Sea, 72 reform and opening up, 13–15, 73 Ren Zhengfei, 90 Renaissance, 7 renewable energy, 21, 187, 188 Renmin University, 106 renminbi, 22–3, 159 Rennie, David, 190 Republic (Plato), 150 Research and Analysis Wing (R&AW), 105–6 responsible stakeholder, 169 Rio Tinto, 36 Road Towards Renewal exhibition (2012), 165 Road, see Maritime Silk Road roads, 9, 19, 40, 43, 52, 54, 55, 57, 67, 107–8 robotics, 75, 88, 90 Rogin, Josh, 122 Rolland, Nadège, 188, 190 Ross, Wilbur, 92 Rotterdam, South Holland, 65 Ruan Zongze, 92 rule of law, 28, 109, 111, 183–4 Russia, 5, 51, 52, 55, 133, 134, 139, 174, 175–6, 180, 181 and Central Asia, 57–9, 129, 133 energy, 22, 23 Eurasian Economic Union, 57–9 Eurasianism, 3–4 Joint Statement on Cooperation on EEU and Silk Road Projects (2015), 57–8 Pacific Fleet, 118 and renminbi internationalization, 23 Soviet era, see under Soviet Union steel industry, 82 Ukraine crisis (2013–), 176 Western values, rejection of, 175, 180, 181 Yamal LNG project, 48, 66 Sabang, Indonesia, 131 safe cities, 101, 171 salt, 67, 71 San Francisco, California, 151–2 Saravan, Sistan-Baluchistan, 105 Sargsyan, Tigran, 59 Sassanian Empire (224–651), 4 satellites, 187 second unbundling, 74 Second World War (1939–45), 165 self-driving vehicles, 88, 90, 186, 187, 190 Serbia, 83, 143 Set Aung, U, 132 Shandong University, 163 Shanghai, China, 2, 20, 92 Shanghai Cooperation Organization, 136 Shanghai Fosun Pharmaceutical, 113 Shanghai Pudong Development Bank, 16 Shanghai Stock Exchange, 50, 56, 103 Sharif, Nawaz, 133–4 sharp power, 170 sheet glass, 17, 83 Shenwan Hongyuan Securities, 16 Shenzhen, Guangdong, 28, 151 shipbuilding, 14, 17, 81, 186 Sichuan, China, 149 Siemens, 170 silicon dioxide, 103 Siliguri Corridor, India, 107–8 Silk Road, 2, 9–10, 23–6, 45, 53, 82, 138 Silk Road Economic Belt, 24, 25–6, 28, 39, 51–62, 83 Silk Road Fund, 48, 56, 98 silk, 23–4 Sindh, Pakistan, 59, 60, 99, 100, 101, 105, 106, 127 Singapore, 54, 77, 92, 119, 130, 150, 151, 160 Sino–Myanmar oil and gas pipeline, 64, 72 Sino–US relations, 116, 119, 121–6, 136, 179–80 and Belt and Road, 5–6, 11, 12, 15, 72, 121–4, 130, 136, 168 and Cold War, 14 and foreign exchange reserves, 16 and Indo-Pacific, 116, 119, 121–3, 125, 126 and Kra Isthmus canal proposal, 65 and Malacca Dilemma, 21–2, 64 and maritime hegemony, 70, 72 and Most Favored Nation status, 15 and Pakistan, 157 and reciprocity, 179–80 and reform and opening up, 14–15 and renminbi internationalization, 23 and South China Sea, 70 and steel, 17 Strategic and Economic Dialogue, 39 and Taiwan, 14 and tariffs, 83, 90–94 and technology transfers, 90–92, 178 Thucydides’ trap, 8 and trade deficit, 90, 92 trade war, 92–4, 173 war, potential for, 5, 8, 13, 14 Yangtze River patrols (1854–1937), 165 and ZTE, 94 Sirisena, Maithripala, 155–6 Sistan-Baluchistan, Iran, 105, 106–7 SLJ900/32, 54 Small, Andrew, 59, 158 smart cities, 44, 151–2 Smederevo, Serbia, 83 soft power, 111, 170 solar power, 187, 188 Somalia, 72 Somersault Cloud, 186 sorghum, 92 South Africa, 101 South America, 25, 187, 188 South China Sea, 21, 62, 65, 69–71, 118, 142, 170, 179 South Korea, 1, 77, 96, 97, 128 South Sudan, 186 Southeast Asia, 6, 8, 12, 18, 100, 131–2, 189 Buddhism, 111 China-Indochina Peninsula Economic Corridor, 51, 52, 54, 62 Indo–Chinese relations, 113, 117–18 Kra Isthmus canal proposal, 65, 186 Maritime Silk Road, 26 phosphate market, 19 South China Sea dispute, 21, 69–71, 142, 170, 179 textile industry, 100 Soviet Union, 1, 13, 14, 15, 21–2, 57, 104 soybeans, 90, 93 space travel, 187 Spain, 92, 140, 189 Sparta, 8 Sri Lanka, 12, 46–7, 63, 64, 68, 89, 117, 134, 155–6, 162 Hambantota port, 46–7, 63, 64, 68, 117, 162 Sirisena’s grant announcement (2018), 156 standards, 89–90 State Administration of Foreign Exchange, 48 State Council, 19, 39, 40, 49, 66, 86 state-owned companies, 42, 153, 160–61, 189 steamships, 69 steel industry, 16–17, 18, 20, 67, 82–4, 86, 88 striving for achievement, 18 Stuenkel, Oliver, 167 subprime mortgage crisis (2007–10), 153 Suez Canal, 3, 66, 68, 72, 119 Suifenhe Port, Heilongjiang, 55 Sukkur, Sindh, 99, 101 Sulawesi, Indonesia, 83 Sumatra, Indonesia, 3 Sun Pharmaceuticals, 114 Sun Wenguang, 163 Surkov, Vladislav, 3–4 surveillance, 44, 101, 171, 187, 190 Suvarnabhumi Airport, Bangkok, 137 Swamy, Subramanian, 110 Swaraj, Sushma, 135 Switzerland, 160, 168 Syria, 24 Tadjoura gulf, Djibouti, 67 taikonauts, 187 Taiwan, 14, 142 Tajikistan, 48, 127 Tanjung Pelepas Johor, 150 Tanzania, 138 tao guang yang hui, 15, 18, 32 Taoism, 11, 51 tariffs, 17, 56, 58, 79, 82, 83, 179 Tawang Monastery, Arunachal Pradesh, 111 tax holidays, 61 TBM Slurry, 54 technology transfers, 85–92, 97, 118, 177–8 Tehreek-e-Insaf, 157–8 telecommunications, 43–4, 52, 86, 89–90, 98, 101, 170–71 television, 101 terrorism, 106, 127–9, 135, 171 Texas, United States, 92 textiles, 86, 100–101 Thailand, 18, 54, 65, 83, 89, 129, 132, 136–7, 186 Thakot, Khyber Pakhtunkhwa, 54 Thar desert, 61 Thein Sein, 132 Thilawa special economic zone, Myanmar, 138 throw-money diplomacy, 163 Thucydides’ trap, 8 Tianjin, China, 129 Tianxia, 26–7, 29, 31–5, 78, 79, 192–3 Tibet, 36, 111–12, 117, 136, 189 Tibetan Academy of Buddhism, 112 Tillerson, Rex, 11, 123, 125 timber, 96 Times of India, 109 Tinbergen, Jan, 20 TIR (Transports Internationaux Routiers) Convention, 55 titanium dioxide, 103 Tokyo, Japan, 137 Tolkien, John Ronald Reuel, 1 tourism, 10, 11, 61, 71 trade wars, 92–4, 113–14, 173 trains, 9–10, 11, 12, 18, 43, 46 Trans-Siberian railway, 10 Transatlantic trade, 3, 139 transnational industrial policy, 81, 84 Transpacific trade, 3, 139 transparency, 12, 28, 109, 143, 144, 146, 157, 173, 193 Transpolar Route, 66 transportation, 9–10, 19, 25–6, 48–9, 52–4, 63–4, 81–3, 99, 103, 104, 118, 143, 162, 186 maritime, 63 railways, see railways roads, 9, 19, 40, 43, 52, 54, 55, 57, 67, 107–8 tributary system, 34–5 Trieste, Italy, 65 Trump, Donald, 83, 91, 93, 122, 124, 167, 179 Tsinghua University, 76, 163 Tsingshan Group Holdings, 83 Tumshuq, Xinjiang, 60 Turkey, 4, 24, 65, 82 Turkmenistan, 186 Twitter, 188 ‘two heads abroad’ (liangtou zai haiwai), 17 Ukraine, 11, 82, 176 United Arab Emirates, 62, 68, 160 United Kingdom, 2, 3, 17, 43, 65, 107, 112, 160, 165, 189, 193 United Nations, 29, 55, 72, 142, 172 United States, 1–2, 5–7, 8, 11, 12, 121–6, 161, 166–9, 176, 185–6 Apollo program, 9 Bush administration (2001–9), 169 Camp Lemonnier Djibouti, 68 China, relations with, see Sino–US relations Clinton administration (1992–2001), 177 Cold War, 14 immigration, 187 India, relations with, 119, 121–2, 134, 135 industrial output per person, 193 and International Monetary Fund (IMF), 157 Marshall Plan, 40 midterm elections (2018), 12–13 National Defense Strategy (2018), 116 National Security Strategy (2017), 179–80 Pacific Command, 125–6 Quadrilateral Security Dialogue, 121–2 Senate Armed Services Committee, 124 State Department, 123–4 steel industry, 17 subprime mortgage crisis (2007–10), 153 Taiwan, relations with, 14 Trump administration (2017–), 83, 90–94, 122–4, 167, 179 universal values, 175, 181, 184 Urdu, 128 Urumqi, Xinjiang, 20, 101, 188 Uyghurs, 20 Uzbekistan, 53, 54, 129 value chains, 3, 43, 64, 73–4, 79–82, 84–5, 94–104, 141 vanadium pentoxide, 103 Venice, Veneto, 65 Vietnam, 19, 54, 70, 100, 117, 132 Vision and Actions document (2015), 40, 41, 45, 49, 50, 52, 67, 78 Vision for Maritime Cooperation (2017), 62 Vladivostok, Primorsky Krai, 118 Wakhan corridor, Afghanistan, 128 Wallerstein, Immanuel, 78 Wang Changyu, 112 Wang Huning, 40 Wang Jisi, 31, 76 Wang Yang, 39 Wang Yi, 40, 60, 123 Wang Yingyao, 50–51 Wang Yiwei, 26 Wang Zhaoxing, 50 Warsaw, Poland, 140 Washington Post, 122 Wei Fenghe, 126 Weibo, 188 Weissmann, Mikael, 42 Wenzhou, Zhejiang, 83 West Asia corridor, 51, 52 West Germany (1949–90), 22, 166 Western world, 5, 30, 31, 165–86, 190–93 Asia-Pacific region, 13 Cold War, 1, 2 cultural imperialism, 28 democracy, 125, 133, 166, 171, 172, 174, 176, 181–3 end of history, 36 global financial crisis (2008), 16–17, 161 individualism, 27, 189 liberal world order, 141, 144, 167–86, 190, 192 Machiavellianism, 31–4 market economies, 16 Marxism, 78 polis, 31 rule of law, 183 rules-based order, 11, 35, 179 separation of powers, 182 soft power, 111 standards, 89 technology, 15, 87, 177–8 telecommunications, 101 and Tianxia, 30–34, 78, 192 value chains, 95, 96, 100, 104 values, 123, 125, 133, 167, 175, 177–8 white elephants, 51 Wickremesinghe, Ranil, 47 win-win, 27–8, 33, 37 wind power, 188 Witness to an Era (Moraes), 113 Working Conference on Neighborhood Policy (2013), 17–18 World Bank, 15, 172 World Economic Forum, 168 World Trade Organization, 170, 177 world-systems theory, 78 Wright, Thomas, 174 Xi Jinping, 11, 183 Astana speech (2013), 23, 25–6, 39 Belt and Road Forum for International Cooperation (2017), 152 Boao Forum for Asia speech (2015), 27, 32 and Constitution, 164 Davos speech (2017), 168 Duterte, relationship with, 156 Jakarta speech (2013), 23, 26, 39 Joint Statement on Cooperation on EEU and Silk Road Projects (2015), 57 London visit (2015), 43 Mahathir’s letter (2018), 130–31 Modi, summit with (2018), 135 National Congress, 19th (2017), 29, 181 National Cybersecurity Work Conference (2018), 84 presidential term limits repeal (2018), 164, 174 Road Towards Renewal exhibition (2012), 165 Sirisena, grant to (2018), 156 and state-owned companies, 42, 153 Sun Wenguang’s letter (2018), 163 telecommunications, 43 Trump’s visit (2017), 124 and value chains, 94 Wang Huning, relationship with, 40 and Western democracy, 166, 181 Working Conference on Neighborhood Policy (2013), 17–18 Xi’an, Shaanxi, 24, 28, 147, 188 Xinhua, 24, 41, 64 Xinjiang, 20, 54, 55, 56, 59, 60, 100–101, 128–9, 188, 189 Xiong Guangkai, 32 Xu Jin, 33 Xu Zhangrun, 163–4 Yamal LNG project, 48, 66 Yang Jian, 132 Yang Jiechi, 39, 171 Yang Jing, 40 Yangtze River, 165 Yao Yunzhu, 169–70 Ye Peijian, 187 yuan, see renminbi Yunnan, China, 54, 129, 149, 188 Zeng Jinghan, 181 zero-sum, 27 Zhang Gaoli, 39 Zhang Qian, 25 Zhang Weiwei, 182–3, 184 Zhao Tingyang, 27 Zheng He, 162–3 Zhi Zhenfeng, 84 Zimbabwe, 12, 44 Zoellick, Robert, 169 ZTE, 94, 170–71 Zurich, Switzerland, 160 First published in the United Kingdom in 2018 by C.


Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, Amazon Web Services, anti-work, artificial general intelligence, autonomous vehicles, basic income, business cycle, cloud computing, collective bargaining, correlation does not imply causation, creative destruction, data is the new oil, David Graeber, David Ricardo: comparative advantage, deindustrialization, deskilling, disintermediation, Donald Trump, Erik Brynjolfsson, feminist movement, Frederick Winslow Taylor, future of work, gig economy, global supply chain, income inequality, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, off grid, pattern recognition, post-work, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Steve Jobs, strong AI, technoutopianism, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

This is not only a quantitative increase in a particular type of data (say, geolocation or financial data), but also a qualitative increase in the kinds of data that are being collected. Partly because of this, what we see is all of these companies starting to expand out from their core business to other places. Amazon is no longer just an ecommerce company; it is getting involved in cloud computing, media content, logistics and the consumer internet of things, to name just a few endeavours. Likewise, with Google and, to a lesser degree, with Facebook. Both are investing and buying up companies all across the tech space in areas that offer new data extraction possibilities. The old monopolies were based on vertical or horizontal integration—but today there is a more rhizomatic integration based upon data as a resource. The end result is that these companies are no longer being siloed into single 140 N.

The critical assumption in this argument is that the productivity gains arising from process technologies are shared with workers and consumers, and thus increase demand and local production (Vivarelli 2014). Another major channel of job creation is the rise of new capital, software and robotics industries. The same process innovations that displace workers in the user industries create demand for workers in the producer industries. The new robots and smart machines need to be developed, designed, built, maintained and repaired. Additionally, the Internet of Things, Industry 4.0, digital Taylorism, driverless cars, big data and artificial intelligence require high investment in new infrastructure such as broadband, transport equipment and IT equipment, as well as increasingly complex software. As a result, process innovations and compensation effects destroy and create jobs, however, they tend to create fewer jobs than they destroyed. Also, the new job profiles and occupations emerging with product innovations tend to be more complex and skills intensive.

., 59 Graeber, David, 6, 76, 157, 161, 168 Greek ideas of work, 74 Growth, 2, 6, 7, 12, 25, 27, 30, 31, 55, 69, 75, 85, 86, 88, 110, 126, 128, 130, 135, 169, 176, 180, 183, 185, 190, 192, 198, 200 H Happiness, 5, 62, 195 Harrop, Andrew, 180 Hassabis, Demis, 119 Hayden, Anders, 182, 183 Healthcare, 3, 87, 94, 117, 165, 197 Heterodox economics, 54, 56, 62 Hierarchy, 46, 48, 55, 69, 170 High-skilled jobs, 128, 134 Homejoy, 135 Homo economicus, 56, 57 Homo laborans, 3 Homo ludens, 3 Household economy, 4, 38–40, 45, 47 Housewives, 42, 43, 46, 47 Housework, 39, 40, 42, 44, 47 Hunter-gatherers, 11, 26, 27, 30 Index I Idleness, 54 India, 44–47 Industrial Revolution, 2, 4, 14, 29, 37, 75, 93, 94, 175, 177, 190, 191 Inequality, 67–69, 86, 87, 192, 193, 199, 200 Informal economy, 47 Information technology, 86, 161 Infrastructure digital, 140 physical, 103 Innovation, 6, 10, 14, 16, 18, 34, 67, 69, 189–199 process innovation vs. product innovation, 16, 18, 190–191, 195 International Labour Organisation (ILO), 193 Internet of Things, 139, 191 Investment in capital, 114 in skills, 70 J Japan, 117 Jensen, C, 55 Job guarantee, 172 Jobs, Steve, 73 Journalism automation of, 118 clickbait, 118 Juries, algorithmic selection of, 150, 153 K Karstgen, Jack, 196 Kasparov, Garry, 91, 112, 129, 130 207 Katz, Lawrence, 198 Kennedy, John F., 160 Keune, Maarten, 180 Keynes, John Maynard, 6, 9, 11, 27, 60, 61, 160, 161, 176 King, Martin Luther, 171 Knowledge (tacit vs. explicit), 127 Komlosy, Andrea, 4, 75 Kubrick, Stanley, 26 Kurzweil, Raymond, 101, 103, 104 Kuznets, Simon, 190 L Labour, 3, 10, 11, 13–16, 18–21, 29, 34–36, 38, 43–46, 55, 59, 65–70, 73–76, 85–87, 89, 90, 93, 94, 96, 114, 125, 126, 128, 130, 131, 141, 158, 165, 176–180, 183–184, 189, 190, 192–196, 199–200 Labour market polarisation, 67, 70, 126 Labour markets, 67, 68, 70, 87, 90, 96, 125, 126, 128, 130, 131, 141, 178, 183–184, 189, 192, 193, 195, 196, 199–200 Labour-saving effect, 86 Lall, Sanjaya, 193 Language translation, 105, 106 Latent Damage Act 1986, 127 Law automation of, 145, 152, 153 ethics, 145–153 Lawrence, Mathew, 177 Layton, E., 58 Le Bon, Gustave, 101 Lee, Richard, 26 Legal search/legal discovery, 148–150 208 Index Leisure, 3, 10, 11, 19, 27, 48, 55, 56, 59–62, 65, 77, 79, 117, 118, 159, 161, 178, 180, 182, 184, 191, 195 Levy, Frank, 126 List, Friedrich, 193 Love, 55, 74, 76, 99, 103, 106, 112, 118 Low-income jobs, 96 Loyalty, 69 Luddites, 2, 14, 18, 35, 59, 94, 96 Lyft, 136 M Machine learning, 59, 84, 90, 91, 96, 138, 139 Machines, 2, 5, 10, 12–15, 17, 19, 20, 35, 36, 38, 59, 84–87, 90–96, 99–103, 105–107, 109–121, 127–131, 138, 139, 145, 147, 148, 160, 168, 191 Machine vision, 120 Malthusian, 19 Man, Henrik de, 79 Management, 27, 30, 41, 69, 70 management theory/ organisational theory (see also Scientific management) Mann, Michael, 46 Manual work, 1 Manufacturing, 86, 87, 90, 94, 95, 176, 184, 198 Markets/market forces, 5, 6, 21, 38, 44–46, 67, 68, 70, 79, 85–88, 90, 96, 120, 125, 126, 128, 130, 131, 140, 141, 150, 152, 159, 164, 165, 171, 178, 183, 189–193, 195, 196, 198–200 Marx, Karl, 17, 18, 27, 56–59, 61, 62, 78 Matrimonial relationships, 37 McCormack, Win, 159 Meaning, 4, 9, 10, 19, 25, 54, 57, 58, 66, 73, 76, 78, 79, 84, 106, 116, 176, 180 Mechanisation, 15, 17, 19, 20, 192 Meckling, W., 55 Méda, Dominique, 183 Medical diagnosis (automation of ), 128, 129 Menger, Pierre-Michel, 4 Mental labour, 3 Meritocracy, 28 Middle-income jobs, 90, 93, 94 Migration, 40, 47 Minimum wage, 67, 69 Mining, 26, 38, 197 Mokyr, J., 59 Monopolies, 6, 136, 138–140 Morals/morality, 48, 77, 159, 160, 162, 164, 166, 167 Moravec’s paradox, 131 Murnane, Richard, 126 N Nagel, Thomas, 100, 102 National Living wage, 184 Needs vs.


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Python Data Analytics: With Pandas, NumPy, and Matplotlib by Fabio Nelli

Amazon Web Services, centre right, computer vision, Debian, DevOps, Google Earth, Guido van Rossum, Internet of things, optical character recognition, pattern recognition, sentiment analysis, speech recognition, statistical model, web application

Thanks to their contribution, the processing speed of deep learning is increased by several orders of magnitude (days instead of months). Data Availability : Open Data Source, Internet of Things, and Big Data Another very important factor affecting the development of deep learning is the huge amount of data that can be accessed. In fact, the data are the fundamental ingredient for the functioning of neural networks, both for the learning phase and for their verification phase. Thanks to the spread of the Internet all over the world, now everyone can access and produce data. While a few years ago only a few organizations were providing data for analysis, today, thanks to the IoT (Internet of Things ), many sensors and devices acquire data and make them available on networks. Not only that, even social networks and search engines (like Facebook, Google, and so on) can collect huge amounts of data, analyzing in real time millions of users connected to their services (called Big Data ).

“Science leads us forward in knowledge, but only analysis makes us more aware” This book is dedicated to all those who are constantly looking for awareness Table of Contents Chapter 1:​ An Introduction to Data Analysis Data Analysis Knowledge Domains of the Data Analyst Computer Science Mathematics and Statistics Machine Learning and Artificial Intelligence Professional Fields of Application Understanding the Nature of the Data When the Data Become Information When the Information Becomes Knowledge Types of Data The Data Analysis Process Problem Definition Data Extraction Data Preparation Data Exploration/​Visualization Predictive Modeling Model Validation Deployment Quantitative and Qualitative Data Analysis Open Data Python and Data Analysis Conclusions Chapter 2:​ Introduction to the Python World Python—The Programming Language Python—The Interpreter Python 2 and Python 3 Installing Python Python Distributions Using Python Writing Python Code IPython PyPI—The Python Package Index The IDEs for Python SciPy NumPy Pandas matplotlib Conclusions Chapter 3:​ The NumPy Library NumPy:​ A Little History The NumPy Installation Ndarray:​ The Heart of the Library Create an Array Types of Data The dtype Option Intrinsic Creation of an Array Basic Operations Arithmetic Operators The Matrix Product Increment and Decrement Operators Universal Functions (ufunc) Aggregate Functions Indexing, Slicing, and Iterating Indexing Slicing Iterating an Array Conditions and Boolean Arrays Shape Manipulation Array Manipulation Joining Arrays Splitting Arrays General Concepts Copies or Views of Objects Vectorization Broadcasting Structured Arrays Reading and Writing Array Data on Files Loading and Saving Data in Binary Files Reading Files with Tabular Data Conclusions Chapter 4:​ The pandas Library—An Introduction pandas:​ The Python Data Analysis Library Installation of pandas Installation from Anaconda Installation from PyPI Installation on Linux Installation from Source A Module Repository for Windows Testing Your pandas Installation Getting Started with pandas Introduction to pandas Data Structures The Series The DataFrame The Index Objects Other Functionalities on Indexes Reindexing Dropping Arithmetic and Data Alignment Operations Between Data Structures Flexible Arithmetic Methods Operations Between DataFrame and Series Function Application and Mapping Functions by Element Functions by Row or Column Statistics Functions Sorting and Ranking Correlation and Covariance “Not a Number” Data Assigning a NaN Value Filtering Out NaN Values Filling in NaN Occurrences Hierarchical Indexing and Leveling Reordering and Sorting Levels Summary Statistic by Level Conclusions Chapter 5:​ pandas:​ Reading and Writing Data I/​O API Tools CSV and Textual Files Reading Data in CSV or Text Files Using RegExp to Parse TXT Files Reading TXT Files Into Parts Writing Data in CSV Reading and Writing HTML Files Writing Data in HTML Reading Data from an HTML File Reading Data from XML Reading and Writing Data on Microsoft Excel Files JSON Data The Format HDF5 Pickle—Python Object Serialization Serialize a Python Object with cPickle Pickling with pandas Interacting with Databases Loading and Writing Data with SQLite3 Loading and Writing Data with PostgreSQL Reading and Writing Data with a NoSQL Database:​ MongoDB Conclusions Chapter 6:​ pandas in Depth:​ Data Manipulation Data Preparation Merging Concatenating Combining Pivoting Removing Data Transformation Removing Duplicates Mapping Discretization and Binning Detecting and Filtering Outliers Permutation Random Sampling String Manipulation Built-in Methods for String Manipulation Regular Expressions Data Aggregation GroupBy A Practical Example Hierarchical Grouping Group Iteration Chain of Transformations Functions on Groups Advanced Data Aggregation Conclusions Chapter 7:​ Data Visualization with matplotlib The matplotlib Library Installation The IPython and IPython QtConsole The matplotlib Architecture Backend Layer Artist Layer Scripting Layer (pyplot) pylab and pyplot pyplot A Simple Interactive Chart The Plotting Window Set the Properties of the Plot matplotlib and NumPy Using the kwargs Working with Multiple Figures and Axes Adding Elements to the Chart Adding Text Adding a Grid Adding a Legend Saving Your Charts Saving the Code Converting Your Session to an HTML File Saving Your Chart Directly as an Image Handling Date Values Chart Typology Line Charts Line Charts with pandas Histograms Bar Charts Horizontal Bar Charts Multiserial Bar Charts Multiseries Bar Charts with pandas Dataframe Multiseries Stacked Bar Charts Stacked Bar Charts with a pandas Dataframe Other Bar Chart Representations Pie Charts Pie Charts with a pandas Dataframe Advanced Charts Contour Plots Polar Charts The mplot3d Toolkit 3D Surfaces Scatter Plots in 3D Bar Charts in 3D Multi-Panel Plots Display Subplots Within Other Subplots Grids of Subplots Conclusions Chapter 8:​ Machine Learning with scikit-learn The scikit-learn Library Machine Learning Supervised and Unsupervised Learning Training Set and Testing Set Supervised Learning with scikit-learn The Iris Flower Dataset The PCA Decomposition K-Nearest Neighbors Classifier Diabetes Dataset Linear Regression:​ The Least Square Regression Support Vector Machines (SVMs) Support Vector Classification (SVC) Nonlinear SVC Plotting Different SVM Classifiers Using the Iris Dataset Support Vector Regression (SVR) Conclusions Chapter 9: Deep Learning with TensorFlow Artificial Intelligence, Machine Learning, and Deep Learning Artificial intelligence Machine Learning Is a Branch of Artificial Intelligence Deep Learning Is a Branch of Machine Learning The Relationship Between Artificial Intelligence, Machine Learning, and Deep Learning Deep Learning Neural Networks and GPUs Data Availability:​ Open Data Source, Internet of Things, and Big Data Python Deep Learning Python Frameworks Artificial Neural Networks How Artificial Neural Networks Are Structured Single Layer Perceptron (SLP) Multi Layer Perceptron (MLP) Correspondence Between Artificial and Biological Neural Networks TensorFlow TensorFlow:​ Google’s Framework TensorFlow:​ Data Flow Graph Start Programming with TensorFlow Installing TensorFlow Programming with the IPython QtConsole The Model and Sessions in TensorFlow Tensors Operation on Tensors Single Layer Perceptron with TensorFlow Before Starting Data To Be Analyzed The SLP Model Definition Learning Phase Test Phase and Accuracy Calculation Multi Layer Perceptron (with One Hidden Layer) with TensorFlow The MLP Model Definition Learning Phase Test Phase and Accuracy Calculation Multi Layer Perceptron (with Two Hidden Layers) with TensorFlow Test Phase and Accuracy Calculation Evaluation of Experimental Data Conclusions Chapter 10:​ An Example— Meteorological Data A Hypothesis to Be Tested:​ The Influence of the Proximity of the Sea The System in the Study:​ The Adriatic Sea and the Po Valley Finding the Data Source Data Analysis on Jupyter Notebook Analysis of Processed Meteorological Data The RoseWind Calculating the Mean Distribution of the Wind Speed Conclusions Chapter 11:​ Embedding the JavaScript D3 Library in the IPython Notebook The Open Data Source for Demographics The JavaScript D3 Library Drawing a Clustered Bar Chart The Choropleth Maps The Choropleth Map of the U.​S.​

Index A Accents, LaTeX Advanced Data aggregation apply() functions transform() function Anaconda Anderson Iris Dataset, see Iris flower dataset Array manipulation joining arrays column_stack() and row_stack() hstack() function vstack() function splitting arrays hsplit() function split() function vsplit() function Artificial intelligence schematization of Artificial neural networks biological networks edges hidden layer input and output layer multi layer perceptron nodes schematization of SLP ( see Single layer perceptron (SLP)) weight B Bar chart 3D error bars horizontal matplotlib multiserial multiseries stacked bar pandas DataFrame representations stacked bar charts x-axis xticks() function Bayesian methods Big Data Bigrams Biological neural networks Blending operation C Caffe2 Chart typology Choropleth maps D3 library geographical representations HTML() function jinja2 JSON and TSV JSON TopoJSON require.config() results US population data source census.gov file TSV, codes HTML() function jinja2.Template pop2014_by_county dataframe population.csv render() function SUMLEV values Classification and regression trees Classification models Climatic data Clustered bar chart IPython Notebook jinja2 render() function Clustering models Collocations Computer vision Concatenation arrays combining concat() function dataframe keys option pivoting hierarchical indexing long to wide format stack() function unstack() function removing Correlation Covariance Cross-validation Cython D Data aggregation apply() functions GroupBy groupby() function operations output of SPLIT-APPLY-COMBINE hierarchical grouping merge() numeric and string values price1 column transform() function Data analysis charts data visualization definition deployment phase information knowledge knowledge domains computer science disciplines fields of application machine learning and artificial intelligence mathematics and statistics problems of open data predictive model process data sources deployment exploration/visualization extraction model validation planning phase predictive modeling preparation problem definition stages purpose of Python and quantitative and qualitative types categorical data numerical data DataFrame pandas definition nested dict operations structure transposition structure Data manipulation aggregation ( see Data aggregation) concatenation discretization and binning group iteration permutation phases of preparation ( see Data preparation) string ( see String manipulation) transformation Data preparation DataFrame merging operation pandas.concat() pandas.DataFrame.combine_first() pandas.merge() procedures of Data structures, operations DataFrame and series flexible arithmetic methods Data transformation drop_duplicates() function mapping adding values axes dict objects replacing values remove duplicates Data visualization adding text axis labels informative label mathematical expression modified of text() function bar chart ( see Bar chart) chart typology contour plot/map data analysis 3D surfaces grid grids, subplots handling date values histogram installation IPython and IPython QtConsole kwargs figures and axes horizontal subplots linewidth plot() function vertical subplots legend chart of legend() function multiseries chart upper-right corner line chart ( see Line chart) matplotlib architecture and NumPy matplotlib library ( see matplotlib library) mplot3d multi-panel plots grids, subplots subplots pie charts axis() function modified chart pandas Dataframe pie() function shadow kwarg plotting window buttons of commands matplotlib and NumPy plt.plot() function properties QtConsole polar chart pyplot module saving, charts HTML file image file source code scatter plot, 3D Decision trees Deep learning artificial ( see Artificial neural networks) artificial intelligence data availability machine learning neural networks and GPUs Python frameworks programming language schematization of TensorFlow ( see TensorFlow) Digits dataset definition digits.images array digit.targets array handwritten digits handwritten number images matplotlib library scikit-learn library Discretization and binning any() function categorical type cut() function describe() function detecting and filtering outliers qcut() std() function value_counts() function Django Dropping E Eclipse (pyDev) Element-wise computation Expression-oriented programming F Financial data Flexible arithmetic methods Fonts, LaTeX G Gradient theory Graphics Processing Unit (GPU) Grouping Group iteration chain of transformations functions on groups mark() function quantiles() function GroupBy object H Handwriting recognition digits dataset handwritten digits, matplotlib library learning and predicting OCR software scikit-learn svc estimator TensorFlow validation set, six digits Health data Hierarchical indexing arrays DataFrame reordering and sorting levels stack() function statistic levels structure two-dimensional structure I IDEs, see Interactive development environments (IDEs) Image analysis concept of convolutions definition edge detection blackandwhite.jpg image black and white system filters function gradients.jpg image gray gradients Laplacian and Sobel filters results source code face detection gradient theory OpenCV ( see Open Source Computer Vision (OpenCV)) operations representation of Indexing functionalities arithmetic and data alignment dropping reindexing Integration Interactive development environments (IDEs) Eclipse (pyDev) Komodo Liclipse NinjaIDE Spyder Sublime Interactive programming language Interfaced programming language Internet of Things (IoT) Interpreted programming language Interpreter characterization Cython Jython PVM PyPy tokenization IPython and IPython QtConsole Jupyter project logo Notebook DataFrames QtConsole shell tools of Iris flower dataset Anderson Iris Dataset IPython QtConsole Iris setosa features length and width, petal matplotlib library PCA decomposition target attribute types of analysis variables J JavaScript D3 Library bar chart CSS definitions data-driven documents HTML importing library IPython Notebooks Jinja2 library pandas dataframe render() function require.config() method web chart creation Jinja2 library Jython K K-nearest neighbors classification decision boundaries 2D scatterplot, sepals predict() function random.permutation() training and testing set L LaTeX accents fonts fractions, binomials, and stacked numbers with IPython Notebook in Markdown Cell in Python 2 Cell with matplotlib radicals subscripts and superscripts symbols arrow symbols big symbols binary operation and relation symbols Delimiters Hebrew lowercase Greek miscellaneous symbols standard function names uppercase Greek Learning phase Liclipse Linear regression Line chart annotate() arrowprops kwarg Cartesian axes color codes data points different series gca() function Greek characters LaTeX expression line and color styles mathematical expressions mathematical function pandas plot() function set_position() function xticks() and yticks() functions Linux distribution LOD cloud diagram Logistic regression M Machine learning (ML) algorithm development process deep learning diabetes dataset features/attributes Iris flower dataset learning problem linear/least square regression coef_ attribute fit() function linear correlation parameters physiological factors and progression of diabetes single physiological factor schematization of supervised learning SVM ( see Support vector machines (SVMs)) training and testing set unsupervised learning Mapping adding values inplace option rename() function renaming, axes replacing values Mathematical expressions with LaTeX, see LaTeX MATLAB matplotlib matplotlib library architecture artist layer backend layer functions and tools layers pylab and pyplot scripting layer (pyplot) artist layer graphical representation hierarchical structure primitive and composite graphical representation LaTeX NumPy Matrix product Merging operation DataFrame dataframe objects index join() function JOIN operation left_index/right_index options left join, right join and outer join left_on and right_on merge() function Meteorological data Adriatic Sea and Po Valley cities Comacchio image of mountainous areas reference standards TheTimeNow website climate data source JSON file Weather Map site IPython Notebook chart representation CSV files DataFrames humidity function linear regression matplotlib library Milan read_csv() function result shape() function SVR method temperature Jupyter Notebook access internal data command line dataframe extraction procedures Ferrara JSON file json.load() function parameters prepare() function RoseWind ( see RoseWind) wind speed Microsoft excel files dataframe data.xls internal module xlrd read_excel() function MongoDB Multi Layer Perceptron (MLP) artificial networks evaluation of experimental data hidden layers IPython session learning phase model definition test phase and accuracy calculation Musical data N Natural Language Toolkit (NLTK) bigrams and collocations common_contexts() function concordance() function corpora downloader tool fileids() function HTML pages, text len() function library macbeth variable Python library request() function selecting words sentimental analysis sents() function similar() function text, network word frequency macbeth variable most_common() function nltk.download() function nltk.FreqDist() function stopwords string() function word search Ndarray array() function data, types dtype (data-type) intrinsic creation type() function NOSE MODULE “Not a Number” data filling, NaN occurrences filtering out NaN values NaN value NumPy library array manipulation ( see Array manipulation) basic operations aggregate functions arithmetic operators increment and decrement operators matrix product ufunc broadcasting compatibility complex cases operator/function BSD conditions and Boolean arrays copies/views of objects data analysis indexing bidimensional array monodimensional ndarray negative index value installation iterating an array ndarray ( see Ndarray) Numarray python language reading and writing array data shape manipulation slicing structured arrays vectorization O Object-oriented programming language OCR, see Optical Character Recognition (OCR) software Open data Open data sources climatic data demographics IPython Notebook matplotlib pandas dataframes pop2014_by_state dataframe pop2014 dataframe United States Census Bureau financial data health data miscellaneous and public data sets musical data political and government data publications, newspapers, and books social data sports data Open Source Computer Vision (OpenCV) deep learning image processing and analysis add() function blackish image blending destroyWindow() method elementary operations imread() method imshow() method load and display merge() method NumPy matrices saving option waitKey() method working process installation MATLAB packages start programming Open-source programming language Optical Character Recognition (OCR) software order() function P Pandas dataframes Pandas data structures DataFrame assigning values deleting column element selection filtering membership value nested dict transposition evaluating values index objects duplicate labels methods NaN values NumPy arrays and existing series operations operations and mathematical functions series assigning values declaration dictionaries filtering values index internal elements, selection operations Pandas library correlation and covariance data structures ( see Pandas data structures) function application and mapping element row/column statistics getting started hierarchical indexing and leveling indexes ( see Indexing functionalities) installation Anaconda development phases Linux module repository, Windows PyPI source testing “Not a Number” data python data analysis sorting and ranking Permutation new_order array np.random.randint() function numpy.random.permutation() function random sampling DataFrame take() function Pickle—python object serialization cPickle frame.pkl pandas library stream of bytes Political and government data pop2014_by_county dataframe pop2014_by_state dataframe pop2014 dataframe Portable programming language PostgreSQL Principal component analysis (PCA) Public data sets PVM, see Python virtual machine (PVM) pyplot module interactive chart Line2D object plotting window show() function PyPy interpreter Python data analysis library deep learning frameworks module OpenCV Python Package Index (PyPI) Python’s world code implementation distributions Anaconda Enthought Canopy Python(x,y) IDEs ( see Interactive development environments (IDEs)) installation interact interpreter ( see Interpreter) IPython ( see IPython) programming language PyPI Python 2 Python 3 running, entire program code SciPy libraries matplotlib NumPy pandas shell source code data structure dictionaries and lists functional programming Hello World index libraries and functions map() function mathematical operations print() function writing python code, indentation Python virtual machine (PVM) PyTorch Q Qualitative analysis Quantitative analysis R R Radial Basis Function (RBF) Radicals, LaTeX Ranking Reading and writing array binary files tabular data Reading and writing data CSV and textual files header option index_col option myCSV_01.csv myCSV_03.csv names option read_csv() function read_table() function .txt extension databases create_engine() function dataframe pandas.io.sql module pgAdmin III PostgreSQL read_sql() function read_sql_query() function read_sql_table() function sqlalchemy sqlite3 DataFrame objects functionalities HDF5 library data structures HDFStore hierarchical data format mydata.h5 HTML files data structures read_html () web_frames web pages web scraping I/O API Tools JSON data books.json frame.json json_normalize() function JSONViewer normalization read_json() and to_json() read_json() function Microsoft excel files NoSQL database insert() function MongoDB pickle—python object serialization RegExp metacharacters read_table() skiprows TXT files nrows and skiprows options portion by portion writing ( see Writing data) XML ( see XML) Regression models Reindexing RoseWind DataFrame hist array polar chart scatter plot representation showRoseWind() function S Scikit-learn library data analysis k-nearest neighbors classification PCA Python module sklearn.svm.SVC supervised learning svm module SciPy libraries matplotlib NumPy pandas Sentimental analysis document_features() function documents list() function movie_reviews negative/positive opinion opinion mining Shape manipulation reshape() function shape attribute transpose() function Single layer perceptron (SLP) accuracy activation function architecture cost optimization data analysis evaluation phase learning phase model definition explicitly implicitly learning phase placeholders tf.add() function tf.nn.softmax() function modules representation testing set test phase and accuracy calculation training sets Social data sort_index() function Sports data SQLite3 stack() function String manipulation built-in methods count() function error message index() and find() join() function replace() function split() function strip() function regular expressions findall() function match() function re.compile() function regex re.split() function split() function Structured arrays dtype option structs/records Subjective interpretations Subscripts and superscripts, LaTeX Supervised learning machine learning scikit-learn Support vector classification (SVC) decision area effect, decision boundary nonlinear number of points, C parameter predict() function regularization support_vectors array training set, decision space Support vector machines (SVMs) decisional space decision boundary Iris Dataset decision boundaries linear decision boundaries polynomial decision boundaries polynomial kernel RBF kernel training set SVC ( see Support vector classification (SVC)) SVR ( see Support vector regression (SVR)) Support vector regression (SVR) curves diabetes dataset linear predictive model test set, data swaplevel() function T TensorFlow data flow graph Google’s framework installation IPython QtConsole MLP ( see Multi Layer Perceptron (MLP)) model and sessions SLP ( see Single layer perceptron (SLP)) tensors operation parameters print() function representations of tf.convert_to_tensor() function tf.ones() method tf.random_normal() function tf.random_uniform() function tf.zeros() method Text analysis techniques definition NLTK ( see Natural Language Toolkit (NLTK)) techniques Theano trigrams() function U, V United States Census Bureau Universal functions (ufunc) Unsupervised learning W Web Scraping Wind speed polar chart representation RoseWind_Speed() function ShowRoseWind() function ShowRoseWind_Speed() function to_csv () function Writing data HTML files myFrame.html to_html() function na_rep option to_csv() function X, Y, Z XML books.xml getchildren() getroot() function lxml.etree tree structure lxml library objectify parse() function tag attribute text attribute


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