digital twin

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Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty, H. James Wilson

3D printing, AI winter, algorithmic management, algorithmic trading, AlphaGo, Amazon Mechanical Turk, Amazon Robotics, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, circular economy, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, data science, deep learning, DeepMind, digital twin, disintermediation, Douglas Hofstadter, driverless car, en.wikipedia.org, Erik Brynjolfsson, fail fast, friendly AI, fulfillment center, future of work, Geoffrey Hinton, Hans Moravec, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, machine translation, Marc Benioff, natural language processing, Neal Stephenson, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, robotic process automation, Rodney Brooks, Salesforce, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, Snow Crash, software as a service, speech recognition, tacit knowledge, telepresence, telepresence robot, text mining, the scientific method, uber lyft, warehouse automation, warehouse robotics

Engineers, thanks to AI, now have more data than ever to understand the operations of their systems.7 Reimagined operations. The field data collected also enables GE to build digital twins of its deployed products, like its jet engines. Engineers can then test virtual flights in which the plane experiences cold, heat, dust, rain, and even a flock of birds.8 The company is also monitoring ten thousand wind turbines, and their digital twins are helping the turbines to adapt in real time. One valuable insight from an analysis of that data is that, depending on the direction of the wind, it might be best to have the leading turbine run slower than engineers might expect.

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One valuable insight from an analysis of that data is that, depending on the direction of the wind, it might be best to have the leading turbine run slower than engineers might expect. When the front turbine absorbs less energy, the ones behind it can operate at close to their optimal levels, increasing energy generation overall. This application shows that digital twin technology can be applied beyond a single product to holistically optimize an entire wind farm’s activity. According to GE, digital twins could increase wind-farm output by 20 percent and provide $100 million of value over the lifetime of a 100-megawatt wind farm.9 All three of these uses of Predix are freeing up human workers to do less routine work and more engaging work.

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In the case of the GE maintenance worker, you would need the ability to ask the machine smart questions across multiple levels of abstraction. We call this skill intelligent interrogation. As a maintenance worker using the GE’s digital twin, you would start your interrogation with the troubled rotor but quickly scale up, asking questions about operations, process, and financial concerns. You aren’t just a rotor expert; with the help of the digital twin, you’ve become an expert of a much more complex system; your knowledge of “how things work” has become ever more important. We describe each of the eight fusion skills to guide managers and workers in designing and developing a workforce capable of thriving in the missing middle (see figure 8-1).

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, Big Tech, bike sharing, blockchain, Brexit referendum, Build a better mousetrap, business cycle, business intelligence, business process, call centre, cloud computing, cognitive dissonance, connected car, data science, death of newspapers, digital nomad, digital rights, digital twin, double entry bookkeeping, Elon Musk, factory automation, fake news, fiat currency, Ford Model T, fulfillment center, growth hacking, hockey-stick growth, Internet of things, inventory management, iterative process, Jeff Bezos, John Zimmer (Lyft cofounder), Kevin Kelly, Lean Startup, Lyft, manufacturing employment, Marc Benioff, Mary Meeker, megaproject, minimum viable product, natural language processing, Network effects, Nicholas Carr, nuclear winter, pets.com, planned obsolescence, pneumatic tube, profit maximization, race to the bottom, ride hailing / ride sharing, Salesforce, Sand Hill Road, shareholder value, Silicon Valley, skunkworks, smart meter, social graph, software as a service, spice trade, Steve Ballmer, Steve Jobs, subscription business, systems thinking, tech worker, TED Talk, Tim Cook: Apple, transport as a service, Uber and Lyft, uber lyft, WeWork, Y2K, Zipcar

He pointed out that digital twins don’t just represent how their physical assets were designed or how they were built—they display how those assets are operating in real time. A jet engine that’s being operated in the US Southwest, for example, has a different digital twin from one that primarily flies across the North Sea. Over time, those engines behave and degrade in different ways, and they transmit usage data accordingly. Very soon, engineers on the ground will use augmented reality headsets to see all this information overlaid on the jet engines when they inspect them. The digital twins will point out wear and trouble spots and offer opinions on how to resolve issues based on asset history.

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Today . . . most of our factories look the same as they did 50 years ago. That’s all about to change. DIGITAL TWINS You may have grown up thinking of General Electric as a kitchen appliance company. Today they build wind turbines, jet engines, oil rigs. They also have a thriving data services business—maybe you’ve seen some of their commercials aimed at recruiting more developers. They have over $3 trillion in assets that they manage on a regular basis, and today almost all of them have twins—more specifically, digital twins. We recently hosted Gytis Barzdukas, vice president at General Electric Digital, at our Subscribed conference in San Francisco.

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So sensor retrofitting and networking, or the “implementation phase” of IoT, are set to become a huge growth industry in the years ahead. And what happens when you have a vast network of digital twins that represent every asset across your entire product line? Well, the first beneficiary was GE itself. What if you had one engine acting up, or one compressor behaving strangely, among thousands? Imagine that if instead of trying to catch problems with expensive and laborious mass maintenance procedures, you had a network of digital twins sending you relevant signals from individual assets. Well, you could fix the biggest problems much faster. GE quickly realized more than $200 million a year in savings, simply by improving their efficiency.

The Metaverse: And How It Will Revolutionize Everything by Matthew Ball

"hyperreality Baudrillard"~20 OR "Baudrillard hyperreality", 3D printing, Airbnb, Albert Einstein, Amazon Web Services, Apple Newton, augmented reality, Big Tech, bitcoin, blockchain, business process, call centre, cloud computing, commoditize, computer vision, COVID-19, cryptocurrency, deepfake, digital divide, digital twin, disintermediation, don't be evil, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, game design, gig economy, Google Chrome, Google Earth, Google Glasses, hype cycle, intermodal, Internet Archive, Internet of things, iterative process, Jeff Bezos, John Gruber, Kevin Roose, Kickstarter, lockdown, Mark Zuckerberg, Metcalfe’s law, Minecraft, minimum viable product, Neal Stephenson, Network effects, new economy, non-fungible token, open economy, openstreetmap, pattern recognition, peer-to-peer, peer-to-peer model, Planet Labs, pre–internet, QR code, recommendation engine, rent control, rent-seeking, ride hailing / ride sharing, Robinhood: mobile stock trading app, satellite internet, self-driving car, SETI@home, Silicon Valley, skeuomorphism, Skype, smart contracts, Snapchat, Snow Crash, social graph, social web, SpaceX Starlink, Steve Ballmer, Steve Jobs, thinkpad, TikTok, Tim Cook: Apple, TSMC, undersea cable, Vannevar Bush, vertical integration, Vitalik Buterin, Wayback Machine, Y2K

In recent years, the biggest uptick in virtual world creation has been via worlds which have no “gameplay” whatsoever. For example, a digital twin of the Hong Kong International Airport was created using the popular game engine Unity—the purpose of the twin was to simulate the flow of passengers, the implications of maintenance issues or runway backups, and other events that would impact airport design choices and operational decision-making. In other cases, entire cities have been re-created and then connected to real-time data feeds for vehicular traffic, weather, and other civic services, such as police, fire, ambulance response. The goal of such a digital twin is to enable city planners to better understand the cities they manage and make more informed decisions about zoning, construction approvals, and more.

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Satya Nadella, “Building the Platform for Platform Creators,” LinkedIn, May 25, 2021, accessed January 4, 2022 https://www.linkedin.com/pulse/building-platform-creators-satya-nadella. 2. Sam George, “Converging the Physical and Digital with Digital Twins, Mixed Reality, and Metaverse Apps,” Microsoft Azure, May 26, 2021, accessed January 4, 2022, https://azure.microsoft.com/en-ca/blog/converging-the-physical-and-digital-with-digital-twins-mixed-reality-and-metaverse-apps/. 3. Andy Chalk, “Microsoft Says It Has Metaverse Plans for Halo, Minecraft, and Other Games,” PC Gamer, November 2, 2021, accessed January 4, 2022, https://www.pcgamer.com/microsoft-says-it-has-metaverse-plans-for-halo-minecraft-and-other-games/. 4.

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In other cases, they might be limited to a single user, as when playing Legend of Zelda, or be shared with many others, as in Call of Duty. These users might affect and be affected by this virtual world through any number of devices, such as a keyboard, motion sensor, or even a camera that tracks their motion. Stylistically, virtual worlds can reproduce the “real world” exactly (these are often called a “digital twin”) or represent a fictionalized version of it (such as Super Mario Odyssey’s New Donk City, or the quarter-scale Manhattan of PlayStation’s 2018 game Marvel’s Spider-Man), or represent an altogether fictional reality in which the impossible is commonplace. The purpose of a virtual world can be “game-like,” which is to say there is an objective such as winning, killing, scoring, defeating, or solving, or the purpose can be “non-game-like” with objectives such as educational or vocational training, commerce, socializing, meditation, fitness, and more.

Supertall: How the World's Tallest Buildings Are Reshaping Our Cities and Our Lives by Stefan Al

3D printing, autonomous vehicles, biodiversity loss, British Empire, Buckminster Fuller, carbon footprint, Cesare Marchetti: Marchetti’s constant, colonial rule, computer vision, coronavirus, COVID-19, Deng Xiaoping, digital twin, Disneyland with the Death Penalty, Donald Trump, Easter island, Elisha Otis, energy transition, food miles, Ford Model T, gentrification, high net worth, Hyperloop, invention of air conditioning, Kickstarter, Lewis Mumford, Marchetti’s constant, megaproject, megastructure, Mercator projection, New Urbanism, plutocrats, plyscraper, pneumatic tube, ride hailing / ride sharing, Salesforce, self-driving car, Sidewalk Labs, SimCity, smart cities, smart grid, smart meter, social distancing, Steve Jobs, streetcar suburb, synthetic biology, Tacoma Narrows Bridge, the built environment, the High Line, transit-oriented development, Triangle Shirtwaist Factory, tulip mania, urban planning, urban sprawl, value engineering, Victor Gruen, VTOL, white flight, zoonotic diseases

While our future responsive building envelopes may require less cooling inside the building, it’s unlikely that air-conditioning systems will be going extinct anytime soon. Your old-fashioned air conditioner is undergoing fundamental changes, including getting a virtual avatar. Machine learning and “smart” devices have led to a technology called a “digital twin.” This is a virtual replica of a building, the bridge between the physical and the digital world. Intelligent control mechanisms can mine real-time data from sensors in the building, such as air quality and people’s activities. Artificial intelligence algorithms run thousands of simulations to test new air-conditioning settings or to uncover problems the real world can benefit from.

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In Barcelona, a system of pneumatic tubes runs below the streets to bring trash to an anaerobic digestion facility. These subways for trash more easily bring it to the facility. Then microorganisms break down the material into biogas, a renewable-energy source. As cities are getting more circular, more sophisticated systems will need to manage and share resources. In 2014, Singapore launched a digital twin, a virtual version of the city called “E3A,” “Everyone, Everything, Everywhere, All the Time.” It displays 3D renderings of all the city’s parks, buildings, and waterways, like the video game SimCity, based on real-time data such as energy use, pollution, and noise. The computer model can run virtual experiments and test policies before they are actually implemented.

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See also glass Debord, Guy, 171 de Botton, Alain, 164, 165–66 de Mestral, George, 82–83 Deng Xiaoping, 101 density, and human behavior, 228–29 de Portzamparc, Christian, 195 design computational methods, 9, 84 principles broken by super slenders, 178 structural efficiency and, 81–82 sustainable ratings of, 137 DeWitt Chestnut Apartments, Chicago, 61 digital twin, 140, 264 Diller Scofidio + Renfro, 201 domes, 27–28, 32, 56, 82, 130–31 Dubai, 3, 13, 36, 37. See also Burj Khalifa, Dubai Easter Island, 41, 207 Eastgate Centre, Zimbabwe, 140–41 economic growth, 12–13, 239 economic height, 188 Eiffel Tower, 6, 7, 88, 89, 145–46, 167, 169 electric lighting, 12, 115, 121, 133, 218 elevator cable, 108–9 elevator consultant, 97 elevator music, 95 elevator operators, 94–95, 107 elevators accidents with, 92, 94–95, 106–7 advances in, 5, 87, 99–100, 104–6, 107, 109–11 air pressure in, 106, 107–8 as an attraction, 97–99 in China, 85, 87, 101, 103, 107 COVID-related changes to, 210 energy consumption by, 109–10 Futurists’ vision for, 96–97 history of, 89–93 howling of, 95, 105, 106 human psychology and, 95–96 partial vacuum in shaft, 105–6 safety and, 11, 87–88, 91–92, 95, 106–7 on side of HSBC Building, 132 sideways, 110–11 speed of, 5, 87, 92, 93, 99, 100–101, 104, 107–8 stacked, 5, 99 of super slenders, 178 wind forces and, 104–5, 106 elevator-testing towers, 104–5, 110 Elzner, A.

Industry 4.0: The Industrial Internet of Things by Alasdair Gilchrist

3D printing, additive manufacturing, air gap, AlphaGo, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, business intelligence, business logic, business process, chief data officer, cloud computing, connected car, cyber-physical system, data science, deep learning, DeepMind, deindustrialization, DevOps, digital twin, fault tolerance, fulfillment center, 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, OSI model, pattern recognition, peer-to-peer, platform as a service, pre–internet, race to the bottom, RFID, Salesforce, Skype, smart cities, smart grid, smart meter, smart transportation, software as a service, stealth mode startup, supply-chain management, The future is already here, trade route, undersea cable, vertical integration, warehouse robotics, web application, WebRTC, Y2K

Again, in this scenario Rolls Royce uses thousands of sensors to monitor the engines every second of their working life, building up huge amounts of predictive data, so that it knows when a component’s service is degrading. By collecting and storing all those vast quantities of data, Rolls Royce can create a “digital twin” of the physical engine. Both the digital and its physical twin are virtual clones so engineers don’t have to open the engine to service components that are subsequently found to be fine, they know that already without touching or taking the engine out of service. This concept of the “digital twin” is very important in manufacturing and in the Industrial Internet as it allows Big Data analytics to determine recommendations that can be tested on a virtual twin machine and then processed before being put into production.

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Creators of these robots are designing them to be self-sufficient, autonomous, and interactive, so that they are no longer simply tools used by humans, but they are already integral work units that function alongside humans. Simulation Previously, if manufacturers wanted to test if a process was working efficiently and effectively, trial and error was required. Industry 4.0 uses virtualization to create digital twins that are used for simulation modeling and testing and they will play more major roles in the optimization of production, as well as product quality. Horizontal and Vertical System Integration Having fully integrated OT and IT systems is something that Industry 4.0 aims for. The goal is to create a scenario where engineering, production, marketing, and after-sales are closely linked.

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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.

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Apollo 11, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, Big Tech, bioinformatics, blockchain, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, Computing Machinery and Intelligence, conceptual framework, creative destruction, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, data science, David Brooks, deep learning, DeepMind, Demis Hassabis, digital twin, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, fake news, fault tolerance, gamification, general purpose technology, Geoffrey Hinton, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, machine translation, Mark Zuckerberg, medical residency, meta-analysis, microbiome, move 37, natural language processing, new economy, Nicholas Carr, Nick Bostrom, nudge unit, OpenAI, opioid epidemic / opioid crisis, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, post-truth, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Skinner box, speech recognition, Stephen Hawking, techlash, TED Talk, text mining, the scientific method, Tim Cook: Apple, traumatic brain injury, trolley problem, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

With their cloud-based platform, cluster computing, natural-language processing, and AI capabilities, there was the infrastructure to build “the world’s largest library of molecular and clinical data and an operating system to make that data accessible and useful.”46 Tempus Labs, now collaborating with more than forty of the National Cancer Institute centers in the United States, performs a range of studies, including the list above from sequencing to culturing. Beyond the extensive assessment of the patient, Tempus provides “digital twin” information with their report generated two to three weeks after samples are received. This consists of treatment and outcomes information from the de-identified patients most similar with respect to demographics and biologic information. That, too, employs an AI advanced analytic method of nearest neighbor analysis.

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It would compensate for the fact that most biomedical research performed to date has been done with subjects of European ancestry, which means that physicians often cannot extrapolate their findings to individuals of other ancestries. If all members of the species had comprehensive data in such a resource, with their treatments and outcomes, this would enable AI nearest neighbor analysis to find “digital twins.” These are individuals who most resemble, by all demographic, biologic, physiologic, and anatomic criteria, the person at risk or with a new important diagnosis. Knowledge of outcomes from twins would enable better prevention or treatment of the individual and the next generation. The likelihood of assembling such a resource for the world’s population is very low, especially impaired by concerns over privacy, data security, and cross-cultural sharing considerations.

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It’s a think-big scenario to imagine what awaits us in the longer term for all medical conditions without geographic boundaries. But even if the odds are low now, I hope recognition of the possibilities will help make those odds better. As soon as patient outcomes are shown to be unequivocally improved by having digital twins inform best treatment, it is likely there will be substantial commitments across health systems to develop and prioritize such infrastructure. With this review of the opportunities at the level of healthcare systems, it’s time to turn upstream—to the discovery side of drugs and the science that leads to better treatments and mechanistic insights about health and disease.

The Fourth Industrial Revolution by Klaus Schwab

"World Economic Forum" Davos, 3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Anthropocene, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, circular economy, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, CRISPR, cross-border payments, crowdsourcing, digital divide, digital twin, disintermediation, disruptive innovation, distributed ledger, driverless car, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, hype cycle, 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, Marc Benioff, mass immigration, megacity, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, nuclear taboo, OpenAI, 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, social contagion, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, synthetic biology, 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!, Wayback Machine, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

Positive impacts – Increased efficiency in using resources – Rise in productivity – Improved quality of life – Effect on the environment – Lower cost of delivering services – More transparency around the use and state of resources – Safety (e.g. planes, food) – Efficiency (logistics) – More demand for storage and bandwidth – Shift in labour markets and skills – Creation of new businesses – Even hard, real-time applications feasible in standard communication networks – Design of products to be “digitally connectable” – Addition of digital services on top of products – Digital twin provides precise data for monitoring, controlling and predicting – Digital twin becomes active participant in business, information and social processes – Things will be enabled to perceive their environment comprehensively, and react and act autonomously – Generation of additional knowledge, and value based on connected “smart” things Negative impacts – Privacy – Job losses for unskilled labour – Hacking, security threat (e.g. utility grid) – More complexity and loss of control Unknown, or cuts both ways – Shift in business model: asset rental/usage, not ownership (appliances as a service) – Business model impacted by the value of the data – Every company potentially a software company – New businesses: selling data – Change in frameworks to think about privacy – Massively distributed infrastructure for information technologies – Automation of knowledge work (e.g. analyses, assessments, diagnoses) – Consequences of a potential “digital Pearl Harbor” (i.e. digital hackers or terrorists paralysing infrastructure, leading to no food, fuel and power for weeks) – Higher utilization rates (e.g. cars, machines, tools, equipment, infrastructure) The shift in action The Ford GT has 10 million lines of computer code in it.

Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, backpropagation, behavioural economics, Big Tech, bike sharing, bitcoin, business intelligence, business logic, business process, chief data officer, circular economy, clean tech, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, congestion pricing, continuous integration, crowdsourcing, data is the new oil, data science, deep learning, digital rights, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, hydroponic farming, income inequality, information security, Infrastructure as a Service, Internet of things, Large Hadron Collider, Masdar, microservices, Minecraft, OSI model, platform as a service, pneumatic tube, ransomware, RFID, ride hailing / ride sharing, risk tolerance, Salesforce, 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

Methods for communicating with devices When a device has been connected to a central platform or solution, we usually operate with a central representation of that device. This is called a digital twin or a digital shadow depending on vendor. The idea is that the centralized system keeps track of the device’s current state and its target state. This is the way that devices are typically managed. Consider a signal that can take the values of red, yellow, and green. The digital shadow may report that it is currently green. A central solution may wish it to be red and set the digital twin target state to red. This is then sent to the device which updates the signal to red. The central solution has to exchange data with the device in order for this to happen.

Data Action: Using Data for Public Good by Sarah Williams

affirmative action, Amazon Mechanical Turk, Andrei Shleifer, augmented reality, autonomous vehicles, Brexit referendum, Cambridge Analytica, Charles Babbage, City Beautiful movement, commoditize, coronavirus, COVID-19, crowdsourcing, data acquisition, data is the new oil, data philanthropy, data science, digital divide, digital twin, Donald Trump, driverless car, Edward Glaeser, fake news, four colour theorem, global village, Google Earth, informal economy, Internet of things, Jane Jacobs, John Snow's cholera map, Kibera, Lewis Mumford, Marshall McLuhan, mass immigration, mass incarceration, megacity, military-industrial complex, Minecraft, neoliberal agenda, New Urbanism, Norbert Wiener, nowcasting, oil shale / tar sands, openstreetmap, place-making, precautionary principle, RAND corporation, ride hailing / ride sharing, selection bias, self-driving car, sentiment analysis, Sidewalk Labs, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Steven Levy, the built environment, The Chicago School, The Death and Life of Great American Cities, transatlantic slave trade, Uber for X, upwardly mobile, urban planning, urban renewal, W. E. B. Du Bois, Works Progress Administration

A single Waymo test vehicle scans the environment with LIDAR sensors producing about 30 terabytes of data per day—that's three thousand times the amount of data that Twitter produces daily.6 Programmers at Google use this data to construct 3D representations of the physical world, often referred to as digital twins, which are used to guide autonomous vehicles on the road. In this virtual environment, autonomous vehicles—or any robot for that matter—can be guided and instructed to turn, to stop and pick up a passenger, or to come to a halt for a pedestrian to cross the street. Now imagine that this data is combined with all the data Google stores about you—what purchases you have made online, where you work, the last concert you went to, the locations of your upcoming vacation, even your political views.

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See also Data analytics; Data analytics ix, xix–xx, 47 “Chicago School” of sociology and 22 interrogating purpose of 214–215 limitations of 166 power dynamics and 199 public health and 10–13 qualitative analytics 39–42 uses of xii Data Canvas: Sense Your City (art project) 85–86 Data collaborations 85–87 Data collection 51–89 crosschecking and correcting the record 68–71 during disasters 80–83 DIY 56–59 governments and 78–79 participatory 52–56 projects 217 Data colonialism xviii, 191–193 Data Deprivation: Another Deprivation to End (World Bank report) 188 Data ethics 131–133, 206 Hacker Code of Ethics 89–90, 135 using data found on the web 90–94 Data exhaust 130 Data for Development (D4D) Challenge 208 Data for Good Bloomberg Fellow 207 Data for Good Exchange 210 Data insights communicating 137–186 public 219–220 DataKind 207 Data licensing 207–208 Data literacy 85–87, 168 data collaborations and 85–87 Local Lotto module 173 Data modeling, cities and 214 Data philanthropy 208–210 Data Pop Alliance (DPA) 210 Data practices, unjust xiii Data privacy xix, 135, 187–188, 194, 196–199, 221 Data Protections Direction 198 Data scientists, contemporary 166 Data sharing 137–186, 204–205 benefits of 143–146 insights of xvii public transport data for Nairobi 146–155 through visuals xvii–xviii when benefits are mutual 200–203 Data-sharing agreements, developing 204, 206–208 Data visualization 138–139, 183–184 comparing stop-and-frisk by race 183 interactive 218 measuring and 61, 62–64, 66 De Blasio, Bill 178 Deepwater Horizon oil spill 2019, 69, 217 Defense Advanced Research Products Agency (DARPA) 193 Democratic Party 5 Department of Health and Mental Hygiene, New York City, air quality initiative 78–79, 79, 85 Department of Sanitation in New York City (DSNY) 127–128, 128 Descriptive Map of London Poverty 17 “Design and the Elastic Mind” exhibit, Museum of Modern Art 162, 162, 163 Dianping 98–99, 103, 113, 134 Digital Ethics Lab, Oxford 210 Digital humanitarianism 131–133 Digital Humanitarian Network 82 Digital Matatus project, Nairobi, Kenya 77, 146, 151, 151–152, 154–155, 157, 183, 216 Digital Neighborhoods research project 126–127, 128–129 Digital twins 189 Disabled people, digital tools for 190–191 Doctors Without Borders 80 Domesday Book 2, 3 Do no harm 220–221 Dosemagen, Shannon 70–71 Du Bois, W. E. B. 22, 24, 30, 43 African American owned businesses in the US (chart) 25 Income and Expenditure of150 Negro Families in Atlanta, GA (chart) 24 The Philadelphia Negro 22, 24 Eagle, Charles W. 8 Easy Taxi 204 Ebola outbreak, West Africa 80, 81, 198, 208–209 Economist magazine, “Data Deluge” stories 47 Edney, Matthew 155 Electronic colonialism 192–193 EmoLex 124 England's Regulated Slave Trade Act of 1788, 140 Environmental Protection Agency (EPA) xv, 53, 68 Erle, Schuyler 83 Ethics 131–133, 206 data and xviii, 54, 198–199 Hacker Code of Ethics 89–90, 135 hacking and 89–90, 132–135 surveys and xii European Union, data protection in xix, 187–188, 194, 198–199, 221.

AI 2041 by Kai-Fu Lee, Chen Qiufan

3D printing, Abraham Maslow, active measures, airport security, Albert Einstein, AlphaGo, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, blue-collar work, Cambridge Analytica, carbon footprint, Charles Babbage, computer vision, contact tracing, coronavirus, corporate governance, corporate social responsibility, COVID-19, CRISPR, cryptocurrency, DALL-E, data science, deep learning, deepfake, DeepMind, delayed gratification, dematerialisation, digital map, digital rights, digital twin, Elon Musk, fake news, fault tolerance, future of work, Future Shock, game design, general purpose technology, global pandemic, Google Glasses, Google X / Alphabet X, GPT-3, happiness index / gross national happiness, hedonic treadmill, hiring and firing, Hyperloop, information security, Internet of things, iterative process, job automation, language acquisition, low earth orbit, Lyft, Maslow's hierarchy, mass immigration, mirror neurons, money: store of value / unit of account / medium of exchange, mutually assured destruction, natural language processing, Neil Armstrong, Nelson Mandela, OpenAI, optical character recognition, pattern recognition, plutocrats, post scarcity, profit motive, QR code, quantitative easing, Richard Feynman, ride hailing / ride sharing, robotic process automation, Satoshi Nakamoto, self-driving car, seminal paper, Silicon Valley, smart cities, smart contracts, smart transportation, Snapchat, social distancing, speech recognition, Stephen Hawking, synthetic biology, telemarketer, Tesla Model S, The future is already here, trolley problem, Turing test, uber lyft, universal basic income, warehouse automation, warehouse robotics, zero-sum game

The treadmill can be tilted to simulate hills or stairs. This allows essentially any movement without the danger of falling. With these capabilities in mind, I project that the most likely application will be entertainment related, for example, hyper-realistic games where our digital twins will play games, compete, and battle with other people’s digital twins in athletic competitions and battle simulations. Users could also interact with and spar with purely synthesized beings (like Hiroshi in “My Haunting Idol”). With such experiences at our disposal, humans by 2041 may increasingly live in multiple worlds, one real, some virtual, and others a mix of the two.

The Price of Tomorrow: Why Deflation Is the Key to an Abundant Future by Jeff Booth

3D printing, Abraham Maslow, activist fund / activist shareholder / activist investor, additive manufacturing, AI winter, Airbnb, Albert Einstein, AlphaGo, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, Bretton Woods, business intelligence, butterfly effect, Charles Babbage, Claude Shannon: information theory, clean water, cloud computing, cognitive bias, collapse of Lehman Brothers, Computing Machinery and Intelligence, corporate raider, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, currency manipulation / currency intervention, dark matter, deep learning, DeepMind, deliberate practice, digital twin, distributed ledger, Donald Trump, Elon Musk, fiat currency, Filter Bubble, financial engineering, full employment, future of work, game design, gamification, general purpose technology, Geoffrey Hinton, Gordon Gekko, Great Leap Forward, Hyman Minsky, hype cycle, income inequality, inflation targeting, information asymmetry, invention of movable type, Isaac Newton, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, John von Neumann, Joseph Schumpeter, late fees, low interest rates, Lyft, Maslow's hierarchy, Milgram experiment, Minsky moment, Modern Monetary Theory, moral hazard, Nelson Mandela, Network effects, Nick Bostrom, oil shock, OpenAI, pattern recognition, Ponzi scheme, quantitative easing, race to the bottom, ride hailing / ride sharing, self-driving car, software as a service, technoutopianism, TED Talk, the long tail, the scientific method, Thomas Bayes, Turing test, Uber and Lyft, uber lyft, universal basic income, winner-take-all economy, X Prize, zero-sum game

Virtual and augmented reality (mixed reality) will offer a different, more immersive connection with our technology, and it will change the way many things are done. Take, for example, a startup in Vancouver called LlamaZOO, which is in a new category of data collection called spatial data that is at the intersection of digital twinning (an exact twin of the physical world that is digital), mixed reality, and business intelligence. By twinning the real world via satellite imagery, drones, and lidar, and adding global positioning, mapping, and other data streams, the company uses mixed reality to reduce the cost of planning and work in the physical world.

Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage by Douglas B. Laney

3D printing, Affordable Care Act / Obamacare, banking crisis, behavioural economics, blockchain, book value, business climate, business intelligence, business logic, business process, call centre, carbon credits, chief data officer, Claude Shannon: information theory, commoditize, conceptual framework, crowdsourcing, dark matter, data acquisition, data science, deep learning, digital rights, digital twin, discounted cash flows, disintermediation, diversification, en.wikipedia.org, endowment effect, Erik Brynjolfsson, full employment, hype cycle, informal economy, information security, intangible asset, Internet of things, it's over 9,000, linked data, Lyft, Nash equilibrium, Neil Armstrong, Network effects, new economy, obamacare, performance metric, profit motive, recommendation engine, RFID, Salesforce, semantic web, single source of truth, smart meter, Snapchat, software as a service, source of truth, supply-chain management, tacit knowledge, technological determinism, text mining, uber lyft, Y2K, yield curve

The rise of the machines, algorithmic sprawl, and the promise of artificial intelligence (AI) depend upon accurate, complete, timely, granular, and unique information sources. The internet of things (IoT) will become the single fastest growing source and most voracious consumer of information. Digital twins that precisely represent models of physical things and their state rely on a variety of metadata, along with condition and event information. 3D printing is entirely contingent upon information-based representations of objects, and their ability to be monetized and managed effectively. The institutionalization of ethics in the face of commercialized and politicized misinformation will require the generation and management of new information sources to emerge with built-in trust indicators.

The Science and Technology of Growing Young: An Insider's Guide to the Breakthroughs That Will Dramatically Extend Our Lifespan . . . And What You Can Do Right Now by Sergey Young

23andMe, 3D printing, Albert Einstein, artificial general intelligence, augmented reality, basic income, Big Tech, bioinformatics, Biosphere 2, brain emulation, caloric restriction, caloric restriction, Charles Lindbergh, classic study, clean water, cloud computing, cognitive bias, computer vision, coronavirus, COVID-19, CRISPR, deep learning, digital twin, diversified portfolio, Doomsday Clock, double helix, Easter island, Elon Musk, en.wikipedia.org, epigenetics, European colonialism, game design, Gavin Belson, George Floyd, global pandemic, hockey-stick growth, impulse control, Internet of things, late capitalism, Law of Accelerating Returns, life extension, lockdown, Lyft, Mark Zuckerberg, meta-analysis, microbiome, microdosing, moral hazard, mouse model, natural language processing, personalized medicine, plant based meat, precision agriculture, radical life extension, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, ride hailing / ride sharing, Ronald Reagan, self-driving car, seminal paper, Silicon Valley, stem cell, Steve Jobs, tech billionaire, TED Talk, uber lyft, ultra-processed food, universal basic income, Virgin Galactic, Vision Fund, X Prize

If our consciousness can really be boiled down to ones and zeros (or the fuzzier calculation models used in quantum computing), then how will we distinguish the difference between you and a perfect computer emulation of you? “Presuming that you are wildly successful with this,” I asked Anders, “what subjective awareness do you think that our digital twins will have? Will this emulation truly be you for all intents and purposes? Or will it be just a lifeless simulation?” “I believe an emulated person would actually be a person, with a consciousness and emotion,” said Anders. “We should treat it as a person and give it human rights. But will brain emulations be a perfect continuation of your personal identity?

Merchants of Truth: The Business of News and the Fight for Facts by Jill Abramson

"World Economic Forum" Davos, 23andMe, 4chan, Affordable Care Act / Obamacare, Alexander Shulgin, Apple's 1984 Super Bowl advert, barriers to entry, Bernie Madoff, Bernie Sanders, Big Tech, Black Lives Matter, Cambridge Analytica, Charles Lindbergh, Charlie Hebdo massacre, Chelsea Manning, citizen journalism, cloud computing, commoditize, content marketing, corporate governance, creative destruction, crowdsourcing, data science, death of newspapers, digital twin, diversified portfolio, Donald Trump, East Village, Edward Snowden, fake news, Ferguson, Missouri, Filter Bubble, future of journalism, glass ceiling, Google Glasses, haute couture, hive mind, income inequality, information asymmetry, invisible hand, Jeff Bezos, Joseph Schumpeter, Khyber Pass, late capitalism, Laura Poitras, Marc Andreessen, Mark Zuckerberg, move fast and break things, Nate Silver, new economy, obamacare, Occupy movement, Paris climate accords, performance metric, Peter Thiel, phenotype, pre–internet, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Saturday Night Live, self-driving car, sentiment analysis, Sheryl Sandberg, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, skunkworks, Snapchat, social contagion, social intelligence, social web, SoftBank, Steve Bannon, Steve Jobs, Steven Levy, tech billionaire, technoutopianism, telemarketer, the scientific method, The Wisdom of Crowds, Tim Cook: Apple, too big to fail, vertical integration, WeWork, WikiLeaks, work culture , Yochai Benkler, you are the product

While the print journalists worked at the paper’s headquarters near the White House, which was made famous in the movie All the President’s Men, “the web people” worked a good distance away, across the Potomac River, in Virginia. The print team didn’t trust the people working on the web to have the same values that Bradlee and Downie had inculcated in the newsroom on 15th Street. Graham thought the culture of the main newsroom would suffocate its digital twin. He also liked that Virginia was a nonunion state. Its storied history and strong local ties did little to save the Post from the inexorable decade of decline that began in 2002. The internet had changed people’s reading habits, and circulation of the printed paper fell by nearly half. Ad revenue plummeted too, as local department stores and businesses of all kinds closed.

…

It was the digital cousin of the old theory of salesmanship, “The customer is always right.” Even in 2011 the digital operations at most of the major news outlets amounted to a website that was only marginally sleeker than it had been more than a decade prior. News websites were still designed to be digital twins of newspapers. For Smith, this presented an enormous business opportunity. “I feel in general the 800–1,200 word form of the news article is broken,” he said in a Nieman Lab interview. The basis for that conclusion: “You don’t see people sharing those kinds of stories.” BuzzFeed’s stated goal was “reinventing the wire story for the social web.”

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, AlphaGo, Amazon Mechanical Turk, Amazon Robotics, augmented reality, autonomous vehicles, barriers to entry, Big Tech, biodiversity loss, bitcoin, blockchain, blood diamond, Boston Dynamics, Burning Man, call centre, cashless society, Charles Babbage, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, CRISPR, crowdsourcing, cryptocurrency, data science, Dean Kamen, deep learning, deepfake, DeepMind, delayed gratification, dematerialisation, digital twin, disruptive innovation, Donald Shoup, driverless car, Easter island, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, fake news, food miles, Ford Model T, fulfillment center, game design, Geoffrey West, Santa Fe Institute, gig economy, gigafactory, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, impact investing, indoor plumbing, industrial robot, informal economy, initial coin offering, intentional community, 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, Kiva Systems, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, Masayoshi Son, mass immigration, megacity, meta-analysis, microbiome, microdosing, mobile money, multiplanetary species, Narrative Science, natural language processing, Neal Stephenson, Neil Armstrong, Network effects, new economy, New Urbanism, Nick Bostrom, Oculus Rift, One Laptop per Child (OLPC), out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, planned obsolescence, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, robo advisor, Satoshi Nakamoto, Second Machine Age, self-driving car, Sidewalk Labs, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, SoftBank, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, tech billionaire, technoutopianism, TED Talk, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Vision Fund, VTOL, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

Your comments become commands: “I’d love some black pumps to match my new dress” makes racks of perfectly fitting shoes appear. Yet none of these shoes seem exactly right. “How would this dress look with those satin Jimmy Choos sitting in your closet?” asks your friend. No problem. Every piece of physical clothing you own in the real world has a digital twin available in the virtual. You ask, and instantly, you’re wearing them. When you’re done selecting your outfit, the AI pays the bill. While your new clothes are being 3-D printed at a warehouse—before speeding your way via drone delivery—a digital version has been added to your personal inventory for use at future virtual events.

New Laws of Robotics: Defending Human Expertise in the Age of AI by Frank Pasquale

affirmative action, Affordable Care Act / Obamacare, Airbnb, algorithmic bias, Amazon Mechanical Turk, Anthropocene, augmented reality, Automated Insights, autonomous vehicles, basic income, battle of ideas, Bernie Sanders, Big Tech, Bill Joy: nanobots, bitcoin, blockchain, Brexit referendum, call centre, Cambridge Analytica, carbon tax, citizen journalism, Clayton Christensen, collective bargaining, commoditize, computer vision, conceptual framework, contact tracing, coronavirus, corporate social responsibility, correlation does not imply causation, COVID-19, critical race theory, cryptocurrency, data is the new oil, data science, decarbonisation, deep learning, deepfake, deskilling, digital divide, digital twin, disinformation, disruptive innovation, don't be evil, Donald Trump, Douglas Engelbart, driverless car, effective altruism, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fake news, Filter Bubble, finite state, Flash crash, future of work, gamification, general purpose technology, Google Chrome, Google Glasses, Great Leap Forward, green new deal, guns versus butter model, Hans Moravec, high net worth, hiring and firing, holacracy, Ian Bogost, independent contractor, informal economy, information asymmetry, information retrieval, interchangeable parts, invisible hand, James Bridle, Jaron Lanier, job automation, John Markoff, Joi Ito, Khan Academy, knowledge economy, late capitalism, lockdown, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, medical malpractice, megaproject, meta-analysis, military-industrial complex, Modern Monetary Theory, Money creation, move fast and break things, mutually assured destruction, natural language processing, new economy, Nicholas Carr, Nick Bostrom, Norbert Wiener, nuclear winter, obamacare, One Laptop per Child (OLPC), open immigration, OpenAI, opioid epidemic / opioid crisis, paperclip maximiser, paradox of thrift, pattern recognition, payday loans, personalized medicine, Peter Singer: altruism, Philip Mirowski, pink-collar, plutocrats, post-truth, pre–internet, profit motive, public intellectual, QR code, quantitative easing, race to the bottom, RAND corporation, Ray Kurzweil, recommendation engine, regulatory arbitrage, Robert Shiller, Rodney Brooks, Ronald Reagan, self-driving car, sentiment analysis, Shoshana Zuboff, Silicon Valley, Singularitarianism, smart cities, smart contracts, software is eating the world, South China Sea, Steve Bannon, Strategic Defense Initiative, surveillance capitalism, Susan Wojcicki, tacit knowledge, TaskRabbit, technological solutionism, technoutopianism, TED Talk, telepresence, telerobotics, The Future of Employment, The Turner Diaries, Therac-25, Thorstein Veblen, too big to fail, Turing test, universal basic income, unorthodox policies, wage slave, Watson beat the top human players on Jeopardy!, working poor, workplace surveillance , Works Progress Administration, zero day

A database may include labeled images of millions of different abnormalities that eventually became cancerous, as well as millions that did not. As we might search on Google for websites matching a query, a computer can rapidly compare images of your colon or skin with those in the database. Ideally, machines learn to spot “evil digital twins”—tissue that proved in the past to be dangerous, which is menacingly similar to your own.9 This machine vision—spotting danger where even experienced specialists might miss it—is far different from our own sense of sight. To understand machine learning—which will come up repeatedly in this book—it is helpful to compare contemporary computer vision to its prior successes in facial or number recognition.

Arriving Today: From Factory to Front Door -- Why Everything Has Changed About How and What We Buy by Christopher Mims

air freight, Airbnb, Amazon Robotics, Amazon Web Services, Apollo 11, augmented reality, autonomous vehicles, big-box store, blue-collar work, Boeing 747, book scanning, business logic, business process, call centre, cloud computing, company town, coronavirus, cotton gin, COVID-19, creative destruction, data science, Dava Sobel, deep learning, dematerialisation, deskilling, digital twin, Donald Trump, easy for humans, difficult for computers, electronic logging device, Elon Musk, Frederick Winslow Taylor, fulfillment center, gentrification, gig economy, global pandemic, global supply chain, guest worker program, Hans Moravec, heat death of the universe, hive mind, Hyperloop, immigration reform, income inequality, independent contractor, industrial robot, interchangeable parts, intermodal, inventory management, Jacquard loom, Jeff Bezos, Jessica Bruder, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kaizen: continuous improvement, Kanban, Kiva Systems, level 1 cache, Lewis Mumford, lockdown, lone genius, Lyft, machine readable, Malacca Straits, Mark Zuckerberg, market bubble, minimum wage unemployment, Nomadland, Ocado, operation paperclip, Panamax, Pearl River Delta, planetary scale, pneumatic tube, polynesian navigation, post-Panamax, random stow, ride hailing / ride sharing, robot derives from the Czech word robota Czech, meaning slave, Rodney Brooks, rubber-tired gantry crane, scientific management, self-driving car, sensor fusion, Shenzhen special economic zone , Shoshana Zuboff, Silicon Valley, six sigma, skunkworks, social distancing, South China Sea, special economic zone, spinning jenny, standardized shipping container, Steve Jobs, supply-chain management, surveillance capitalism, TED Talk, the scientific method, Tim Cook: Apple, Toyota Production System, traveling salesman, Turing test, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, vertical integration, warehouse automation, warehouse robotics, workplace surveillance

This simplified, averaged, and partly inferred simulation of the outside world—a blend of what’s sensed in this instant with things remembered from a past encoded in the system’s detailed, 3D map of the world—is an essential buffer between the part of the machine that makes decisions and the parts of the machine that sense what’s going on in and around the truck. On the surface, at least, the virtual world presented to the truck’s AI has remarkable parallels with what goes on in your head. One reason this “digital twin” of the world outside is so important is that it allows the truck’s AI to interact with a relatively stable and highly accurate version of reality, with almost all the errors, which are inevitable in individual sensors, filtered out. The human brain does something similar, and what happens when this function of our minds breaks down is telling.