cloud computing

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pages: 525 words: 142,027

CIOs at Work by Ed Yourdon


8-hour work day, Apple's 1984 Super Bowl advert, business intelligence, business process, call centre, cloud computing, crowdsourcing, distributed generation, Flash crash, Googley, Grace Hopper, Infrastructure as a Service, Innovator's Dilemma, inventory management, Julian Assange, knowledge worker, Mark Zuckerberg, Nicholas Carr, rolodex, shareholder value, Silicon Valley, six sigma, Skype, smart grid, smart meter, software as a service, Steve Ballmer, Steve Jobs, Steven Levy, the scientific method, WikiLeaks, Y2K, Zipcar

Are you spending a lot of time worrying and thinking about things like virtualization and cloud computing and so forth? Strassmann: Oh absolutely. Yourdon: Or are there, if you’re looking further into the future, are there other things? Strassmann: Yes. By the way, my course, that I’m starting … has 13 lectures. And they are three-hour lectures, and two of those lectures are on virtualization and cloud computing. Yourdon: Okay, well, that obviously gives it some great significance. Strassmann: And the significance is really driven by the economics, the shifting economics of how do you equip an enterprise with information technology that’s long-lasting? And so you have to go towards cloud computing. Yourdon: The less exotic sort of form or sister of that is the virtualization approach, which also seems like a clear-cut economic issue for any large organization.

So those technologies are big ones in terms of your vision of the future. What I see of virtualization is that it’s no longer a leading-edge or early adopter stuff. It’s becoming mainstream. Strassmann: Yes, it is. Yourdon: Cloud computing is a little further out. Strassmann: Well, it depends. You know, I have a list of cloud computing companies. I don’t know if you’ve looked at the list. They’re global now. I looked at companies that provide servers that have over 100,000 servers in one building. Yourdon: Wow. Strassmann: So a huge amount of business is now being channeled to cloud computing. One of the intriguing things is that many of the startups are experiments—in other words, if you are in a given corporation, and you want to experiment with something, and they don’t want to let it into the protected area, you just go out to Amazon and you buy yourself a server, for 25 cents a minute.

And our sweet spot is certainly central to where most IT organizations are, and I think that’s a part of it as well. Yourdon: I’ve obviously been following many of the things that Microsoft has been doing in the marketplace, and I would imagine you can just give me a general answer on a lot of these topical issues, like cloud computing and so on, you’ve got or Microsoft has got white papers or position papers. Do those tend to come from your group or are they influenced by your group? Scott: Well, it is really collaboration. Just like the dogfooding and things I was describing earlier. For example, cloud computing group, we have played a key role in helping shape the product from an architecture perspective and from the perspective of, “here is what CIOs are going to look for in terms of capability, and manageability, and how they think about the business case for the cloud and so on.”


pages: 307 words: 17,123

Behind the cloud: the untold story of how went from idea to billion-dollar company--and revolutionized an industry by Marc Benioff, Carlye Adler


Albert Einstein, Apple's 1984 Super Bowl advert, barriers to entry, Bay Area Rapid Transit, business continuity plan, call centre, carbon footprint, Clayton Christensen, cloud computing, corporate social responsibility, crowdsourcing, iterative process, Maui Hawaii, Nicholas Carr, platform as a service, Silicon Valley, software as a service, Steve Ballmer, Steve Jobs

Because offers employees an opportunity to make a difference, not just earn a paycheck, it’s known as one of the best places to work. Its original application has become the number-one hosted CRM service, and the company has established itself as the leader in the Software-as-a-Service (SaaS) industry it pioneered. And, through relentless focus, creativity, and passion, inspired an enterprise cloud computing industry. In short, the new and unconventional ideas that has evangelized have changed the way we do business and changed the world. There has been a profound shift toward cloud computing in the past few years. Nearly every major public and private cloud is powered by Dell, and we are ecstatic to be running today’s most exciting companies, including, Facebook, Microsoft, and many others. What motivates me most about this new way of computing is its potential for mass innovation.

For me, launching was a way to respond to new directions and new opportunities that I could not pursue from inside an established corporation. It was a license to do things differently. From the very beginning, set out to build a new technology model (on-demand, or delivered over the Internet—now called cloud computing), a new sales model (subscription based), and a new philanthropic model (integrated into the corporation). Ten years later, we had succeeded on all of these fronts. We also had surpassed my expectations by creating the first $1 billion cloud computing company and spawning a new $46 billion industry, of which we are the market leader. Read on to learn how we became one of the world’s fastest-growing software companies and about the tremendous fun we’ve had along the way. You’ll travel with us as we have our big entrepreneurial epiphany, as we turn a simple idea into a start-up company, and as we develop innovative technology and sell it through unconventional strategies.

Today, more than ever before, companies do not need to build technology from scratch; you can build on Internet-based platforms and tap into distribution centers, data centers, and unlimited computing power. The cloud computing model saves time and capital. All companies benefit when they can afford to focus on innovation rather than infrastructure. Consider Appirio, a software and services company that runs its entire business in the cloud. It has exploded from zero to one hundred fifty people in twenty-three states and in three countries in two-and-a-half years—and spent less than one-third of what a company of its size spends on IT. ‘‘Because of the cloud we were able to save money and be more innovative in how we work,’’ says cofounder and marketing chief Narinder 109 BEHIND THE CLOUD Singh. ‘‘We’re like a next-generation IBM without the baggage of hardware.’’ Play #56: Embrace Transparency and Build Trust One of the biggest issues for any cloud computing company is ensuring reliability of the service.


pages: 398 words: 86,855

Bad Data Handbook by Q. Ethan McCallum


Amazon Mechanical Turk, asset allocation, barriers to entry, Benoit Mandelbrot, business intelligence, cellular automata, chief data officer, cloud computing, cognitive dissonance, combinatorial explosion, conceptual framework, database schema,, Firefox, Flash crash, Gini coefficient, illegal immigration, iterative process, labor-force participation, loose coupling, natural language processing, Netflix Prize, quantitative trading / quantitative finance, recommendation engine, sentiment analysis, statistical model, supply-chain management, text mining, too big to fail, web application

Goldstein’s career retrospective explains how dirty data will give your classical statistics training a harsh reality check. Data Storage and Infrastructure How you store your data weighs heavily in how you can analyze it. Bobby Norton explains how to spot a graph data structure that’s trapped in a relational database in Crouching Table, Hidden Network (Chapter 13). Cloud computing’s scalability and flexibility make it an attractive choice for the demands of large-scale data analysis, but it’s not without its faults. In Myths of Cloud Computing (Chapter 14), Steve Francia dissects some of those assumptions so you don’t have to find out the hard way. We debate using relational databases over NoSQL products, Mongo over Couch, or one Hadoop-based storage over another. Tim McNamara’s When Databases Attack: A Guide for When to Stick to Files (Chapter 12) offers another, simpler option for storage.

Computer Networks and ISDN Systems 30: 107–117 Chapter 14. Myths of Cloud Computing Steve Francia Myths are an important and natural part of the emergence of any new technology, product, or idea as identified by the hype cycle. Like any myth, technology myths originate in a variety of ways, each revealing intriguing aspects of the human psyche. Some myths come from early adopters, whose naive excitement and need to defend their higher risk decision introduce hopeful, yet mistaken myths. Others come from vendors who, with eagerness, over-promise to their customers. By picking apart some of the more prominent myths surrounding the cloud, we gain better understanding of not only this technology, but hopefully the broader ability to discern truth from hype. Introduction to the Cloud In some ways, cloud computing myths are easily among the most pervasive of all technology myths.

For the purposes of this text, we will be using the term “the cloud” to refer to virtualized nodes on elastic demand as provided by vendors like Amazon’s EC2, Rackspace, Microsoft Azurel, Joyent, and more. Even with this somewhat restricting definition, there are significant differences between the different vendors. The Cloud and Big Data You may be wondering what cloud computing has to do with big data. A significant percentage of companies today are using cloud computing and that number is increasing daily. While some positions exist where a data scientist can leave things completely to an infrastructure team, in many jobs they may be responsible for the infrastructure. In a startup, it’s quite likely, at least to some degree. In all jobs, some knowledge and awareness of infrastructure strengths and best practices would benefit the diligent data scientist.


pages: 291 words: 77,596

Total Recall: How the E-Memory Revolution Will Change Everything by C. Gordon Bell, Jim Gemmell


airport security, Albert Einstein, book scanning, cloud computing, conceptual framework, full text search, information retrieval, invention of writing, inventory management, Isaac Newton, Menlo Park, optical character recognition, pattern recognition, performance metric, RAND corporation, RFID, semantic web, Silicon Valley, Skype, social web, statistical model, Stephen Hawking, Steve Ballmer, Ted Nelson, telepresence, Turing test, Vannevar Bush, web application

Here you can find references to printed publications, Web sites, people, products, conferences, and research labs. The section is arranged by chapter, and the order of material follows the order of the chapter as much as possible. 1. THE VISION Ray Ozzie is quoted from personal correspondence with the Authors. Other references on cloud computing: Hayes, B. 2008. “Cloud Computing.” ACM, Communications of the ACM 51, Issue 7 ( July). Gruman, Galen, and Eric Knorr. 2008. “What Cloud Computing Really Means. InfoWorld (April 7). Martin, Richard, and J. Nicholas Hoover. 2008. “Guide to Cloud Computing.” Information Week (June 21). Amazon Elastic Compute Cloud (Amazon EC2). Azure Services Platform. Science fiction that grapples with e-memories: Sawyer, Robert J. 2003. Hominids. New York: Macmillan.

See also files-and-folders organization; organization of data cell phones. See also smartphones and call logs and children and cloud computing and contact information and e-textbooks and electronic reminders and Gilmore and health data and lifelogging and memex as memory aid and miniaturization and physiological data and proactive health advisors and public surveillance and Total Recall technology CellScope cemeteries, digital Centers for Disease Control and Prevention Central Intelligence Agency (CIA) Chalmers, David chat chatbots Cheng, Allen children cholera cholesterol monitoring chronic illnesses classification of data. See also organization of data clothing cloud computing and CARPE and contact information and data storage described and Internet connection clutter. See also paperless environment coaching Cognitive Assistant that Learns and Organizes (CALO) cognitive computers cognitive impairment Cognitive Machines Cohen, Harold collaboration collections collective welfare command structures communism compact discs.

See also biometric sensors improvised explosive devices (IEDs) In Search of Memory: The Emergence of a New Scientific Mind (Kandel) indexing inductive charging industrial revolution Infinite Memory Multifunction Machine (IM3) Information Age inheritance instant messaging and cloud computing and cyber twins and note taking and smartphones and total data collection institutional memory instruction manuals insurance insurgency Intel Intellectual Ventures interfaces International Technology Roadmap for Semiconductors Internet. See also World Wide Web and cloud computing and data backup services and gossip and higher learning and implementation of Total Recall and information availability and the Millennial Generation and social values and unified communications inventory management IOgear iPhone Iraq War iTunes J Jaimes, Alexandro Jim Gray Endowed Chair in Computer Systems Joe Bill Jones, William JPEG files.


pages: 532 words: 139,706

Googled: The End of the World as We Know It by Ken Auletta


23andMe, AltaVista, Anne Wojcicki, Apple's 1984 Super Bowl advert, bioinformatics, Burning Man, carbon footprint, citizen journalism, Clayton Christensen, cloud computing, Colonization of Mars, corporate social responsibility, death of newspapers, disintermediation, don't be evil, facts on the ground, Firefox, Frank Gehry, Google Earth, hypertext link, Innovator's Dilemma, Internet Archive, invention of the telephone, Jeff Bezos, jimmy wales, Kevin Kelly, knowledge worker, Long Term Capital Management, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Network effects, new economy, Nicholas Carr, PageRank, Paul Buchheit, Peter Thiel, Ralph Waldo Emerson, Richard Feynman, Richard Feynman, Sand Hill Road, Saturday Night Live, semantic web, sharing economy, Silicon Valley, Skype, slashdot, social graph, spectrum auction, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, strikebreaker, telemarketer, the scientific method, The Wisdom of Crowds, Upton Sinclair, X Prize, yield management

Google also introduced other services: Gmail, Google News, Google Earth, Google Maps, Google Video, Picasa for sharing digital photographs, Google Books to search every book ever published, Orkut, a social network site, or additional “cloud computing” applications such as Desktop or Docs. By 2008, Mel Karmazin was no longer alone in questioning Google’s intentions. Nor were those intentions obscure. In the disclosure documents it filed with the SEC in 2008, Google declared, “We began as a technology company, and have evolved into a software, technology, internet, advertising and media company all rolled into one.” When Google adds mobile phones and a full menu of software applications to its cloud computing, and if it figures out a way to monetize YouTube, Eric Schmidt told me, he thinks it is conceivable that Google can become the first media company to generate one hundred billion dollars in revenues.

“First place, you’re not going to get there with small little advertising deals. You need these big initiatives ... the number one big one right in front of us is television. Big market, well monetized, easily automatable. Second one is ... mobile.” The third was “enterprise,” by which he meant web-based services—“cloud computing”—offering various software applications and IT services for corporate customers, organizations, and individual consumers. Brave words, but throughout 2008 Schmidt’s company made no money from its mobile or YouTube or cloud-computing efforts. Google did not let up. It was still talking to cable companies, Schmidt said, about partnering to target advertising for cable’s digital set-top boxes, and for Android to become the operating system for cable mobile phones—should cable decide to enter the thriving wireless market.

And if the cable companies let Google in the door and grant them access to its data, “you can never build an alternative because Google’s will always be that much more efficient.” Cloud computing was another new Google initiative. Like other corporate giants with massive data centers and servers—IBM, Amazon, Oracle—Google was intent on launching its “cloud” of servers. The cloud would allow a user to access data stored in the Google server from anywhere; it would reduce corporate costs because companies could outsource their data centers; and it would subvert more expensive boxed software sold by Microsoft and spur the development of inexpensive netbooks whose applications are stored in the cloud. Because all these software applications can function on a browser, escaping the dominance of Microsoft’s operating system, in the future, said Christophe Bisciglia, the twenty-eight-year-old chief of cloud computing, “The browser becomes the operating system.


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, 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 skilled workers, millennium bug, pattern recognition, 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, web application, WebRTC, WebSocket, Y2K

Along with SDN, network concepts fog can address outstanding issues with vehicular networks such as long latency, irregular connections, and 51 52 Chapter 3 |TheTechnical and Business Innovators of the Industrial Internet high packet loss by supplementing vehicle-vehicle communications with vehicle-infrastructure communication and ultimately unified control. • Fog computing addresses many of the severe problems cloud computing has with network latency and congestion over the Internet; however, it cannot completely replace cloud computing which will always have a place due to its ability to store Big Data and perform analytics on massive quantities of data. As Big Data analytics is a major part of the IIoT and then the cloud, computing will also remain highly relevant to the overall architecture. Big Data and Analytics Big Data describes data that is just too large to be managed by traditional databases and processing tools. These large data structures can be and usually are made up of a combination of structured and non-structured data from a variety of sources such as text, forms, web blogs, comments, video, photographs, telemetry, GPS trails, IM chats, news feeds, and so on.

Amazon’s vision of the cloud was on hyper-provisioning; in so much as they built massive data centers with hyper-capacity in order to meet their web-scale requirements. Amazon then took the business initiative to rent spare capacity to other businesses, in the form of leasing compute, and storage resources on an as-used basis. The cloud model has proved to be hugely successful. Microsoft and Google followed Amazon’s lead, as did several others such as IBM, HP, and Oracle. In essence, cloud computing is still following Amazon’s early pay-as-you-use formula, which makes cloud computing financially attractive to SMEs (small to medium enterprises), as the costs of running a data center and dedicated infrastructure both IT and networks can be crippling. Consequently, many cash-strapped businesses, for example start-ups, elected to move their development and application platforms to the cloud, as they only paid for the resources they used.

Therefore the question industrial business leaders often ask is, “why would connecting my M2M architecture to the Internet provide me with greater value?” What Is the Industrial Internet? To explain why businesses should adopt the Industrial Internet, we need to first consider what the IIoT actual is all about. The Industrial Internet provides a way to get better visibility and insight into the company’s operations and assets through integration of machine sensors, middleware, software, and backend cloud compute and storage systems. Therefore, it provides a method of transforming business operational processes by using as feedback the results gained from interrogating large data sets through advanced analytics. The business gains are achieved through operational efficiency gains and accelerated productivity, which results in reduced unplanned downtime and optimized efficiency, and thereby profits. Although the technologies and techniques used in existing machine-to-machine (M2M) technologies in today's industrial environments may look similar to the IIoT, the scale of operation is vastly different.


pages: 222 words: 54,506

One Click: Jeff Bezos and the Rise of by Richard L. Brandt


Amazon Web Services, automated trading system, big-box store, call centre, cloud computing, Dynabook, Elon Musk, inventory management, Jeff Bezos, Kevin Kelly, new economy, science of happiness, search inside the book, Silicon Valley, Silicon Valley startup, skunkworks, software patent, Steve Jobs, Stewart Brand, Tony Hsieh, Whole Earth Catalog, Y2K

About two years after the launch of Web services, Amazon boasted sixty-five thousand developers using the program and sending some ten million queries a day to Amazon’s servers.That’s a lot of new customers. Further, the offering began to look a lot like the phenomenon now known as cloud computing—tapping into a program sitting on a Web server somewhere rather than one sitting on your own desktop. Another company using the service, for example, Monsoon of Portland, Oregon, offered software that companies could use to tap into Amazon’s software to simplify their own inventory management. “Web 1.0 was making the Internet for people; Web 2.0 is making the Internet better for computers,” Bezos predicted in a speech at the Web 2.0 conference in San Francisco in 2004. Amazon became known as one of the most innovative companies in cloud computing. From its initial start in 2002, Amazon Web Services offerings just kept expanding. It can distribute content for other companies (such as Netflix) from its own computers and networks.

That’s less than 2 percent of overall sales. But it has higher profit margins than the retail businesses—up to 23 percent operating margins compared to 5 percent in the rest of the business. During the company’s shareholder meeting in May 2010, Bezos saved most of his ever-present enthusiasm for a discussion of cloud computing services. “It has the potential to be as big as our retail business,” he said. In his opinion, Amazon can do a better job than most competitors in the business. Cloud computing, he said, is “a very large area right now [and] it’s done in our opinion in a very inefficient way. Whenever something big is done inefficiently that creates an opportunity.” That’s an astounding claim, since Web Services provides less than 2 percent of revenues today. But Bezos is now on a 1999-style rush to build up the business and maintain an early lead advantage.

Netflix can’t afford (at least not yet) to buy all the computing power needed to load up films instantly and stream them to thousands of customers at any moment. So it rents computers from Amazon’s vast store at pennies per minute to handle the tasks, tapping into just as much computer power as it needs at any given moment. It’s all part of a surprising business from the online retailing company, called Amazon Web Services, which is part of a larger trend known as cloud computing. Services like this bring in half a billion dollars annually in revenues to Amazon. Buying companies is a relatively easy way for a stock-rich company to expand its business. But sometimes a great executive will stumble upon an unexpected new idea, or one of his employees may come up with something. The key is the ability to look beyond the current conventional wisdom and embrace a radical new idea.


pages: 257 words: 72,251

Nothing to Hide: The False Tradeoff Between Privacy and Security by Daniel J. Solove


Albert Einstein, cloud computing, Columbine, hindsight bias, illegal immigration, invention of the telephone, Marshall McLuhan, national security letter, security theater, the medium is the message, traffic fines, urban planning

Despite the fact only these companies have the information, and despite the fact that they don’t share it with anybody, you lack a reasonable expectation of privacy in the information according to the third party doctrine.3 Cloud Computing For quite a long time, we’ve been accustomed to having all our electronic documents and software stored on our own computers. A recent trend is to store them remotely and access them via the Internet. 105 Constitutional Rights An example is GoogleDocs. It allows you to store wordprocessing and spreadsheet documents to Google’s servers, where you can jointly edit them with other people you’re collaborating with. Another example is Apple’s MobileMe, where you can back up the information on your iPhone—your photos, documents, contacts, and other personal data. Microsoft’s SkyDrive lets you store your personal documents for free. This allows you to back up many of the important files on your computer. The promise of cloud computing is that your documents can be much safer and your software can be always up to date.

Since people’s documents are no longer stored on their home computers but reside instead with third parties, the shift to cloud computing will effectively remove Fourth Amendment protection from their documents.4 Collusion and Compulsion There are times when companies readily cooperate with the government and will turn over your information. This happened after September 11. Government agencies went to the airlines and demanded that they surrender their customer records. Despite the fact the airlines had promised never to share their information with others, they readily handed it over.5 But in many instances, companies would rather not give your information to the government. They want you to trust them. Suppose you’re uncertain about using a cloud computing service. The company might want to point out that it respects your privacy and will never share your information with anyone without your consent.

Leis, 255 F.3d 325, 336 (6th Cir. 2001) (holding that people “lack a Fourth Amendment privacy interest in their [Internet service] subscriber information because they communicate[] it to the systems operators”); see also United States v. Kennedy, 81 F. Supp. 2d 1103, 1110 (D. Kan. 2000); United States v. Hambrick, 55 F. Supp. 2d 504, 508 (W.D. Va. 1999). 4. For further discussion about cloud computing and privacy, see Nicole A. Ozer & Chris Conley, Cloud Computing: Storm Warning for Privacy? (2010) (report for the ACLU of Northern California), available at http:// 5. See In re Jet Blue Airways Corp. Privacy Litigation, 379 F. Supp. 2d 299, 305 (E.D.N.Y. 2005); Dyer v. Northwest Airlines Corp., 334 F. Supp. 2d 1196, 1197, 1199 (D.N.D. 2004). 6. Protecting Your Personal Information, U.S. Census 2010, http://2010. (last visited Aug. 17, 2010). 7.


pages: 294 words: 81,292

Our Final Invention: Artificial Intelligence and the End of the Human Era by James Barrat


3D printing, AI winter, Amazon Web Services, artificial general intelligence, Automated Insights, Bernie Madoff, Bill Joy: nanobots, brain emulation, cellular automata, cloud computing, cognitive bias, computer vision, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Isaac Newton, Jaron Lanier, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, Loebner Prize, lone genius, mutually assured destruction, natural language processing, Nicholas Carr, optical character recognition, PageRank, pattern recognition, Peter Thiel, prisoner's dilemma, Ray Kurzweil, Rodney Brooks, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, smart grid, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, superintelligent machines, technological singularity, The Coming Technological Singularity, traveling salesman, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero day

First, as we learned from Kurzweil’s LOAR, computer speed and capacity double in as little as a year, every year. That means whatever hardware requirements an AGI system requires today should be satisfied on average by half the hardware, and cost, a year from now. Second, the accessibility of cloud computing. Cloud computing permits users to rent computing power and capacity over the Internet. Vendors like Amazon, Google, and Rackspace offer users a choice of processor speeds, operating systems, and storage space. Computer power has become a service instead of a hardware investment. Anyone with a credit card and some know-how can rent a virtual supercomputer. On Amazon’s EC2 cloud computing service, for instance, a vendor called Cycle Computing created a 30,000-processor cluster they named Nekomata (Japanese for Monster Cat). Every eight processors of its 30,000 came with seven gigabytes of RAM (about as much random access memory as a PC has), for a total of 26.7 terabytes of RAM and two petabytes of disk space (that’s equal to forty million, four-drawer filing cabinets full of text).

And like any information technology, market forces and innovation fuel it. One important innovation for cybercrime is cloud computing—selling computing as a service, not a product. As we’ve discussed, cloud services like those offered by Amazon, Rackspace, and Google allow users to rent processors, operating systems, and storage by the hour, over the Internet. Users can pile on as many processors as their project needs, within reason, without attracting attention. Clouds give anyone with a credit card access to a virtual supercomputer. Cloud computing has been a runaway success, and by 2015 is expected to generate $55 billion in revenue worldwide. But, it’s created new tools for crooks. In 2009 a criminal network used Amazon’s Elastic Cloud Computing Service (EC2) as a command center for Zeus, one of the largest botnets ever. Zeus stole some $70 million from customers of corporations, including Amazon, Bank of America, and anti-malware giants Symantec and McAfee.

In 2011, botnet victims increased 654 percent: Schwartz, Mathew, “Botnet Victims Increased 654 percent in 2011,” InformationWeek, February 18, 2011, (accessed July 11, 2012). a one trillion-dollar industry: Symantec, “What is Cybercrime?” last modified 2012, (accessed July 11, 2012). Cloud computing has been a runaway success: Malik, Om, “How Big is Amazon’s Cloud Computing Business? Find Out,” GIGAOM, August 11, 2010, (accessed June 4, 2011). Zeus stole some $70 million: Ragan, Steve, “ZBot data dump discovered with over 74,000 FTP credentials,” The Tech Herald, June 29, 2009, (accessed June 4, 2011). 21.3 percent overall, comes from Shaoxing: Melanson, Donald, “Symantec names Shaoxing, China, as world’s malware capital,” Engadget, March 29, 2010, (accessed June 4, 2011).


pages: 484 words: 104,873

Rise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford


3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, banking crisis, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, computer age, debt deflation, deskilling, diversified portfolio, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Fractional reserve banking, Freestyle chess, full employment, Goldman Sachs: Vampire Squid, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Khan Academy, knowledge worker, labor-force participation, labour mobility, liquidity trap, low skilled workers, low-wage service sector, Lyft, manufacturing employment, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, performance metric, Peter Thiel, Plutocrats, plutocrats, post scarcity, precision agriculture, price mechanism, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Richard Feynman, Rodney Brooks, secular stagnation, self-driving car, Silicon Valley, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, Thomas L Friedman, too big to fail, Tyler Cowen: Great Stagnation, union organizing, Vernor Vinge, very high income, Watson beat the top human players on Jeopardy!, women in the workforce

IBM envisions the rapid emergence of an entire ecosystem of smart, natural language applications—all carrying the “Powered by Watson” label.26 The migration of leading-edge artificial intelligence capability into the cloud is almost certain to be a powerful driver of white-collar automation. Cloud computing has become the focus of intense competition among major information technology companies, including Amazon, Google, and Microsoft. Google, for example, offers developers a cloud-based machine learning application as well as a large-scale compute engine that lets developers solve huge, computationally intensive problems by running programs on massive supercomputer-like networks of servers. Amazon is the industry leader in providing cloud computing services. Cycle Computing, a small company that specializes in large-scale computing, was able to solve a complex problem that would have taken over 260 years on a single computer in just 18 hours by utilizing tens of thousands of the computers that power Amazon’s cloud service.

At the same time, entrepreneurs are already finding ways to use the same cloud-based building blocks to create affordable automation products geared toward small or medium-sized businesses. Cloud computing has already had a significant impact on information technology jobs. During the 1990’s tech boom, huge numbers of well-paying jobs were created as businesses and organizations of all sizes needed IT professionals to administer and install personal computers, networks, and software. By the first decade of the twenty-first century, however, the trend began to shift as companies were increasingly outsourcing many of their information technology functions to huge, centralized computing hubs. The massive facilities that host cloud computing services benefit from enormous economies of scale, and the administrative functions that once kept armies of skilled IT workers busy are now highly automated.

Jet aircraft were still essentially similar to the designs of the 1970s; however, they now had “fly by wire” systems, in which computers moved the control surfaces in response to the pilots’ inputs, as well as increased flight automation. In the years following 2000, information technology continued its acceleration and productivity rose as businesses got better at taking full advantage of all the new innovations. Many of those good jobs created in the 1990s began to disappear as corporations automated or offshored jobs, or began to outsource their IT departments to centralized “cloud” computing services. Throughout the economy, computers and machines were increasingly replacing workers rather than making them more valuable, and wage increases fell far short of growth in productivity. Both the share of national income going to labor and the labor force participation rate declined dramatically. The job market continued to polarize, and jobless recoveries became the norm. Jet aircraft still used the same basic designs and propulsion systems as in the 1970s, but computer-aided design and simulation had resulted in many incremental improvements in areas such as fuel efficiency.


pages: 329 words: 95,309

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


algorithmic trading, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, bank run, Basel III, bitcoin, business intelligence, business process, business process outsourcing, call centre, cashless society, clean water, cloud computing, corporate social responsibility, credit crunch, crowdsourcing, cryptocurrency, demand response, disintermediation, don't be evil,, 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, mobile money, Mohammed Bouazizi, new economy, Northern Rock, Occupy movement, platform as a service, Ponzi scheme, prediction markets, pre–internet, quantitative easing, ransomware, reserve currency, RFID, Satoshi Nakamoto, Silicon Valley, smart cities, software as a service, Steve Jobs, strong AI, Stuxnet, trade route, unbanked and underbanked, underbanked, upwardly mobile, We are the 99%, web application, Y2K

This will be the new bank model and the new bank order post this crisis will weed out those who get the follow the free model and provide real value, versus those transactional banks that are just processors. Banking as a Service Banking as a Service (BaaS) is the new model of banking, and is based upon cloud computing structures of Digital Banking. Bearing in mind that the bank has moved from integrated to modular, this is the new way of working where bank processes are apps and bank processing are APIs (Application Program Interfaces). A slightly confusing and technical discussion, so let’s start with the idea of cloud computing in banking. Cloud Computing is a wide and diverse operation that has gained a panacea status of being all things to all people. It’s, Azure, Exalogic, Amazon and more. Put in “Cloud Computing” to Google, who also provide clouds, and you get sponsored adverts from HP, Intel, Siemens and more all talking about clouds. It’s Software as a Service, Platform as a Service, and Infrastructure as a Service.

The customer can then setup the way in which their payments account works for them, in the same way you would set up your iPhone. It’s totally flexible and unique to them. This can only be achieved through collaboration and partnership however and we, as a company, develop these capabilities and then ensure that they conform to the rules, which is the regulations to maintain our banking licence. Within these partnerships, do you use cloud computing? Our technology people philosophically think cloud is potentially relevant but, in fact, we are not using cloud computing today for four main reasons. First of all we feel that it is not that secure for financial servicing and we are careful about, and possibly distrust, the use of cloud. We prefer to know where the data is stored and security is crucial to a bank, so this is why we stay out of any cloud discussion today. Second, we do not feel it is necessary to use such services today.

It’s not something where we are putting our bank services in a cloud computing operation like Amazon. So it depends how you define cloud. Yes. There are very many ways of talking about cloud, and I am referring here to placing my operating systems and bank data in the cloud. I would never place my bank data in the cloud, but outsourcing is different. Do you not think cloud is just like outsourcing? We are using outsourced services, but the difference between outsourced relationships and cloud is that we use outsourcing for very specific reasons. For example, if I outsource the running of my machines I know who the companies are, I know where they are, my auditors have approved them and they are working according to the requirements of a German banking regulator. We don’t have that today with cloud computing. The quality and security standards are not there yet, and a typical cloud provider is not able to give those to us.


pages: 90 words: 17,297

Deploying OpenStack by Ken Pepple


Amazon Web Services, cloud computing, database schema, Infrastructure as a Service, web application, x509 certificate

While there, he co-authored two books “Consolidation in the Data Center: Simplifying IT Environments to Reduce Total Cost of Ownership” and “Migrating to the Solaris Operating System: The Discipline of UNIX-to-UNIX Migrations” for Prentice Hall PTR. Ken is also a frequent speaker, presenting at conferences including Gartner's Data Centre Summit, TOGAF China, IDC's Asia/Pacific Cloud Computing Conferences and JavaOne. Currently, Ken focused on building cloud computing infrastructure. As part of this work, he has designed clouds for service providers and written code for the OpenStack project. You can catch up on Ken's current work at his blog ( or view his author page at Amazon (​QQBWJW). Colophon The animal on the cover of Deploying OpenStack is a Tenrec.

., was aware of a trademark claim, the designations have been printed in caps or initial caps. While every precaution has been taken in the preparation of this book, the publisher and authors assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein. O'Reilly Media * * * Preface This book is aimed at developers, technologists, and system administrators eager to understand and deploy cloud computing infrastructure projects based upon OpenStack software. It is intended to provide the reader with a solid understanding of the OpenStack project goals, details of specific OpenStack software components, general design decisions, and detailed steps to deploy OpenStack in a few controlled scenarios. Along the way, readers would also learn common pitfalls in architecting, deploying, and implementing their cloud.

The OpenStack Project The OpenStack project has been created with the audacious goal of being the ubiquitous software choice for building cloud infrastructures. In just over one year, it has gone from an idea to start collaborating to being the most talked-about project in open source. In this chapter, we will examine the project’s goals, history, and how you can participate in its future. What Is the OpenStack Project ? The OpenStack Project aims to create an open source cloud computing platform for public and private clouds aimed at scalability without complexity. Initially focusing on Infrastructure as a Service (IaaS) offerings, the project currently encompasses three components: OpenStack Compute: Software to orchestrate, manage, and offer virtual machines. The software for this is called “Nova.” OpenStack Object Store: Software for the redundant storage of static objects.


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, 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, Julian Assange, Khan Academy, M-Pesa, 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

John Nasibett once said Brian Monger, “Knowing Who Your Market Is and What They Want,” SmartaMarketing, November 11, 2012, 40 to 80 percent Ray, “Cloud Computing Economics: 40–80 percent Savings in the Cloud,” CloudTweaks, April 9, 2011, General Martin Dempsey General Martin Dempsey, “Defending the Nation at Network Speed,” remarks at the Brookings Institution, Washington, DC, June 27, 2013. $149 billion in 2014 Transparency Market Research, “Cloud Computing Services Market-Global Industry Size, Market Share, Trends, Analysis and Forecasts, 2012–2018,”, accessed August 11, 2013. a Brookings report explored Allan A. Friedman and Darrell M. West, “Privacy and Security in Cloud Computing,” Issues in Technology Innovation, no. 3, the Brookings Institution (October 26, 2010),

It’s yet another illustration of how the Internet isn’t ungoverned, but rather is self-governed in strange and fascinating ways. Security Risk or Human Right? Foreign Policy and the Internet Cloud computing, the concept of delivering computing resources remotely over a network, is both a multibillion-dollar industry and a growing field that many believe is key to the future of the online world (as we’ll explore later on). But for three days in 2011, the Dutch government threatened to undermine the new era of cloud computing, all in the name of human rights. Taking issue with American laws that gave the US government access to any data stored on computers controlled by American companies, the Dutch Minister of Safety and Justice threatened to deny any American firm the ability to offer cloud-computing services to the Dutch government in 2011. Yet if no country was willing to let its data be held by a foreign company for fear of government surveillance, the transformative power of cloud computing to store and distribute data globally would be severely undermined.

Centers for Disease Control and Prevention (CDC): A public agency that coordinates research, communications, and information sharing for public health in the United States. certificate authority (CA): A trusted organization that produces signed digital “certificates” that explicitly tie an entity to a public key. This allows asymmetric cryptography users to trust that they are communicating with the right party. cloud computing: A shift in control of computing resources from the individual or organization to a shared resource run by a third party. By pooling network-enabled resources, cloud computing enables mobility, scalability, flexibility, and efficiency, but increases the dependency on the cloud provider. computer emergency response team (CERT): Organizations located around the world that serve as hubs of cybersecurity technical expertise, collaboration, and security information dissemination. Many governments have their own national CERTs, as do an increasing number of industrial sectors and large organizations.


pages: 510 words: 120,048

Who Owns the Future? by Jaron Lanier


3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, automated trading system, barriers to entry, bitcoin, book scanning, Burning Man, call centre, carbon footprint, cloud computing, computer age, crowdsourcing, David Brooks, David Graeber, delayed gratification, digital Maoism,, facts on the ground, Filter Bubble, financial deregulation, Fractional reserve banking, Francis Fukuyama: the end of history, George Akerlof, global supply chain, global village, Haight Ashbury, hive mind, if you build it, they will come, income inequality, informal economy, invisible hand, Jacquard loom, Jaron Lanier, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Kickstarter, Kodak vs Instagram, life extension, Long Term Capital Management, Mark Zuckerberg, meta analysis, meta-analysis, moral hazard, mutually assured destruction, Network effects, new economy, Norbert Wiener, obamacare, packet switching, Peter Thiel, place-making, Plutocrats, plutocrats, Ponzi scheme, post-oil, pre–internet, race to the bottom, Ray Kurzweil, rent-seeking, reversible computing, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart meter, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, The Market for Lemons, Thomas Malthus, too big to fail, trickle-down economics, Turing test, Vannevar Bush, WikiLeaks

By paying it you not only create new money, but you strengthen property values around your own house, effectively making a little of the money that your neighbors create when they get mortgages. This sort of result is already calculated today, but the payments don’t flow. The extra work for the microprocessors in the cloud computers would be trivial, considering the expected course of Moore’s Law, and the extra payments would expand the economy for everyone, including the cloud computing companies. Economic expansion ought to more than pay for the extra trouble. Would the correlation be valid? Well, this would be business and not science. Honestly, as I explained earlier, I am super-skeptical of algorithms of this kind. It’s incredibly hard to design experiments that separate the influence of such algorithms from their predictive veracity.

If we continue on the present path, benefits will instead flow mostly to the tenders of the top computers that route data about surgery, essentially by spying on doctors and patients. The Beach at the Edge of Moore’s Law A heavenly idea comes up a lot in what might be called Silicon Valley metaphysics. We anticipate immortality through mechanization. A common claim in utopian technology culture is that people—well, perhaps not everyone—will be uploaded into cloud computing servers* later in this century, perhaps in a decade or two, to become immortal in Virtual Reality. Or, if we are to remain physical, we will be surrounded by a world animated with robotic technology. We will float from joy to joy, even the poorest among us living like a sybaritic magician. We will not have to call forth what we wish from the world, for we will be so well modeled by statistics in the computing clouds that the dust will know what we want.

These nanopayments will add up, and lead to a new social contract in which people are motivated to contribute to an information economy in ever more substantial ways. This is an idea that takes capitalism more seriously than it has been taken before. A market economy should not just be about “businesses,” but about everyone who contributes value. I could just as well frame my argument in the language of barter and sharing. Leveraging cloud computing to make barter more efficient, comprehensive, and fair would ultimately lead to a similar design to what I am proposing. The usual Manichaean portrayal of the digital world is “new versus old.” Crowdsourcing is “new,” for instance, while salaries and pensions are “old.” This book proposes pushing what is “new” all the way instead of part of the way. We need not shy away. Big Talk, I Know . . .


pages: 302 words: 82,233

Beautiful security by Andy Oram, John Viega


Albert Einstein, Amazon Web Services, business intelligence, business process, call centre, cloud computing, corporate governance, credit crunch, crowdsourcing, defense in depth,, fault tolerance, Firefox, loose coupling, market design, Monroe Doctrine, new economy, Nicholas Carr, Nick Leeson, Norbert Wiener, optical character recognition, packet switching, performance metric, pirate software, Search for Extraterrestrial Intelligence, security theater, SETI@home, Silicon Valley, Skype, software as a service, statistical model, Steven Levy, The Wisdom of Crowds, Upton Sinclair, web application, web of trust, x509 certificate, zero day, Zimmermann PGP

This chapter represents just my perspective—maybe my bias—but my team’s performance depends on how closely the future measures up to the thoughts in this chapter! Cloud Computing and Web Services: The Single Machine Is Here Civilization advances by extending the number of important operations which we can perform without thinking of them. —Alfred North Whitehead An Introduction to Mathematics (1911) Today, much is being made of “cloud computing” in the press. For at least the past five years, the computer industry has also expressed a lot of excitement about web services, which can range from Software as a Service (SaaS) to various web-based APIs and service-oriented architecture (SOA, pronounced “so-ah”). Cloud computing is really nothing more than the abstraction of computing infrastructure (be it storage, processing power, or application hosting) from the hardware system or users.

They care about the functionality of the system instead of the infrastructure that makes it possible, in the same way that average telephone users don’t care which exchanges they are routed through or what type of cable the signal travels over in order to talk to their nanas. But even though cloud computing is a natural extension of other kinds of online services and hosting services, it’s an extremely important development in the history of the global network. Cloud computing democratizes the availability of computing power to software creators from virtually all backgrounds, giving them supercomputers on-demand that can power ideas into reality. Some may say this is a return to the old days when all users could schedule time on the mainframe and that cloud computing is nothing new, but that’s hardly the point. The point is that this very day, supercomputers are available to anyone who has access to the Internet. Web services are standards-based architectures that expose resources (typically discrete pieces of application functionality) independently of the infrastructure that powers them.

Google is renowned for building megalithic data centers across the world; Microsoft is investing heavily in a cloud operating system called Azure, along with gigantic data center infrastructures to host software and services; and Amazon has started renting out parts of the infrastructure that they built as part of their own bid to dominate the online retailing space. Clouds and Web Services to the Rescue The question security professionals should be asking is not “Can cloud computing and web services be made secure?” but “How can we apply security to this new approach?” Even more cleverly, we should think: “How can we embrace this paradigm to our advantage?” The good news is that applying security to web services and cloud computing is not as hard as people may think. What at first seems like a daunting task just requires a change of paradigm. The assumption that the company providing you with a service also has to guarantee your security is just not valid. To show you how readily you can see the new services as a boon to security instead of a threat, let me focus on a real-world scenario.


pages: 458 words: 135,206

CTOs at Work by Scott Donaldson, Stanley Siegel, Gary Donaldson


Amazon Web Services, bioinformatics, business intelligence, business process, call centre, centre right, cloud computing, computer vision, connected car, crowdsourcing, data acquisition, distributed generation, domain-specific language, glass ceiling, pattern recognition, Pluto: dwarf planet, Richard Feynman, Richard Feynman, shareholder value, Silicon Valley, Skype, smart grid, smart meter, software patent, thinkpad, web application, zero day

The second one is we decided about a year and a half ago to change the world in terms of how IT works. And not a lot of companies do that. And I sometimes joke, “We're either going to succeed beyond our wildest expectations or go down in a giant ball of flames, but it's not going to be anything in between.” We decided to change the world. It's about cloud computing and managing cloud computing. The realization I came to is 98% of what you need for cloud computing is IT management and security. Historically, if you look at the way IT has worked, it has been application platforms, software development tools, pre-built applications, but if I'm using the Amazon relational database I don't need a database platform. I need to manage the Amazon RDS (relational database service). S. Donaldson: Right. Ferguson: If you look at, people don't actually write applications.

But they don't want to be controlled by a commercial vendor who can go out of business, can be purchased, merged, acquired, situations like that. Siegel: So given what you just said, how does the rush to cloud computing influence how you handle your customers? Cherches: Cloud computing is a very big, emerging technology right now. In the old days, literally five years ago, I would say to someone, “It will take us two weeks, three weeks, or even a month to get the new server from the manufacturer, then configure the system, then patch it, then provision it on a network, then…” Customers (and our internal developers) won't take that answer anymore. They want something in days at most. Virtualization and cloud computing are important technologies. Customers still want custom solutions, but that custom solution can now live in the cloud. If they are very successful, they can scale the solution quickly.

Index 3D technology David Kuttler, 302 Jerry Krill, 83–85 64-bit architectures, 272–274, 281 A acquisitions, William Ballard, 279–280 Adobe, reverse image searching and, 246 AEP (American Electric Power), 128–129 Aguru Images, Craig Miller, 53–54, 56–59 algae, Craig Miller, 69, 76 Alm, Al, 50 Alving, Amy, 1–20 Amazon EC2, 36 Amazon Web Services (AWS), 245 American Electric Power (AEP), 128–129 American Public Media, 163 Amperion, 128 APL (Applied Physics Laboratory) global technical outreach, 90 Jerry Krill, 82 application development, Jeff Tolnar, 145 architecture technical review, 26 Arduinos, Craig Miller, 77 asymmetric warfare, Jerry Krill's comments on, 92 AWS (Amazon Web Services), 245 B Ballard, William, CTO of Gerson Lehrman Group, Inc, 261–283 Beyster, Bob, 51–52 Bilger, Mark, 23 Black, David, 262 Bloore, Paul, 239–260 Bodine, Greg, 30 BPLG (BPL Global), 127–128, 132 breakout engagements, Gerson Lehrman, 265 budgeting, Jeff Tolnar, 146–148 bundling hardware and software, Jeff Tolnar, 135 Burke, Thomas, 177 business development personnel, Gerson Lehrman, 266 C CA Open Space, 39 callable interface, 41 career lessons Darko Hrelic, 206–207, 211 Jan-Erik de Boer, 236 Jerry Krill, 91 Paul Bloore, 253 Wesley Kaplow, 110 career path Amy Alving, 1–6 Darko Hrelic, 205–206 Dmitry Cherches, 181–185 Jan-Erik de Boer, 237 Jeff Tolnar, 128 Marty Garrison, 152 Paul Bloore, 240–242 Tom Loveland, 176–178 Wesley Kaplow, 105–110 CATEX, Craig Miller, 51 Cherches, Dimitri background, 173 of Mind Over Machines, 173–204 ChoicePoint, 158 CIO responsibilities, of William Ballard, 268 CIO role, versus CTO role, 282 CIOs, Jeff Tolnar, 130–131 cloud computing, 35 Amy Alving, 16–17 Craig Miller, 65 David Kuttler, 302 Dmitry Cherches, 186–188, 200 Gerson Lehrman, 277 Jeff Tolnar, 142, 147–148 Marty Garrison, 160, 167 CloudShield, 13 cluster analysis, Craig Miller, 64 CommonCrawl group, 257 communication activities, of William Ballard, 269 communication, importance of, 30 competition, evaluating Amy Alving, 12–13 Darko Hrelic, 211–212, 217 Gerson Lehrman, 265 Jerry Krill, 101–102 Paul Bloore, 244–245 computing cloud computing, 35 Amy Alving, 16–17 Craig Miller, 65 David Kuttler, 302 Dmitry Cherches, 186–188, 200 Gerson Lehrman, 277 Jeff Tolnar, 142, 147–148 Marty Garrison, 160, 167 distributed computing, 242 mobile computing, 39–40 Darko Hrelic, 209–210 impact on Gerson Lehrman, 276 Jerry Krill, 96 Marty Garrison, 168 Paul Bloore, 254 Wesley Kaplow, 123 Comverge, 137 conference calls, ZipDx, 277–278 consulting, by Gerson Lehrman, 265 continuous deployment cycle, at Gerson Lehrman, 281 corporate strategy, Rick Mosca, 191–194 councils, Gerson Lehrman, 264 creativity, role in career path Jerry Krill, 85–87 Paul Bloore, 241 Wesley Kaplow, 116 Crinks, Bert, 115–116 CTO responsibilities, of William Ballard, 267–271, 282–283 Cuomo, Jerry, 25 customizing software, William Ballard's advice regarding, 270–272 cyanobacteria, Craig Miller, 79 cyber security Amy Alving, 18–19 CloudShield, 13 Darko Hrelic, 214–215 Dmitry Cherches, 201 Gerson Lehrman, 276 Springer, 235 Wesley Kaplow, 123 D Dannelly, Doug, 69 DARPA (Defense Advanced Research Projects Agency), Amy Alving, 5–6 Darwin, Charles, 70 data mining, real-time, 281–282 databases Jeff Tolnar, 141 used at Gerson Lehrman, 272 David Kuttler, 296 DAVID system, 165 de Boer, Jan-Erik, 219–237 Debevec, Paul, 57 decision-making, Jeff Tolnar, 133–134 Defense Advanced Research Projects Agency (DARPA), Amy Alving, 5–6 Delman, Debra, 161 Demand Media, 261–262 Department of Energy (DoE), 54–55, 64 deployment cycle, at Gerson Lehrman, 281 DER (distributed energy resources), 139, 142–149 DEs (Distinguished Engineers), 25 development methodology, Paul Bloore, 256–257 development resources, Jeff Tolnar, 139–140 DiData, Craig Miller, 53, 61 digital watermarking, 243 Dimension Data, Craig Miller, 52 Distinguished Engineers (DEs), 25 distributed computing, 242 distributed energy resources (DER), 139, 142–149 Dobson, David, 36 DoE (Department of Energy), 54–55, 64 domain expertise, 36 E economics of consulting with Gerson Lehrman, 265 William Ballard's advice regarding, 270–271, 279 electric co-ops, Craig Miller, 54–55 electrical transformers, Craig Miller, 68 employees, Gerson Lehrman, 265–266 Endhiran movie, Craig Miller, 58–59 energy policy, Craig Miller, 50 engineering offices, Gerson Lehrman, 266 engineers, cost of, 270, 279 ETL (extraction, translation, load), 203 evaluating competition Amy Alving, 12–13 Darko Hrelic, 211–212, 217 Gerson Lehrman, 265 Jerry Krill, 101–102 Paul Bloore, 244–245 expert network space, Gerson Lehrman, 265 expertise, use of, 274–275 external organizations, affiliations of Gerson Lehrman with, 269 extinction, Craig Miller, 78–79 extraction, translation, load (ETL), 203 F FDA, David Kuttler, 300–301 Ferguson, Don, interview with, 21–47 Fernandez, Raul, 52 ferrofluid, 241 First of a Kind project, 23 Folderauer, Ken, 114 fractal architecture, 273–274 free space optics, 84, 95 frequency variations, Craig Miller, 62–63 functional programming, 278 fundraising, Jeff Tolnar, 146 G Garrison, Marty, interview with, 151 Gayal, Amoosh, 24 Gelpin, Tim, 89 G.I.


pages: 382 words: 120,064

Bank 3.0: Why Banking Is No Longer Somewhere You Go but Something You Do by Brett King


3D printing, additive manufacturing, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, asset-backed security, augmented reality, barriers to entry, bitcoin, bounce rate, business intelligence, business process, business process outsourcing, call centre, capital controls, citizen journalism, Clayton Christensen, cloud computing, credit crunch, crowdsourcing, disintermediation,, George Gilder, Google Glasses, high net worth, I think there is a world market for maybe five computers, Infrastructure as a Service, invention of the printing press, Jeff Bezos, jimmy wales, London Interbank Offered Rate, M-Pesa, Mark Zuckerberg, mass affluent, microcredit, mobile money, more computing power than Apollo, Northern Rock, Occupy movement, optical character recognition, performance metric, platform as a service, QWERTY keyboard, Ray Kurzweil, recommendation engine, RFID, risk tolerance, self-driving car, Skype, speech recognition, stem cell, telepresence, Tim Cook: Apple, transaction costs, underbanked, web application

Now, extend that to personal medical data, financial information, important company documents, purchase history, favourite movies, music and so forth. How do we get access to this information on the move? Figure 10.1: All the major platforms see a silver lining in Cloud services For this reason, Google, IBM, Apple, Microsoft and a host of other players are making various bets on what is known as cloud computing. Cloud computing uses the Internet and central remote servers to maintain data and applications. It allows the use of applications without installation and allows users access to their personal data and files using any device that has Internet access. Cloud computing abstracts users from their applications and data by providing those facilities via a browser, effectively minimising storage requirements and leaving processing to the cloud rather than requiring heavy local processing capability. It does, however, rely heavily on bandwidth to get expeditious results.

Why transfer files constantly from one device to another, or sync our smartphone every few days, when the data is shared constantly via an online store of all our personal information, our private and public data and our identity and associated artefacts? If all our devices connect with the same data in the cloud, we need never sync or transfer a file between our devices ever again. The Players Apple has recently started to make a foray into cloud computing in a major way. It is building a $1-billion data centre in North Carolina, possibly the largest of any in the world.2 iCloud (previously MobileMe®) was the first of a series of online services based on cloud computing designed to create new revenue streams for the tech giant. iCloud is designed to connect all our devices and push information up and down to keep everything synced and up to date. iDisk, incorporated into iCloud, gives users 20GB of remote hard disk space for storing files that are too big to email, photo galleries, and such.

The questions remain as to what services work, and what revenue models will drive cloud computing. For corporations, the business case is simple: shifting to the cloud reduces infrastructure costs and moves platform and application costs to an OpEx (Operating Expense) model instead of CapEx (Capital Expense). In the current economic environment, this has to be promising. Distributed platform access and the benefit of data centres in the cloud also create more opportunities for more agile institution operations and different models such as telecommuting, homeshoring, portable or outreach branches and so forth. If you are sitting there reading this right now with some scepticism about the possibilities of the cloud as it pertains to banking, think about this. Arguably the most successful cloud computing service today, with close to one billion users, is Facebook.3 It is run almost completely through our browser or apps.


pages: 270 words: 79,992

The End of Big: How the Internet Makes David the New Goliath by Nicco Mele


3D printing, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apple's 1984 Super Bowl advert, barriers to entry, Berlin Wall, big-box store, bitcoin, business climate, call centre, Cass Sunstein, centralized clearinghouse, Chelsea Manning, citizen journalism, cloud computing, collaborative consumption, collaborative editing, crony capitalism, cross-subsidies, crowdsourcing, David Brooks, death of newspapers, Donald Trump, Douglas Engelbart,, Exxon Valdez, Fall of the Berlin Wall, Filter Bubble, Firefox, Galaxy Zoo, global supply chain, Google Chrome, Gordon Gekko, Hacker Ethic, Jaron Lanier, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, Lean Startup, Mark Zuckerberg, minimum viable product, Mohammed Bouazizi, Mother of all demos, Narrative Science, new economy, Occupy movement, Peter Thiel, pirate software, Ronald Reagan, Ronald Reagan: Tear down this wall, sharing economy, Silicon Valley, Skype, social web, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, Ted Nelson, Telecommunications Act of 1996, telemarketer, The Wisdom of Crowds, transaction costs, uranium enrichment, Whole Earth Catalog, WikiLeaks, Zipcar

Radical connectivity has played a key role in collapsing the advantages of scale, removing barriers to entry to the marketplace and—more importantly—allowing small companies to share resources that previously were only available to Big Companies. Inside the Cloud Cloud computing exemplifies such resource sharing. You hear people talking about the cloud all the time in the context of the Internet, but a lot of us still have a fairly cloudy notion of what exactly cloud computing means. From the perspective of companies, cloud computing makes it easier to share computing resources that otherwise would be too expensive. Let’s take a look at how this works. The Internet physically exists on computers called servers. Technically, any computer can be a server, even your smartphone. (For a while, I kept a server in my closet to host my personal Web site,, using an old laptop I had retired from travel duty.)

Buy it from Amazon. Suddenly need 10,000 times more space because your tiny start-up has gone viral? Amazon can turn it on in seconds. Hundreds if not thousands of vendors now offer cloud computing. The complicated technical resources required to host and manage Web sites used to cost a lot of money and take a lot of time. They still do. But thousands or even millions of small businesses, groups, or individuals can now share that cost, allowing your tiny start-up access to the same kind of computing resources mobilized by a giant corporation like Google or Facebook. This kind of level playing field offered by cloud computing threatens Big Companies—and it ultimately even challenges the hegemony of the large, Even Bigger platforms described in chapter 4. Harvard Business School’s Wessel articulates, in effect, an argument for why loose coalitions of small businesses banding together can achieve comparable competitive power as large platform players like Amazon.

Finding a burgeoning culture of self-employed Americans like him, he excitedly wrote a landmark article for Fast Company magazine about the “free agent nation” he had stumbled upon.7 The article hit a nerve, and he went on to turn it into a best-selling book. Almost fifteen years later, Harvard Business Review revisited Pink’s argument and found that workplace trends did indeed show an astonishing movement toward individual employment.8 Why is that? I argue here that radical connectivity—in particular the efficiencies provided by cloud computing for sharing resources and collaboration—is dramatically reducing scale effects and will continue to reduce them in the coming decades. Add in technologies that enable on-demand fabrication, and you’ll see a significant erasure of the advantages of size in commerce, and economies that are far more local than at present. The Future That Is upon Us I admit, talk of scale economies is abstract.


pages: 666 words: 181,495

In the Plex: How Google Thinks, Works, and Shapes Our Lives by Steven Levy


23andMe, AltaVista, Anne Wojcicki, Apple's 1984 Super Bowl advert, autonomous vehicles, book scanning, Brewster Kahle, Burning Man, business process, clean water, cloud computing, crowdsourcing, Dean Kamen, discounted cash flows, don't be evil, Douglas Engelbart, El Camino Real, fault tolerance, Firefox, Gerard Salton, Google bus, Google Chrome, Google Earth, Googley, HyperCard, hypertext link, IBM and the Holocaust, informal economy, information retrieval, Internet Archive, Jeff Bezos, Kevin Kelly, Mark Zuckerberg, Menlo Park, optical character recognition, PageRank, Paul Buchheit, Potemkin village, prediction markets, recommendation engine, risk tolerance, Sand Hill Road, Saturday Night Live, search inside the book, second-price auction, Silicon Valley, skunkworks, Skype, slashdot, social graph, social software, social web, spectrum auction, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, Ted Nelson, telemarketer, trade route, traveling salesman, Vannevar Bush, web application, WikiLeaks, Y Combinator

“When people said that it should be canceled, I told them it’s really the foundation for a lot of other products. It just seemed obvious that the way things were going, all information was going to be online.” People would quickly identify that concept as a core value of “cloud computing.” The term came from the phenomenon where data—even private, proprietary information once stored on one’s own computer—would be accessed via the Internet, no matter where you were. As far as the user was concerned, information lived in a huge data cloud, and you pulled it down and sent it back up without regard to its actual location. The term originally wasn’t popular at Google. “Internally, we thought of ‘cloud computing’ as a marketing term,” says Urs Hölzle. (“Marketing” being pejorative in this context.) “Technically speaking, it’s cluster computing that you do.” (At Google, people refer to a “cluster” as a large number of servers—well into the thousands—usually representing the minimum number of machines needed to serve search results from a query.)

This program guaranteed that Google’s ideas would spread throughout the world and made it easier to implement cloud computing. Even though competitors would benefit, this wasn’t seen as a negative in Mountain View. If everyone adopted this new computing paradigm, people would always be just a click away from Google’s services—and Google’s ads. What was good for the cloud would be good for Google. 3 “They’re created by machines. And that is what makes us powerful.” In its earlier days, Google had taken pains not to draw the attention of the world’s biggest software company. But everyone knew that eventually the Silicon Valley search kings would wind up in a death cage match with Microsoft. With the development of Google’s cloud computing strategy, it became clear just how that would happen. Microsoft’s revenues flowed largely from two cash cows, both of which were monopolies.

The program worked in two steps—first by mapping the system (figuring out how the information was spread out and duplicated in various locations—basically an indexing process) and then by reducing the information to the transformed data requested. The key was that the programmers could control a massive number of machines, swapping and sharing their contents—a cluster’s worth or more—as if they were a single desktop computer. Ghemawat and Jeff Dean called their project MapReduce. “The engineers only have to think about the data,” says Christophe Bisciglia, a Google engineer who became an evangelist for cloud computing. “The system takes care of the parallelization. You don’t have to think about what machine the data is stored on or how to synchronize what happens when the machine fails or if there’s a bad record or any of that. I just think about the data and how I want to explore or transform the data, so I write code for that, and the system takes care of everything else.” What’s more, with MapReduce Google could easily build out its system—adding thousands more machines, allowing for much more storage and much faster results—without having to change the original code.


pages: 353 words: 104,146

European Founders at Work by Pedro Gairifo Santos


business intelligence, cloud computing, crowdsourcing, fear of failure, full text search, information retrieval, inventory management, iterative process, Jeff Bezos, Lean Startup, Mark Zuckerberg, natural language processing, pattern recognition, pre–internet, recommendation engine, Richard Stallman, Silicon Valley, Skype, slashdot, Steve Jobs, Steve Wozniak, subscription business, technology bubble, web application, Y Combinator

But I happen to be a big fish in a small pond and I'm happy there. Santos: Of all these experiences that you had, including EINSTEINet, what were the main learning points? Varsavsky: I think that Fon exists today thanks to EINSTEINet because in EINSTEINet, I sold the company for one euro to save the jobs of the employees thinking that I was the only crazy person to think that cloud computing had a future. And then two years later, cloud computing really took off. Now cloud computing is huge. So when Wi-Fi looked like it was failing, I remembered EINSTEINet and I said, “I'm going to put my money there because my ideas are not crazy. It's just sometimes ahead of their time and if I have enough money to wait, the market will help me.” Santos: What advice would you give to a new entrepreneur? Varsavsky: Well, I would be realistic and I would say, “Look, if you think you are the lucky sperm that's going to get the ovule, go ahead and start the business.”

In 2000 Jos White, again with his brother Ben, co-founded MessageLabs where he served as Chief Marketing Officer and later as President of the US region. MessageLabs became the market leader for messaging and web security services. In 2008 MessageLabs was acquired by Symantec for approximately $700M, marking the second largest transaction for a private company in the history of the IT security industry. In 2009 Jos White co-founded Notion Capital, again with his brother Ben and three other partners. Notion invests in next generation cloud computing companies. Pedro Santos: Tell me a bit about MessageLabs' history. Jos White: The background is that my brother, Ben White, and I have founded four businesses. We founded our first one with Rory Sweet in 1993, which was called RBR Networks. Originally we were buying and selling second-hand IBM equipment, which is a horrible business with very, very small margins— this business required a lot of wheeling and dealing and definitely attracted its fair share of cowboys!

I worked for a few months in Symantec and then I left, had some time off, and then Ben and I, and three other guys, founded a VC called Notion Capital. We only invest in B2B, cloud-based businesses—really the market we've come from. The best way to add value and to be informed investors is to invest in the market where you have direct experience. Notion was set up in 2009. We've made eight investments and we are pretty excited about the portfolio that we have. Just generally, we were huge believers in this megatrend of cloud-computing. It's a big sort of a tectonic shift in the tech landscape, and we want to try and take advantage of that by backing multiple businesses that are going to play a part in this transition. Santos: Going back to MessageLabs, where were you thinking of doing the IPO? In the UK? In the US? White: We had a big debate about this. I was in the US, so my preference was always a bit more to do it in the US.


pages: 274 words: 58,675

Puppet 3 Cookbook by John Arundel


Amazon Web Services, cloud computing, continuous integration, Debian, defense in depth, GnuPG, place-making, web application

Puppet 3 Cookbook Build reliable, scalable, secure, and high-performance systems to fully utilize the power of cloud computing John Arundel BIRMINGHAM - MUMBAI Puppet 3 Cookbook Copyright © 2013 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Table of Contents Preface 1 Chapter 1: Puppet Infrastructure 7 Introduction 7 Installing Puppet 8 Creating a manifest 10 Managing your manifests with Git 11 Creating a decentralized Puppet architecture 14 Writing a papply script 16 Running Puppet from cron 18 Deploying changes with Rake 22 Bootstrapping Puppet with Rake 26 Automatic syntax checking with Git hooks 29 Chapter 2: Puppet Language and Style 33 Introduction 34 Using community Puppet style 34 Checking your manifests with puppet-lint 36 Using modules 38 Using standard naming conventions 42 Using inline templates 44 Iterating over multiple items 45 Writing powerful conditional statements 47 Using regular expressions in if statements 49 Using selectors and case statements 50 Using the in operator 53 Using regular expression substitutions 54 Table of Contents Chapter 3: Writing Better Manifests 57 Chapter 4: Working with Files and Packages 87 Introduction 58 Using arrays of resources 58 Using definitions 59 Using dependencies 61 Using tags 65 Using run stages 68 Using node inheritance 71 Passing parameters to classes 73 Using class inheritance and overriding 75 Writing reusable, cross-platform manifests 79 Getting information about the environment 81 Importing dynamic information 83 Passing arguments to shell commands 84 Introduction 87 Making quick edits to config files 88 Using Augeas to automatically edit config files 89 Building config files using snippets 91 Using ERB templates 94 Using array iteration in templates 96 Using GnuPG to encrypt secrets 98 Installing packages from a third-party repository 103 Building packages automatically from source 106 Comparing package versions 108 Chapter 5: Users and Virtual Resources 111 Introduction 112 Using virtual resources 112 Managing users with virtual resources 115 Managing users' SSH access 118 Managing users' customization files 121 Efficiently distributing cron jobs 126 Using schedules to limit when resources can be applied 129 Using host resources 132 Using multiple file sources 133 Distributing directory trees 135 Cleaning up old files 137 ii Table of Contents Auditing resources Temporarily disabling resources 139 140 Chapter 6: Applications 143 Introduction 143 Managing Apache servers 144 Creating Apache virtual hosts 145 Creating Nginx virtual hosts 150 Managing MySQL 153 Managing Ruby 158 Chapter 7: Servers and Cloud Infrastructure 165 Chapter 8: External Tools and the Puppet Ecosystem 199 Chapter 9: Monitoring, Reporting, and Troubleshooting 235 Introduction 165 Building high-availability services using Heartbeat 166 Managing NFS servers and file shares 171 Using HAProxy to load-balance multiple web servers 174 Managing firewalls with iptables 178 Managing EC2 instances 188 Managing virtual machines with Vagrant 193 Introduction 200 Creating custom facts 200 Adding external facts 202 Setting facts as environment variables 205 Importing configuration data with Hiera 206 Storing secret data with hiera-gpg 210 Generating manifests with puppet resource 213 Generating manifests with other tools 214 Testing your manifests with rspec-puppet 218 Using public modules 221 Using an external node classifier 223 Creating your own resource types 226 Creating your own providers 228 Creating your own functions 231 Introduction 235 Doing a dry run 236 Logging command output 237 Logging debug messages 239 iii Table of Contents Generating reports Producing automatic HTML documentation Drawing dependency graphs Understanding Puppet errors Inspecting configuration settings 240 242 245 248 251 Index 253 iv Preface A revolution is underway in the field of IT operations. The new generation of configuration management tools can build servers in seconds and automate your entire network. Tools such as Puppet are essential to take full advantage of the power of cloud computing, and build reliable, scalable, secure, high-performance systems. This book takes you beyond the basics and explores the full power of Puppet, showing you in detail how to tackle a variety of real-world problems and applications. At every step, it shows you exactly what commands you need to type and includes complete code samples for every recipe. It takes the reader from rudimentary knowledge of Puppet to a more complete and expert understanding of Puppet's latest and most advanced features, community best practices, writing great manifests, scaling and performance, and how to extend Puppet by adding your own providers and resources.

Once you have verified that the changes are good, then you can merge them into the master branch and roll them out. 187 Servers and Cloud Infrastructure Managing EC2 instances It doesn't make sense for many of us to own and host our own servers, in the same way as it doesn't make sense for us to generate our own electricity. Just like electricity, computing is now a utility. Utility computing (often called cloud computing, for no known reason) allows you to buy as much compute power as you need, for as long as you need it. This makes it easy and cost-efficient to scale your service in response to fluctuating demand. Being able to create new cloud server instances, use them for a few minutes or hours, and then delete them also makes it a lot easier to test and experiment with new software or configurations. If you had to build the servers by hand every time, this process would be too lengthy to make it worthwhile, but with automated configuration management, it's a snap.


pages: 272 words: 64,626

Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs by Andy Kessler


23andMe, Andy Kessler, bank run, barriers to entry, Berlin Wall, British Empire, business process, California gold rush, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, computer age, disintermediation, Eugene Fama: efficient market hypothesis, fiat currency, Firefox, Fractional reserve banking, George Gilder, Gordon Gekko, greed is good, income inequality, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, knowledge economy, knowledge worker, libertarian paternalism, low skilled workers, Mark Zuckerberg, McMansion, Netflix Prize, packet switching, personalized medicine,, prediction markets, pre–internet, profit motive, race to the bottom, Richard Thaler, risk tolerance, risk-adjusted returns, Silicon Valley, six sigma, Skype, social graph, Steve Jobs, The Wealth of Nations by Adam Smith, transcontinental railway, transfer pricing, Yogi Berra

For all the talk of giant data centers with zillions of servers, which sure as heck sounds like the center of the network, Google is the number one beneficiary of intelligence at the edge of the network. It’s the transport of data to and from those data centers that stays dumb. Our desktop computers and laptops and smartphones on the edge aren’t going away, but as bandwidth speeds increase, more and more computing can be done on the network of computers sitting in data centers—also known as the “cloud.” Cloud computing provides search results, processes company payrolls, coordinates video games played by thousands of people simultaneously; even the complex graphics for those games are starting to be drawn in the cloud. Anyone can do it, but it’s not cheap. These clouds are multibillion-dollar investments in data centers and fiber optics. The Internet is far from mature, and its growth is an ever more high-stakes game.

Once you build the cloud, it’s all about network operations. Whoever can deliver search results faster wins. Users usually only realize this subconsciously, but it’s true: Google’s dominant share is as much about speed as it is about relevant results. Compare it with Microsoft or Yahoo! search and you’ll see. Google often builds its data centers next to waterfalls so electricity can be cheap enough to help it win the speed war. New cloud computing applications appear every day—backing up files, managing your money, editing photos, running the back end of multiplayer games like World of Warcraft. Now corporate America is moving its accounting, scheduling, order management, and the like into the cloud, and speed is a top priority. Now wait one second. I invoke the IGA (the Inevitable Google Analogy—all you have to do is show that Google does something to prove it’s the greatest strategy ever!)

INDEX Abundance and scarcity abundance, recognizing cheap versus expensive and cost cutting economic principles main scarcities tech examples of waste, benefits of and wealth creation Activision Advertising Google sales and scarcity Airports, global comparisons Ajax Alinsky, Saul Amazon, recommendations to customers America Online (AOL), instant messaging virtual pipe Anderson, Chris Apache Apple and cloud computing Stores and vertical integration virtual pipe of See also specific products Application, versus features, businesses Applied Semantics Arkwright, Richard Artificial intelligence AT&T Bell Labs vertical integration Wireless Baby boomers Bach, David Back to basics Banking FDIC Federal Reserve, roles of fractional reserve banking money supply as Thieves Behavioral economics Bell Labs Bennett Mechanical Comprehension Test Bernanke, Ben Bessemer, Henry Bezos, Jeff Bionetworks Biotech industry, personalized medicine Birdseye, Clarence BitTorrent Blink (Gladwell) Books, digital Boulton, Matthew Brain and original thought Stroud number Brenner, Reuven Brin, Sergey Broadcasters, as Thieves Brotherhood Brown, Charles Buffett, Warren Burger, Warren Businesses FAB (Feature, Application, Business) with highest returns profitability.


pages: 255 words: 78,207

Web Scraping With Python: Collecting Data From the Modern Web by Ryan Mitchell


AltaVista, Amazon Web Services, cloud computing,, Firefox, meta analysis, meta-analysis, natural language processing, optical character recognition, random walk, self-driving car, Turing test, web application

Thanks to the economies of scale, buying a small compute instance with a large com‐ pany is about the same as buying your own physical, dedicated, machine—except that now, you don’t need to hire an IT guy to keep it running. Of course, step-by-step instructions for setting up and running cloud computing instances are somewhat outside of the scope of this book, but you will likely find that step-by-step instructions are not needed. With both Amazon and Google (not to mention the countless smaller companies in the industry) vying for cloud computing dollars, they’ve made setting up new instances as easy as following a simple prompt, thinking of an app name, and providing a credit card number. As of this writing, both Amazon and Google also offer hundreds of dollars worth of free computing hours to further tempt new clients.

Remote Hosting | 205 Additional Resources Many years ago, running “in the cloud” was mostly the domain of those who felt like slogging through the documentation and already had some server administration experience. However, today, the tools have improved dramatically, due to increased popularity and competition among cloud computing providers. Still, for building large-scale or more-complex scrapers and crawlers, you might want a little more guidance on creating a platform for collecting and storing data. Google Compute Engine by Marc Cohen, Kathryn Hurley, and Paul Newson is a straightforward resource on using Google Cloud Computing with both Python and JavaScript. Not only does it cover Google’s user interface, but also the command-line and scripting tools that you can use to give your application greater flexibility. If you prefer to work with Amazon, Mitch Garnaat’s Python and AWS Cookbook is a brief but extremely useful guide that will get you started with Amazon Web Services and show you how to get a scalable application up and running.

There are two main reference pages for browsing Google APIs. The first is the Prod‐ ucts page, which serves as an organized repository of its APIs, software development kits, and other projects that might be of interest to software developers. The other is the APIs console, which provides a convenient interface to turn API services on and off, view rate limits and usage at a glance, and even spin up a Google-powered cloud computing instance if you feel like it. Most of Google’s APIs are free although some, such as its search API, require a paid license. Google is fairly liberal with its collection of free APIs allowing from 250 requests per day to 20,000,000 requests per day with a basic account. There is also the option to raise the rate limits on some of the APIs by verifying your identity with a credit card (the card is not charged).


pages: 603 words: 141,814

Python for Unix and Linux System Administration by Noah Gift, Jeremy M. Jones


Amazon Web Services, bash_history, cloud computing, create, read, update, delete, database schema, Debian, distributed revision control, Firefox, industrial robot, inventory management, job automation, MVC pattern, skunkworks, web application

Some of the products you may want to consider scripting are VMware Site Recovery Manager, VMware ESX Server, VMware Server, and VMware Fusion. We won’t have room to cover scripting these technologies, as they fall outside the scope of this book, but it would pay to closely monitor these products and examine what role Python will play. Cloud Computing Just when the buzz was settling from virtualization, suddenly cloud computing is raising the buzz yet again. Simply put, “cloud computing” is about using resources that respond on demand to workload requirements. The two big players in cloud computing are Amazon and Google. Google just literally dropped the “C” bomb just a few weeks before this book went to the publisher. Google offered an interesting twist in it that only currently supports Python. This being a book on Python programming, we are sure this doesn’t disappoint you too much.

Object-Relationship Mapping (ORM), Storm ORM, Storm ORM (see also SQLAlchemy ORM; Storm ORM) objects, pinfo, psearch, psearch, who, whos listing, functions for, who, whos obtaining information on, with pinfo, pinfo searching for, with psearch, psearch, psearch OIDs (object identifiers), SNMP Overview open() method, Creating files open() method (shelve), shelve OpenLDAP using with Python, Using LDAP with OpenLDAP, Active Directory, and More with Python, Importing an LDIF File operating systems, Introduction, Using Zenoss to Manage Windows Servers from Linux, Cross-Platform Unix Programming in Python, Creating a Cross-Platform Build Network, PyInotify, PyInotify, OS X, Managing Plist Files from Python, Red Hat Linux Systems Administration, Ubuntu Administration, Solaris Systems Administration, Virtualization, Cloud Computing, Building a sample Google App Engine application cloud computing, Cloud Computing, Building a sample Google App Engine application GNU/Linux, PyInotify with, PyInotify, PyInotify OS X, OS X, Managing Plist Files from Python Red Hat systems administration, Red Hat Linux Systems Administration Solaris systems administration, Solaris Systems Administration Ubuntu administration, Ubuntu Administration Unix programming, cross-platform, Cross-Platform Unix Programming in Python, Creating a Cross-Platform Build Network Virtualization, Virtualization OperatingSystem class (Django), Simple Database Application option with multiple arguments usage pattern (optparse), Option with Multiple Arguments Usage Pattern optparse, Introduction to Optparse, Option with Multiple Arguments Usage Pattern ORM (Object-Relationship Mapping), Storm ORM, Storm ORM (see also SQLAlchemy ORM; Storm ORM) os module, Using the OS Module to Interact with Data, Using the OS Module to Interact with Data, Copying, Moving, Renaming, and Deleting Data, Copying, Moving, Renaming, and Deleting Data, Working with Paths, Directories, and Files, Working with Paths, Directories, and Files, Using os.list copying, moving, renaming, and deleting data, Copying, Moving, Renaming, and Deleting Data, Copying, Moving, Renaming, and Deleting Data listdir() function, Using os.list paths, directories, and files, Working with Paths, Directories, and Files, Working with Paths, Directories, and Files OS X programming, OS X, Managing Plist Files from Python, OS X, Managing Plist Files from Python OSA (Open Scripting Architecture), OS X Scripting APIs Out built-in variable, Interacting with IPython output, Standard Input and Output, Standard Input and Output standard input and output, Standard Input and Output, Standard Input and Output output history, History results, History results output paging, with page function, page output prompts, Python versus IPython, Interacting with IPython P package management, Introduction, EPM Summary: It Really Is That Easy, Registering a Package with the Python Package Index, Registering a Package with the Python Package Index, Distutils, Distutils, Distutils, Buildout, Developing with Buildout, Developing with Buildout, virtualenv, Creating a Custom Bootstrapped Virtual Environment, EPM Package Manager, EPM Summary: It Really Is That Easy building pages with setuptools, Distutils (see setuptools) Buildout tool, Buildout, Developing with Buildout, Developing with Buildout developing with, Developing with Buildout creating packages with disutils, Distutils, Distutils EPM package manager, EPM Package Manager, EPM Summary: It Really Is That Easy registering packages with Python Package Index, Registering a Package with the Python Package Index, Registering a Package with the Python Package Index virtualenv tool, virtualenv, Creating a Custom Bootstrapped Virtual Environment package version, changing active, Change Active Version of Package packet manipulation program, Scapy (see Scapy program) page function, page paramkio library, SSH, SSH parse() method (ElementTree), ElementTree parsing logfiles (example), Log Parsing, Log Parsing parsing XML files with ElementTree, ElementTree, ElementTree partition re-imaging, Automatically Re-Imaging Machines password-protected sites, installing eggs on, Authenticating to a Password Protected Site paths, walking with os module, Working with Paths, Directories, and Files, Working with Paths, Directories, and Files pattern matching, re (see regular expressions) pattern matching with files and directories, Pattern Matching Files and Directories, Pattern Matching Files and Directories pdef function, pdef PDF files, saving data as, PDFs, PDFs pdoc function, pdoc Perez, Fernando, IPython Perl, Python versus, Why Python?

Bayer, Michael, SQLAlchemy ORM Bicking, Ian, virtualenv blocks of code, editing, Magic Edit bookmark command, bookmark bookmarks, cd navigating to bookmarked directories, cd bootstrapped virtual environment, custom, Creating a Custom Bootstrapped Virtual Environment Boto (Amazon Web services), Amazon Web Services with Boto Buildout tool, Buildout, Developing with Buildout, Developing with Buildout developing with, Developing with Buildout bzip2 compression, Using tarfile Module to Create TAR Archives C callbacks, Callbacks, Callbacks capitalization, Built-in methods for str data extraction (see case) case (capitalization), Built-in methods for str data extraction converting for entire string, Built-in methods for str data extraction cd command, cd, cd, cd, dhist -<TAB> option, dhist -b option, cd charts, creating, Graphical Images checksum comparisons, MD5 Checksum Comparisons, MD5 Checksum Comparisons choices usage pattern (optparse), Choices Usage Pattern close( ) function (socket module), socket close() method, Creating files close() method (shelve), shelve cloud computing, Cloud Computing, Building a sample Google App Engine application, Amazon Web Services with Boto, Google App Engine, Building a sample Google App Engine application Amazon Web services with Boto, Amazon Web Services with Boto cmp() function (filecmp module), Using the filecmp Module combining strings, Built-in methods for str data extraction command history, History command line, Introduction, Summary, Basic Standard Input Usage, Basic Standard Input Usage, Introduction to Optparse, Option with Multiple Arguments Usage Pattern, Unix Mashups: Integrating Shell Commands into Python Command-Line Tools, Hybrid Kudzu Design Pattern: Wrapping a Unix Tool in Python to Spawn Processes, Integrating Configuration Files, Integrating Configuration Files basic standard input usage, Basic Standard Input Usage, Basic Standard Input Usage integrating configuration files, Integrating Configuration Files, Integrating Configuration Files integrating shell commands, Unix Mashups: Integrating Shell Commands into Python Command-Line Tools, Hybrid Kudzu Design Pattern: Wrapping a Unix Tool in Python to Spawn Processes optparse, Introduction to Optparse, Option with Multiple Arguments Usage Pattern community of Python users, Why Python?


pages: 283 words: 85,824

The People's Platform: Taking Back Power and Culture in the Digital Age by Astra Taylor


A Declaration of the Independence of Cyberspace, Andrew Keen, barriers to entry, Berlin Wall, big-box store, Brewster Kahle, citizen journalism, cloud computing, collateralized debt obligation, Community Supported Agriculture, conceptual framework, corporate social responsibility, cross-subsidies, crowdsourcing, David Brooks, digital Maoism, disintermediation, don't be evil, Donald Trump, Edward Snowden, Fall of the Berlin Wall, Filter Bubble, future of journalism, George Gilder, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, Internet Archive, Internet of things, invisible hand, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, Kickstarter, knowledge worker, Mark Zuckerberg, means of production, Naomi Klein, Narrative Science, Network effects, new economy, New Journalism, New Urbanism, Nicholas Carr, oil rush, Peter Thiel, Plutocrats, plutocrats, pre–internet, profit motive, recommendation engine, Richard Florida, Richard Stallman, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, slashdot, Slavoj Žižek, Snapchat, social graph, Steve Jobs, Stewart Brand, technoutopianism, trade route, Whole Earth Catalog, WikiLeaks, winner-take-all economy, Works Progress Administration, young professional

On Google traffic figures, see Robert McMillan, “Google Serves 25 Percent of North American Internet Traffic,”, July 22, 2013, Amazon’s centrality in the cloud computing space is hard to exaggerate: in 2012, an outage of one of Amazon’s data centers in Northern Virginia temporarily took down a wide array of dependent sites including Pinterest, Instagram, and Netflix. Related to this, the fact that WikiLeaks never recovered after being booted off of Amazon’s servers is another indication of the company’s dominance of the cloud computing space. Amazon also has a cloud computing contract with the CIA worth a reported $600 million. For the one-in-three-Internet-users figure, see Patrick Thibodeau, “Amazon Cloud Accessed Daily by a Third of All ’Net Users,”, April 18, 2012,

Originality and depth eat away at profits online, where faster fortunes are made by aggregating work done by others, attracting eyeballs and ad revenue as a result. Indeed, the advertising industry is flourishing as never before. In a world where creative work holds diminishing value, where culture is “free,” and where fields like journalism are in crisis, advertising dollars provide the unacknowledged lifeblood of the digital economy. Moreover, the constant upgrading of devices, operating systems, and Web sites; the move toward “walled gardens” and cloud computing; the creep of algorithms and automation into every corner of our lives; the trend toward filtering and personalization; the lack of diversity; the privacy violations: all these developments are driven largely by commercial incentives. Corporate power and the quest for profit are as fundamental to new media as old. From a certain angle, the emerging order looks suspiciously like the old one.

A handful of Internet and technology companies have become as enormous and influential as the old leviathans: they now make up thirteen of the thirty largest publicly traded corporations in the United States.28 The omnipresent Google, which, on an average day, accounts for approximately 25 percent of all North American consumer Internet traffic, has gobbled up over one hundred smaller firms, partly as a method of thwarting potential rivals, averaging about one acquisition a week since 2010; Facebook now has well over one billion users, or more than one in seven people on the planet; Amazon controls one-tenth of all American online commerce and its swiftly expanding cloud computing services host the data and traffic of hundreds of thousands of companies located in almost two hundred countries, an estimated one-third of all Internet users accessing Amazon’s cloud at least once a day; and Apple, which sits on almost $140 billion in cash reserves, jockeys with Exxon Mobil for the title of the most valuable company on earth, with a valuation exceeding the GDP (gross domestic product) of most nations.29 Instead of leveling the field between small and large, the open Internet has dramatically tilted it in favor of the most massive players.


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, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, congestion charging, disintermediation, 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, Julian Assange, Kevin Kelly, license plate recognition, linked data, Lyft, Mark Zuckerberg, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, recommendation engine, RFID, self-driving car, 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, urban planning, WikiLeaks, zero day

The relationship is more feudal: Bruce Schneier (26 Nov 2012), “When it comes to security, we’re back to feudalism,” Wired, We like having someone else: Rachel King (15 Oct 2012), “Consumers actually really like cloud storage, report says,” ZDNet, the rise of cloud computing: This is a good introduction to cloud computing. Michael Armbrust et al. (10 Feb 2009), “Above the clouds: A Berkeley view of cloud computing,” Technical Report No. UCB/EECS-2009-28, Electrical Engineering and Computer Sciences, University of California at Berkeley, they turn our data over: Both Google and Microsoft have turned child porn suspects over to the FBI on their own initiative. Robert Macpherson (4 Aug 2014), “Google defends child porn tip-offs to police,” Yahoo!

NSA revelations made executives: NTT Communications (28 Mar 2014), “NSA after-shocks: How Snowden has changed ICT decision-makers’ approach to the cloud,” Estimates of how much business: Daniel Castro (5 Aug 2013), “How much will PRISM cost the U.S. cloud computing industry?” Information Technology and Innovation Foundation, Andrea Peterson (7 Aug 2013), “NSA snooping could cost U.S. tech companies $35 billion over three years,” Washington Post, Forrester Research believes: James Staten (14 Aug 2013), “The cost of PRISM will be larger than ITIF projects,” James Staten’s Blog,

We like automatic security updates and automatic backups; the companies do a better job of protecting our devices than we ever did. And we’re really happy when, after we lose a smartphone and buy a new one, all of our data reappears on it at the push of a button. In this new world of computing, we’re no longer expected to manage our computing environment. We trust the feudal lords to treat us well and protect us from harm. It’s all a result of two technological trends. The first is the rise of cloud computing. Basically, our data is no longer stored and processed on our computers. That all happens on servers owned by many different companies. The result is that we no longer control our data. These companies access our data—both content and metadata—for whatever profitable purpose they want. They have carefully crafted terms of service that dictate what sorts of data we can store on their systems, and can delete our entire accounts if they believe we violate them.


pages: 202 words: 59,883

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, Elon Musk, factory automation, Filter Bubble, Google Earth, Google Glasses, Internet of things, job automation, Kickstarter, Mars Rover, Menlo Park, New Urbanism, PageRank, pattern recognition, RFID, ride hailing / ride sharing, 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, urban planning, Zipcar

Similarly, significant innovations and accuracy improvements in voice recognition make systems like Apple’s Siri, Google Now and Google Voice Search possible. The foundation for the Age of Context—all of these technologies working together—is the cloud computing infrastructure, which continues to grow exponentially in capability and capacity. And it had better keep growing: A self-driving car, which we describe in Chapter 5, generates about 700 megabytes of data per second. We talked with GM, Ford, Toyota—and Google—about what would happen if every car had that technology. Well, for one thing, today’s cloud computing technology would melt down. Rackspace, a cloud hosting provider and Scoble’s employer, was the first and largest sponsor of this book. Since 2009, it has funded Scoble to travel the world interviewing hundreds of entrepreneurs and innovators.

No part of this book may be reproduced in any form by any means without the express permission of the authors. This includes reprints, excerpts, photocopying, recording, or any future means of reproducing text. Published in the United States by Patrick Brewster Press 1st Edition About the Authors Robert Scoble is among the world’s best-known tech journalists. In his day job as Startup Liaison for Rackspace, the Open Cloud Computing Company, Scoble travels the world looking for what’s happening on technology’s bleeding edge. He’s interviewed thousands of executives and technology innovators and reports for Rackspace TV and in social media. He can be found at You can email him at, and on social networks as Robert Scoble. Shel Israel helps businesses tell their stories in engaging ways as a writer, consultant and presentation coach.

They need to change and advance to meet the rising expectations of modern customers. Today, we are in the midst of a customer revolution where the world is being reshaped by the convergence of social and mobile cloud technologies. The combination of these technologies enables us to connect everything together in a new way and is dramatically transforming the way we live and work. Now, cloud computing over powerful LTE wireless networks is delivering on the promise of billions of computers interconnecting. 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.


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The Flat White Economy by Douglas McWilliams


access to a mobile phone, banking crisis, Big bang: deregulation of the City of London, bonus culture, cleantech, cloud computing, computer age, correlation coefficient, Edward Glaeser,, Erik Brynjolfsson, eurozone crisis, George Gilder, hiring and firing, income inequality, informal economy, knowledge economy, low skilled workers, Network effects, new economy, offshore financial centre, Peter Thiel, Productivity paradox, Silicon Valley, smart cities, special economic zone, Steve Jobs, working-age population

In the UK, for example, roughly 50% of adults over 16 (and possibly a higher proportion of those below 16) used the internet every day, while the proportion who never used the internet fell down to only a quarter. But the intensity and usage of the internet for commercial purposes only started to grow massively towards the end of the decade. In part this was because of the coming together of a range of digital technologies. Cloud computing, for example, has taken off in the past five years, moving data storage away from the hard drives of personal computers onto mass databases, hosted and accessible online. The Cebr report4 on cloud computing showed that this technology alone had the potential to generate over €750 billion of cumulative economic benefits and an additional 2.4 million jobs. Big data, which enables online retailers to target customers, was forecast by Cebr5 to yield benefits of over £200 billion in the UK alone between 2012 and 2017.

Gordon Earle Moore was the co-founder of the Intel Corporation no less (and still its Chairman Emeritus), who in 1965 postulated that the number of transistors in a dense integrated circuit doubles roughly every two years.1 Amazingly the prediction seems to have been proved roughly accurate even half a century on, though my friends in the industry claim that this is partly because the ‘Law’ is used as the benchmark for driving research activity. Whatever the cause, this continued improvement in technological performance means that the scope for improved applications continues to grow. And the two current most highly publicised areas in IT – cloud computing and big data – are if anything even more dependent on improved technology and in turn particularly potent generators of new applications. There has been some discussion of whether the tendency towards monopoly for parts of the IT industry such as search engines (Google), social media (Twitter and Facebook), chips (Intel), operating software (Microsoft) and hardware (Apple) will constrain growth.

‘The Economics of Information’, George J Stigler, Chicago University Journal of Political Economy, June 1961, pp213–225. 2. Originally published as ‘Metcalfe’s Law and Legacy’, Forbes ASAP, September 1993, and developed in Telecosm, George Gilder, Simon & Schuster, 1996. 3. I first presented these arguments with some accompanying detail to the IBM Computer Users Association in May 1989 – they have changed remarkably little in the past 25 years! 4. ‘The Economic Impact of Cloud Computing: a Cebr report for EMC2’, Cebr, December 2010. 5. ‘The Value of Data Equity: A Cebr report for SAS’, Cebr, April 2012. 6. ‘Britons are the biggest online shoppers in the developed world’, James Hall, Daily Telegraph, 1 Feb 2012. 7. 8. ‘Advertising Pays’, Deloitte, Jan 9.


pages: 161 words: 44,488

The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar


Airbnb, airport security, Albert Einstein, altcoin, Amazon Web Services, bitcoin, Black Swan, blockchain, business process, centralized clearinghouse, Clayton Christensen, cloud computing, cryptocurrency, disintermediation, distributed ledger, Edward Snowden,, ethereum blockchain, fault tolerance, fiat currency, global value chain, Innovator's Dilemma, Internet of things, Kevin Kelly, Kickstarter, market clearing, Network effects, new economy, peer-to-peer lending, prediction markets, pull request, ride hailing / ride sharing, Satoshi Nakamoto, sharing economy, smart contracts, social web, software as a service, too big to fail, Turing complete, web application

Blockchains are like a virtual computer somewhere in a distributed cloud that is virtual and does not require server setups. Whoever opens a blockchain node runs the server, but not users or developers. So, the blockchain is like a networked infrastructure of computing machinery. With that in mind, we could easily imagine how computer programs can run on this new infrastructure. But we should not take the cloud computing analogy literally. The blockchain infrastructure does not replace cloud computing. It unbundles it, and democratizes parts of it. More likely, the blockchain infrastructure resembles a layer of cloud computing infrastructure. Blockchain virtual machines may be too expensive if we are to literally compare their functionality to a typical cloud service such as Amazon Web Services or DigitalOcean, but they will be be certainly useful for smart contracts that execute their logic on the blockchain’s virtual machinery, or decentralized applications, also called Dapps.

The novelty with virtual machine costing is that you are paying to run the business logic on the blockchain, which is otherwise running on physical servers (on existing cloud infrastructure), but you do not have to worry about setting up these servers because they are managed by other users who are getting paid anyways for running that infrastructure via mining. Therefore, the blockchain cloud has a form of micro-value pricing model that parallels the traditional cloud computing stack, but via a new layer. It is not a physical unbundling of the cloud, rather it is a new layering of cryptography-based transaction validation and state transition recordings on a parallel, but thinner cloud. But here is the challenge to running applications on this new infrastructure: you need to do some work. That work comes in the form of adhering to a new paradigm of decentralized apps that follows a new tiered architecture coined as “web3” by Gavin Wood.6 Web3 is an architecture that runs specifically on the blockchain.

Running business logic that contains trust and verification components will be plug and play in the practical sense. Peer-to-peer decentralized base layers will be common in data storage, computing infrastructure, identity, and reputation. Decentralized trust will be relegated to the network and embedded inside the applications instead of controlled by intermediaries. University degrees in Cryptography and Game Theory will become popular. More decentralized forms of cloud computing will emerge. This all comes with one warning from a key lesson I learned during the Internet dot-com crash of the year 2000. Speed kills. Speed in hyping what the blockchain can do will end-up derailing it, putting us ahead of reality. This type of disconnect is guaranteed to disappoint those who expect benefits faster than what is possible. That said, keeping with Carlota Perez’s6 model of explaining how technological revolutions unfold, there may be no escaping the fact a crash will happen somewhere between the blockchain’s installation phase (2015–2018), and its resulting deployment phase (2018 and beyond).


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, business process, call centre, centre right, Clayton Christensen, clean water, cloud computing, corporate social responsibility, 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 supply chain, illegal immigration, immigration reform, income inequality, indoor plumbing, Internet of things, invention of the steam engine, inventory management, Jeff Bezos, job automation, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, low skilled workers, Lyft, Mark Zuckerberg, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, 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, TaskRabbit, Thomas L Friedman, transaction costs, Transnistria, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra

Google started as a search engine and is now also becoming a car company and a home energy management system. Apple is a computer manufacturer that is now the biggest music seller and is also going into the car business, but in the meantime, with Apple Pay, it’s also becoming a bank. Amazon, a retailer, came out of nowhere to steal a march on both IBM and HP in cloud computing. Ten years ago neither company would have listed Amazon as a competitor. But Amazon needed more cloud computing power to run its own business and then decided that cloud computing was a business! And now Amazon is also a Hollywood studio. On January 12, 2016, ran a story about the Golden Globes award ceremony that began: “I want to thank Amazon, Jeff Bezos…” Those words were spoken at a Hollywood awards show [by the director Jill Soloway] for the first time on Sunday as Amazon’s comedic television series Transparent picked up two Golden Globe awards, beating shows from HBO, Netflix, and the CW.

., high-speed Internet in Chávez, Hugo Chesky, Brian chess Chicago Mercantile Exchange chickens, poverty and child marriage child mortality Children First Child Tax Credit China; as authoritarian state; “century of humiliation” in; debt of; Madagascar and; nationalism in; nuclear weapons of; 2015 economic slowdown in; U.S. relations with; workforce in China Daily “China Shock, The” (Autor) Chipman, John chlorofluorocarbons Chopra, Karan Chow, Alex Yong-Kang Citibank Citizens United decision Citrix civic idealism Civilian Conservation Corps (CCC) civil liberties civil rights, movements for Civil Rights Act (1964) Clapper, James clean energy Clear Channel Outdoor Inc. climate change; acceleration of; in Africa; agriculture and; biodiversity loss and; black elephants in; developing countries and; in Earth history; extreme weather in; geopolitics and; Moore’s law and; population growth and; Republican denial of; 2016 Paris conference on; weak states and Clinton, Bill Clodd, Edward cloud computing, see supernova (cloud computing) Coast Guard Academy, U.S. Codecademy Code Division Multiple Access (CDMA) Coen, Joel and Ethan Cold War; U.S. economic growth in; U.S.-Soviet competition for allies in Coleman, David collaboration, software innovation and College Advising Corps College Board college degrees, skill sets and colleges: continuous innovation in; traditional role of Collins, Thomas J.

“That’s because technology stands on its own shoulders—each generation of invention stands on the inventions that have come before,” said Teller. “So by 1900, it was taking twenty to thirty years for technology to take one step big enough that the world became uncomfortably different. Think of the introduction of the car and the airplane.” Then the slope of the curve started to go almost straight up and off the graph with the convergence of mobile devices, broadband connectivity, and cloud computing (which we will discuss shortly). These developments diffused the tools of innovation to many more people on the planet, enabling them to drive change farther, faster, and more cheaply. “Now, in 2016,” he added, “that time window—having continued to shrink as each technology stood on the shoulders of past technologies—has become so short that it’s on the order of five to seven years from the time something is introduced to being ubiquitous and the world being uncomfortably changed.”


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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, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, distributed ledger, Edward Snowden, Elon Musk,, ethereum blockchain, Galaxy Zoo, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loose coupling, loss aversion, Lyft, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, Network effects, new economy, Oculus Rift, offshore financial centre, p-value, PageRank, pattern recognition, Paul Graham, 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, Tyler Cowen: Great Stagnation, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator

Just imagine what that will make possible. When Marc Andreessen proclaimed in a 2011 Wall Street Journal article that “software is eating the world,” he was addressing this very phenomenon. Andreessen, who helped invent the Internet browser and is now one of Silicon Valley’s most powerful venture capitalists, argued that in every industry, and at every level, software is automating and accelerating the world. Cloud computing and the app store ecosystems are clear testaments to this trend, with the Apple and Android platforms each hosting more than 1.2 million applications programs, most of them crowdsourced from customers. Nowhere is this staggering pace of change more apparent than with the consumer Internet. Many products are now launched early—unfinished and in perpetual beta—for the sole purpose of gathering data from users as early as possible to determine how to “finish” the product.

The era of traditional, hierarchical market domination by dinosaur companies is coming to an end. The world now belongs to smarter, smaller and faster-moving enterprises. This is certainly true now for information-based industries, and it will soon be true for more traditional industries as well. 7. Rent, Don’t Own An important mechanism empowering individuals and small teams everywhere is low-cost access to technology and tools. Emblematic of this new reality is cloud computing, which offers the ability to store and manage massive amounts of information with unlimited processing, all on a cost-per-use basis requiring no upfront costs or capital investments. In practice, this makes memory almost free. The cloud also puts small companies on the same footing as—or even gives them an advantage over—big companies, which are burdened by expensive internal IT operations.

CHAPTER SIX Starting an ExO From the dawn of the Internet, we’ve seen fundamental changes in how businesses are built and grown. In particular, the earliest playbook for building a hyper-growth company emerged during the dot-com boom of 1998 to 2000. That narrative gained a new chapter in 2005 with the rise of social media, and 2008 saw yet another chapter thanks to the widespread availability of low-cost cloud computing. Today, we are seeing the addition of the most important text yet with the rise of the Exponential Organization. Driven by accelerating technologies, ExOs allow us to organize ourselves in new ways to tap into this information-enabled world. Local Motors is a good example of an ExO startup. Founded by Jeff Jones and Jay Rogers in 2007, and based in Phoenix, Arizona, it is a global co-creation platform that empowers its community to design, build and sell custom-built vehicles.


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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, 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, Jacquard loom, Jane Jacobs, jitney, John Snow's cholera map, Khan Academy, Kibera, knowledge worker, load shedding, M-Pesa, Mark Zuckerberg, megacity, mobile money, mutually assured destruction, new economy, New Urbanism, Norbert Wiener, Occupy movement, openstreetmap, packet switching, patent troll, 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 Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, 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, Upton Sinclair, uranium enrichment, urban decay, urban planning, urban renewal, Vannevar Bush, working poor, working-age population, X Prize, Y2K, zero day, Zipcar

According to Massoud Amin of the University of Minnesota, power outages and power quality disturbances cost the US economy between $80 billion and $188 billion a year.32 A back-of-the-envelope calculation published by International Working Group on Cloud Computing Resiliency tagged the economic cost of cloud outages between 2007 and mid-2012 at just $70 million (not including the July 2012 Amazon outage).33 But as more and more of the vital functions of smart cities migrate to a handful of big, vulnerable data centers, this number is sure to swell in coming years. Cloud-computing outages could turn smart cities into zombies. Biometric authentication, for instance, which senses our unique physical characteristics to identify individuals, will increasingly determine our rights and privileges as we move through the city—granting physical access to buildings and rooms, personalizing environments, and enabling digital services and content.

The grass roots may be a source of new ideas, but what they need is someone who can design and deliver a robust infrastructure that is centrally planned to be safe, efficient, and reliable at a reasonable cost. To an extent, they’re right. Scaling up things that work at the grass roots is a challenge few have overcome. Foursquare, even with all its resources, went through a wrenching series of outages before it was able to work out a scalable database scheme (although one of the worst problems was caused by an outage on Amazon’s cloud-computing services, the epitome of large-scale smart infrastructure). Even when they can manage the technical hurdles that come with growth, many civic hacks never get that far. They solve a problem for a small group of users, but fail to sustain the effort to refine their design into something that can connect to a larger audience. As DIYcity’s Geraci explained, “it’s dead simple to prototype version one of a smart city app.

But Moldova was also an opportunity to airlift the same ideas about openness that Zoellick was using to reinvent the bank and drop them onto an entire country. e-Transformation aimed to sweep aside Moldova’s entire Soviet-era paper-based bureaucracy and put all government services online. Even in 2010, basic transactions—such as obtaining an exit visa to work overseas—required a long and costly trip to the capital. With $23 million in loans from the World Bank, parceled out over five years, the new government would build a “g-cloud” (a cloud-computing infrastructure that would allow for the delivery of services to both fixed and mobile devices), create a new digital citizen-identity program, and rewrite legislation to encourage private investment in online services. In a country where most rural people still stored their savings under their mattress or in a hole in the backyard, new rules would allow mobile banking. Zoellick spent an hour and a half of his day in Moldova at our workshop (just one of several more conventional programs launched that day).


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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, 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, Edward Snowden, Elon Musk,, Eratosthenes, 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, intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Jony Ive, Julian Assange, Khan Academy, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, performance metric, personalized medicine, Peter Thiel, phenotype, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, 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, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, WikiLeaks, working poor, Y Combinator

The computational future of energy and the infrastructural program of computation form such a coil, one end feeding on the other like Ouroboros, the ancient symbol of a snake eating its own tail. Whether or not the risks associated with the energy costs of Stack infrastructure will outpace the efficiencies provided by calculative technologies as they become pervasive across industrial sectors is unknown, and probably unknowable at the moment. Prognostications vary from measured good news to very bad news. According to a Greenpeace report on cloud computing and climate change, the electricity consumed by cloud computing globally will increase from 632 billion kilowatt-hours (0.6 terawatts) in 2007 to 1,963 billion kilowatt-hours (1.9 terawatts) by 2020, and the associated carbon dioxide equivalent emissions would reach 1.034 megatons (currently the world economy's total energy appetite is roughly 15 terawatts). If imagined as an emergent nation-state, the Cloud would be today the fifth largest consumer of electricity, ahead of India, Germany, Canada, France, Brazil, and the United Kingdom.

Climate Group, “SMART 2020: Enabling the Low Carbon Economy in the Information Age,” 2008, 58.  For a taste of that ecstasy, 59.  See Nick Land, “Lure of the Void, pt. 1,” August 2012, 60.  See Pete Foster, “Cloud Computing—a Green Opportunity or Climate Change Risk?” Guardian, August 18, 2011. 61.  On smart grids and data ownership, see Jon Bruner, “Two Crucial Questions for the Smart Grid,” O’Reilly Radar, November 5, 2012, 62.  See Sally Daultrey, “Adaptation on the Roof of the World,” December 30, 2010, 63. 

Unlike modern political geography, which divided up horizontal maps, Stack geography also vertically layers spaces on top of one another. Instead of surveying all the various forms of planetary-scaled computation—cloud computing, smart cities, ubiquitous computing, massive addressing systems, next-generation interfaces, nonhuman users, and so on—as different genres or species of computing, each off on its own, this model locates them on layers of a consolidated metaplatform, an accidental megastructure. We observe these bottom-up from the Earth layer up to the User layer. Energy drawn from planetary resources at the Earth layer drives Cloud computation, and its global platforms organize new political topologies. The City layer is animated by those Cloud platforms from within, organizing things, events, and relations at the Address layer into Interfacial regimes that provide a window into the whole system for Users.


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Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr


23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, business intelligence, call centre, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, David Brooks, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, Frederick Winslow Taylor, Google Glasses, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, John von Neumann, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!

Its customers provide a window into the progress data techniques are making, as well as the challenges, across a spectrum of industries. IBM itself has lined up its research, its strategy, and its investment behind the big-data business. “We are betting the company on this,” Virginia Rometty, the chief executive, told me in an interview. But for IBM, big data is a threat as well as an opportunity. The new, low-cost hardware and software that power many big-data applications—cloud computing and open-source code—will supplant some of IBM’s traditional products. The company must expand in the new data markets faster than its old-line businesses wither. No company can match IBM’s history in the data field; the founding technology of the company that became IBM, punched cards, developed by Herman Hollerith, triumphed in counting and tabulating the 1890 census, when the American population grew to sixty-three million—the big data of its day.

The goal is to nurture a flourishing commercial ecosystem, in the way that Apple’s iOS and Google’s Android have done in smartphone software, and Microsoft’s Windows did in personal computer software. In early 2014, IBM also focused the activities of the 3,000 researchers in its labs to make data projects the priority. The realignment, according to Rometty, is the most significant shift at IBM research since the 1990s, when retooling for the Internet era became the imperative. A program of fundamental research, as in the materials science of computer hardware, will continue. Along with cloud computing, research will be concentrated on big-data projects in specific industries and the underlying machine-learning technologies used to find answers and insights in data, as Watson does. IBM refers to these machine-learning capabilities as “cognitive” computing. Pick your term, Rometty says—big data, analytics, or cognitive—but it’s all in the same data neighborhood, and it is the direction in which IBM is unequivocally headed.

And a sizable swath of IBM’s services business involves engineers writing applications, using traditional software, for corporate customers. Today’s big-data applications typically use cloud-style computing in which processing and software are delivered remotely, from distant data centers, over the Internet. Under Rometty, IBM is making huge investments in the future—big-data technology and cloud computing. But the dilemma facing the company is whether the new business will grow faster than the old business erodes. In early 2014, when I spoke to Rometty, she talked of the lessons she had learned about the imperative of constant corporate evolution. “Don’t fight cannibalization,” she says at one point. Trying to preserve the past is a formula for failure, she notes, a lesson IBM learned the hard way in the 1990s.


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


23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, 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, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, 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, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, 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, 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 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, WikiLeaks, Y Combinator, zero day

Cloudy Weather Ahead Though massive amounts of data are leaking from our mobile devices, an increasing number of big-data risks come from the world of “cloud computing.” The cloud refers to the massive network of computing resources available online and the practice of using these remote servers to store, manage, and process the world’s information. The changing paradigm in computing means that less information is stored locally on our machines and is instead being hosted elsewhere on earth. We mostly do not buy software anymore; we just rent it or receive it for free using a new business model known as Software as a Service (SaaS). On the personal front, cloud computing means Google is storing our mail, Instagram our photographs, and Dropbox our documents—not to mention what mobile phones are automatically uploading to the cloud for us.

The availability of such cheap computing resources and a growing array of SaaS offerings will have untold positive impact on personal productivity, entrepreneurship, and innovation, which in turn will only hasten the inevitable transition to cloud computing. But with this move to store all available data in the cloud come additional risks. Think of the largest hacks to date—Target, Heartland Payment Systems, TJX, and Sony PlayStation Network. All of these thefts of hundreds of millions of accounts were made possible because the data were stored in the same virtual location. The cloud is equally convenient for individuals, businesses, and criminals. To deal with these risks, organizations such as the nonprofit Cloud Security Alliance have been formed to promote best practices and improve security in the age of cloud computing. The virtualization and storage of all of these data are highly complex and raise a wide array of security, public policy, and legal issues.

As a result, we’ve entered the age of weaponized computing, where literally anybody with a few dollars to spare can have access to previously unimaginable levels of computing power to use for good or ill. For example, the hackers who broke into the Sony PlayStation Network used the vast computing power of Amazon’s cloud-computing services to break several of Sony’s encryption keys, providing access to hundreds of thousands of user accounts and credit card details. This “cloud cracking” significantly reduces the time it takes to break even the strongest passwords and in the process leaves us all less secure. Today, using the distributed computing power of the cloud and tools such as CloudCracker, you can try 300 million variations of your potential password in about twenty minutes at a cost of about $17. This means that anyone could rent Amazon’s cloud-computing services to crack the average encryption key protecting most Wi-Fi networks in just under six minutes, all for the paltry sum of $1.68 in rental time (sure to drop in the future thanks to Moore’s law).


pages: 518 words: 107,836

How Not to Network a Nation: The Uneasy History of the Soviet Internet (Information Policy) by Benjamin Peters


Albert Einstein, Andrei Shleifer, Benoit Mandelbrot, bitcoin, Brownian motion, Claude Shannon: information theory, cloud computing, cognitive dissonance, computer age, conceptual framework, crony capitalism, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, Dissolution of the Soviet Union, double helix, Drosophila, Francis Fukuyama: the end of history, From Mathematics to the Technologies of Life and Death, hive mind, index card, informal economy, invisible hand, Jacquard loom, Jacquard loom, John von Neumann, Kevin Kelly, knowledge economy, knowledge worker, linear programming, mandelbrot fractal, Marshall McLuhan, means of production, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Network effects, Norbert Wiener, packet switching, pattern recognition, Paul Erdős, Peter Thiel, RAND corporation, rent-seeking, road to serfdom, Ronald Coase, scientific mainstream, Steve Jobs, Stewart Brand, stochastic process, technoutopianism, The Structural Transformation of the Public Sphere, transaction costs, Turing machine

Vladimir Starovsky, the head of the Central Statistical Administration, “harshly objected to the whole project,” Glushkov recalled in the late 1960s—out of opposition not to the economic reform but to the prospect that the Central Statistical Administration would have to cede control over some element of the governance of his administrative turf (economic statistics) to future OGAS directors. Starovsky rejected the remote-access portion of Glushkov’s proposal (a precursor to “cloud computing”). If realized, the OGAS was going to provide access to information and processing power to any authenticated user anywhere on the network. Even though the permission hierarchy for authenticated users presumably could still reaffirm the strong hierarchical structure supporting his administration, Starovsky opposed what we now recognize as a cloud computing provision as being politically “unnecessary” because the Central Statistical Administration was “organized by the initiative of Lenin” and already does everything that Lenin asked of it. Reversing Lenin’s original question, “What is to be done?

This kernel vision of a network as an expression of the nervous system of a factory, writ large across a nation, magnified the image of the workplace until it incorporated the whole command economy—a sort of simultaneously metaphorical and mechanical collectivization of the industrial household (or what Hannah Arendt calls the oikos). The OGAS Project might be seen as preceding, although not precipitating, the current trends in so-called cloud computing. The national network was to provide “collective access,” “remote access,” and “distance access” on a massive scale to civilian users who could “access,” “input,” “receive,” and “process” data related to the command economy (such older terms appear to bear more descriptive heft than the modern computing metaphors such as upload, download, share, and stream). The decentralized network was designed so that information for economic planning could be transmitted, modified, and managed in relative real time up, down, and laterally across the networked administrative pyramid.

Figure 4.1 Map of the three tiers (I, II, III) of planned computing center sites behind the OGAS (All-State Automated System), 1964. Figure 4.2 Map of the EGSVTs (Unified State Network of Computing Centers) that were projected to be operational in 1990, possibly from 1964.4 As communication scholar Vincent Mosco has recently noted, the Soviets offer perhaps the first glimpse of the modern imagining of decentralized remote computing (what recently has been called cloud computing) on a massive scale.5 In Glushkov’s design, the network would afford interactive and collective remote access and communication vertically up and down the planning pyramid and horizontally among peer and associated computing centers. Glushkov writes: “the characteristic quality of the network was a distributed database with zero-address access from any point of the system to all the information after automatic verification of the qualified user.”


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,, 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, knowledge economy, knowledge worker, litecoin, M-Pesa, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, new economy, offshore financial centre, open economy, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Satoshi Nakamoto, 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, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

Sanger, “Obama Had Security Fears on JPMorgan Data Breach,” New York Times, October 8, 2014, Items of interest will be located: Spencer Ackerman, “CIA Chief: We’ll Spy on You through Your Dishwasher,” Wired, March 15, 2012, One study pegged the lost business: Daniel Castro, “How Much Will PRISM Cost the US Cloud Computing Industry?” Information Technology and Innovation Foundation, August 2013, In February 2015, President Obama: “Executive Order: Improving Critical Infrastructure Cybersecurity,” White House, February 12, 2013, Justifying the unusual step: Joyce Brayboy, “Army Cyber Defenders Open Source Code in new GitHub Project,” US Army, January 28, 2015,

By taking North Korea offline, they were reminding the North Koreans who controls their networks, and they were doing a favor for the United States that served their own purposes. CYBERATTACKING EVERYTHING As the Internet grows, it is expanding not simply to new users but to entirely new devices, well beyond standard computers, tablets, and smartphones. Electronic communications and electronic sensors have been around for some time, but the costs of sensors and data storage have recently plummeted—in part due to cloud computing. 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.”

The Code War has no such simple organization, and traditional alliances have fractured. After the revelations of Edward Snowden, the governments and public of European countries condemned American cyberpractices. Billions of dollars of business were lost by American telecommunications and technology companies, which were no longer trusted. One study pegged the loss to American businesses in the cloud computing industry alone at between $22 billion and $25 billion over three years. Yet there is little to no prospect for any sort of short-term progress to be made developing international law, treaties, or other frameworks establishing norms and rules for cyberactivity. The United States won’t agree to anything that the Europeans would demand that limits intelligence-gathering activities. The Chinese won’t admit to, much less agree to, anything related to industrial espionage.


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, connected car, corporate social responsibility, crowdsourcing, Elon Musk, financial innovation, global supply chain, income inequality, industrial robot, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, 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, ride hailing / ride sharing, 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, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar

A frugal services revolution GAPPAA.ORG Companies are finding new, highly effective and affordable ways to deliver services or services bundled with products. Such business models include: software as a service (SaaS) in computing; power by the hour in aircraft engines; massive open online courses (MOOCs) in education; hub-and-spoke and yield management models in airlines; online retailing; and cloud computing. By flexing their assets, airlines such as Southwest Airlines, easyJet and Ryanair have created a new, low-cost market segment for flyers within the US and Europe, and have succeeded in challenging long-haul incumbents. First, the low-cost carriers rebased the existing airline business model by maximising the time that their most valuable assets – their aircraft – spend in the air, and reducing the time they spend on the ground.

In retailing, Amazon has from the outset sought ways to flex its assets. The company first used its book distribution platform to sell music and household goods as well. It then used its installed customer base for peer-to-peer sales, as on eBay. Amazon then made and sold consumer electronics such as the Kindle (on which to read its books) and market-research tools such as mTurk, to captive customers. Lastly, it used its server space for cloud computing, which it sells as a service. Given its interest in drones as a mode of product delivery, Amazon might one day expand into travel and transport. Meanwhile, a wave of creative destruction is crashing through the education industry and, by extension, the textbook publishing world. The arrival of MOOCs has threatened higher-education models. Startups such as Coursera, Udacity and EdEx in the US and FutureLearn in the UK are now offering courses on an ever-widening range of subjects to students worldwide.

SNCF has also tied up with Orange and Total to launch Ecomobilité Ventures, Europe’s first multi-corporate investment fund, which invests in a portfolio of promising start-ups that can collectively deliver end-to-end solutions in sustainable mobility. Non-competing brands can also work together, not only to respond to the current needs of their shared customers, but also to anticipate their future needs. Simon Mulcahy, senior vice-president and managing director of financial services industry at Salesforce. com, which offers a customer relationship management platform based on cloud computing, encourages companies to adopt a wide lens to perceive their customer needs through the diverse perspectives of other industries, and to address these needs by borrowing best practices from other sectors.9 For example, diverse industries such as construction, interior design and renovation, food, retail, entertainment, logistics, health, financial services, energy and communication all share a single customer in one particular location: their home.


pages: 261 words: 10,785

The Lights in the Tunnel by Martin Ford


Albert Einstein, Bill Joy: nanobots, Black-Scholes formula, call centre, cloud computing, collateralized debt obligation, credit crunch, double helix,, factory automation, full employment, income inequality, index card, industrial robot, inventory management, invisible hand, Isaac Newton, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, knowledge worker, low skilled workers, moral hazard, pattern recognition, prediction markets, Productivity paradox, Ray Kurzweil, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, strong AI, superintelligent machines, technological singularity, Thomas L Friedman, Turing test, Vernor Vinge, War on Poverty

The software to participate in these programs can be downloaded from the web.* In the future, we can anticipate that grid computing will become increasingly important. In addition, it is already evolving into what computer scientists refer to as “cloud computing.” Essentially this will amount to a new architecture for leveraging the power of huge numbers of computers on an as needed basis: computational capability, together with specific applications, will be delivered as though it were a utility much like electric power. The trend toward grid and cloud computing offers a fantastic opportunity to deploy our incredible newcomputational capacity in areas that will undoubtedly bring positive advances in fields such as science and medicine. Our next example, however, is far less benign. Meltdown As nearly everyone knows, the “subprime” meltdown of 2007 was triggered when borrowers who did not have the best credit ratings began to default on their mortgages.

§ Help promote the book by writing a reviewon your blog or website or on, or by telling your friends, students or coworkers about the book. Feel free to email the PDF file to anyone who might be interested. CONTENTS Introduction 1 Chapter 1: The Tunnel The Mass Market Visualizing the Mass Market Automation Comes to the Tunnel A Reality Check Summarizing 7 10 11 17 21 24 Chapter 2: Acceleration The Rich Get Richer World Computational Capability Grid and Cloud Computing Meltdown Diminishing Returns Offshoring and Drive-Through Banking Short Lived Jobs Traditional Jobs: The “Average” Lights in the Tunnel A Tale of Two Jobs “Software” Jobs and Artificial Intelligence Automation, Offshoring and Small Business “Hardware” Jobs and Robotics “Interface” Jobs The Next “Killer App” Military Robotics Robotics and Offshoring Nanotechnology and its Impact on Employment The Future of College Education Econometrics: Looking Backward The Luddite Fallacy 27 28 39 41 43 47 54 57 58 63 67 74 75 80 81 85 86 87 90 93 95 Copyrighted Material – Paperback/Kindle available @ Amazon THE LIGHTS IN THE TUNNEL / vi A More Ambitious View of Future Technological Progress: The Singularity A War on Technology 100 103 Chapter 3: Danger The Predictive Nature of Markets The 2008-2009 Recession Offshoring and Factory Migration Reconsidering Conventional Views about the Future The China Fallacy The Future of Manufacturing India and Offshoring Economic and National Security Implications for the United States Solutions Labor and Capital Intensive Industries: The Tipping Point The Average Worker and the Average Machine Capital Intensive Industries are “Free Riders” The Problem with Payroll Taxes The “Workerless” Payroll Tax “Progressive” Wage Deductions Defeating the Lobbyists A More Conventional View of the Future The Risk of Inaction 107 107 110 113 115 117 124 127 Chapter 4: Transition The Basis of the Free Market Economy: Incentives Preserving the Market Recapturing Wages Positive Aspects of Jobs The Power of Inequality Where the Free Market Fails: Externalities 156 158 159 162 168 169 170 128 131 131 135 138 140 142 144 146 149 152 Copyrighted Material – Paperback/Kindle available @ Amazon Contents / vii Creating a Virtual Job Smoothing the Business Cycle and Reducing Economic Risk The Market Economy of the Future An International View Transitioning to the New Model Keynesian Grandchildren Transition in the Tunnel 172 179 180 183 185 189 192 Chapter 5: The Green Light Attacking Poverty Fundamental Economic Constraints Removing the Constraints The Evolution toward Consumption The Green Light 194 196 201 202 204 207 Appendix / Final Thoughts Are the ideas presented in this book WRONG?

.* I have the feeling that this staggering increase in our computational capability represents a pent up resource that is poised to burst out in new and unexpected ways. In the future, we can expect that many more traditional technologies, and in fact nearly every aspect of our lives, will change—perhaps very rapidly—in ways that we cannot foresee. As examples of what we might expect, let’s look at two things that have already occurred: one that, at least so far, has been generally positive, and one that has been decidedly negative. Grid and Cloud Computing Grid computing is a rapidly growing field that focuses on leveraging not just the power of an individual computer, but also the large number of such computers now available. The idea is to tie many computers together using special software. A big computational problem can then be broken down into pieces and distributed across hundreds or even thousands of computers so that they can work on it simultaneously.


pages: 188 words: 9,226

Collaborative Futures by Mike Linksvayer, Michael Mandiberg, Mushon Zer-Aviv


4chan, Benjamin Mako Hill, British Empire, citizen journalism, cloud computing, collaborative economy, corporate governance, crowdsourcing, Debian,, Firefox, informal economy, jimmy wales, Kickstarter, late capitalism, loose coupling, Marshall McLuhan, means of production, Naomi Klein, Network effects, optical character recognition, packet switching, postnationalism / post nation state, prediction markets, Richard Stallman, semantic web, Silicon Valley, slashdot, Slavoj Žižek, stealth mode startup, technoutopianism, the medium is the message, The Wisdom of Crowds, web application

We’ve made a balance between the absolute don’t-use-other-people’scomputers argument and the maybe-it’s-OK-sometimes argument in the Franklin Street Statement. Time will tell whether we can cra a culture around Free Network Services that is respectful of users’ autonomy, such that we can use other computers with some measure of confidence.” —Evan Prodromou, “RMS on Cloud Computing: “Stupidity””, CC BY-SA, <> 109 The Franklin Street Statement on Freedom and Network Services is an initial a empt to distill actions that users, service providers (the “other people” here), and developers should take to retain the benefits of free so ware in an era of so ware services: “The current generation of network services or So ware as a Service can provide advantages over traditional, locally installed so ware in ease of deployment, collaboration, and data aggregation.

., beholden to users and volunteers, not investors and employees. Maybe. Would I be less sanguine about the long term prospects of Wikipedia if it were forprofit? I don’t know of evidence for or against this feeling. —Mike Linksvayer, “Constitutionally open services”, CC0, <> So ware services are rapidly developing and subjected to much hype, o en referred to the buzzword Cloud Computing. However, some of the most potent means of encouraging autonomy may be relatively boring—for example, making it easier to maintain one’s own computer and deploy slightly customized so ware in a secure and foolproof fashion. Any such development helps traditional users of free so ware as well as makes doing computing on one’s own computer (which may be a “personal server” or virtual machine that one controls) more a ractive. 112 Perhaps one of the most hopeful trends is relatively widespread deployment by end users of free so ware web applications like WordPress and MediaWiki.

Previously he co-founded Bitzi, an early open data/open content/mass collaboration service, and worked as a web developer and so ware engineer. In 1993 he published one of the first interviews with Linus Torvalds, creator of Linux. He is a co-founder and currently active in, which investigates and works to further the role of free so ware, culture, and data in an era of so ware-as-a-service and cloud computing. His chapter on “Free Culture in Relation to So ware Freedom” was published in FREE BEER, a book wri en by speakers at FSCONS 2008. Linksvayer holds a degree from the University of Illinois at UrbanaChampaign in economics, a field which continues to strongly inform his approach. He lives in Oakland, California. 146 Michael Mandiberg is known for selling all of his possessions online on Shop Mandiberg, making perfect copies of copies on A, and creating Firefox plugins that highlight the real environmental costs of a global economy on


pages: 320 words: 87,853

The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale


Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, asset-backed security, Atul Gawande, bank run, barriers to entry, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, cloud computing, collateralized debt obligation, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, Edward Snowden,, Fall of the Berlin Wall, Filter Bubble, financial innovation, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, search engine result page, shareholder value, Silicon Valley, Snapchat, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks

Bob Brown, “What Is a ‘Certified EHR’?,” Journal of Health Care Compliance 12, No. 1 (2010): 31– 67. See generally Nicolas P. Terry, “Certification and Meaningful Use: Reframing Adoption of Electronic Records as a Quality Imperative,” Indiana Health Law Review 8 (2011): 45–70 (examining meaningful use as the condition for receiving EHR subsidy funds). 32. Cloud computing transfers “application software and server-based databases to centralized, large data centers.” Jared A. Harshbarger, “Cloud Computing Providers and Data Security Law,” Journal of Technology Law and Policy 16 (2011): 230–231. 33. David A. Moss, When All Else Fails: Government as the Ultimate Risk Manager (Cambridge, MA: Harvard University Press, 1999). 34. Richard A. Posner, A Failure of Capitalism: The Crisis of ’08 and the Descent into Depression (Cambridge, MA: Harvard University Press, 2009); Andrew Ross Sorkin, Too Big to Fail: The Inside Story of How Wall Street and Washington Fought to Save the Financial System— and Themselves (New York: Viking Penguin, 2009). 35.

Others will invest, as venture capitalist Marc Andreessen recommends. Though he strikes fear into publishers, Amazon’s Jeff Bezos has not yet reduced writers at his newspaper (the Washington Post) to the status of Mechanical Turkers or warehouse pickers.213 But we should not assume media independence as tech firms swallow more of the revenue that might have once gone to journalists. After Amazon inked a $600 million deal to provide the CIA with cloud computing services, 30,000 people petitioned the Post with the message “Washington Post: Readers Deserve Full Disclosure in Coverage of CIA.”214 Such inquiries will only become more common as Washington and Silicon Valley develop more partnerships for information dominance. Of course, we can see why large firms want to keep their industry (and government) alliances under wraps. People want to feel like there is someone looking out for them.

Google found itself needing more compelling content, and that content would only materialize for a price.216 These are trust issues. In a classic example of what philosopher Langdon Winner called “technological somnambulism,”217 we have given the search sector an almost unimaginable power to determine what we see, where we spend, how we perceive. Top legal scholars have already analogized the power relationships in virtual worlds and cloud computing to medieval feudalism.218 Technological advance goes hand-in-hand with politico-economic regression. Toward a Digital New Deal In the late 1990s, tech enthusiasts looked to search engines as an extraordinary democratization of the Internet. They permitted content creators from all over the world to reach far-flung audiences. Web 2.0 promised even more “democratization” by enabling selforganization of virtual communities.


pages: 56 words: 16,788

The New Kingmakers by Stephen O'Grady


Amazon Web Services, barriers to entry, cloud computing, correlation does not imply causation, crowdsourcing, DevOps, Jeff Bezos, Khan Academy, Kickstarter, Mark Zuckerberg, Netflix Prize, Paul Graham, Silicon Valley, Skype, software as a service, software is eating the world, Steve Ballmer, Steve Jobs, Tim Cook: Apple, Y Combinator

Anyone with a credit card could rent hardware and storage space, dynamically, for minutes, hours, months, or years. Practically speaking, AWS, and the cloud market it created, removed the final cost constraint on developer creativity. As Flip Kromer, CTO of data startup Infochimps put it, “EC2 means anyone with a $10 bill can rent a 10-machine cluster with 1TB of distributed storage for 8 hours.” For all of the focus on the technology of cloud computing, its real import has been the elimination of up-front capital expense costs and making any class of hardware instantly accessible. Hardware had certainly been available via a network before, but never this cheaply, and never in such an on-demand fashion. With the creation of the cloud market, developers had, for the first time in history, access to both no-cost software and infrastructure affordable for even an individual.

Developers are attracted to its platform because of the size of the market…those developers create thousands of new applications…the new applications give consumers thousands of additional reasons to buy Apple devices rather than the competition…and those new Apple customers give even more developers reason to favor Apple. Apple not only profits from this virtuous cycle, it benefits from ever-increasing economies of scale, realizing lower component costs than competitors. None of which would be possible without the developers Apple has recruited and, generally, retained. Amazon Web Services The company that started the cloud computing craze was founded in 1994 as a bookstore. The quintessential Internet company, competed with the traditional brick-and-mortar model via an ever-expanding array of technical innovations: some brilliant, others mundane. The most-important of Amazon’s retail innovations co-opted its customers into contributors. From affiliate marketing programs to online reviews, Amazon used technology to enable its customers’ latent desire to more fully participate in the buying process.


pages: 281 words: 95,852

The Googlization of Everything: by Siva Vaidhyanathan


1960s counterculture, AltaVista, barriers to entry, Berlin Wall, borderless world, Burning Man, Cass Sunstein, choice architecture, cloud computing, computer age, corporate social responsibility, correlation does not imply causation, data acquisition, death of newspapers, don't be evil, Firefox, Francis Fukuyama: the end of history, full text search, global village, Google Earth, Howard Rheingold, informal economy, information retrieval, Joseph Schumpeter, Kevin Kelly, knowledge worker, libertarian paternalism, market fundamentalism, Marshall McLuhan, means of production, Mikhail Gorbachev, Naomi Klein, Network effects, new economy, Nicholas Carr, PageRank, pirate software, Ray Kurzweil, Richard Thaler, Ronald Reagan, side project, Silicon Valley, Silicon Valley ideology, single-payer health, Skype, social web, Steven Levy, Stewart Brand, technoutopianism, The Nature of the Firm, The Structural Transformation of the Public Sphere, Thorstein Veblen, urban decay, web application

Because of the mistakes Google made in the Books program, federal regulators and many important segments of the reading public grew concerned with the scope of Google’s ambitions.15 In the public mind, Google’s informal motto, “Don’t be evil,” resonates more than its formal mission statement. But the mission statement is far more interesting. It is a stunning statement. What other institution would define changing the world as its unifying task? The Web-using public has adopted Google services at an astounding rate, and Google has expanded to master widely used Internet functions such as Web search, e-mail, personal “cloud computing,” and online advertising. Chapter 6 and the conclusion consider how Google is changing and challenging both the technologies and the companies that govern human I NT ROD UCT I ON 11 communication. The book concludes with a call for more explicitly public governance of the Internet. Such governance might take the form of greater privacy guarantees for Web users or strong antitrust scrutiny of companies like Google.

It now offers online software such as a word processor, spreadsheets, presentation software, and a REN D E R UNTO CA ESA R 17 calendar service—all operating “in the cloud” and thus freeing users from managing multiple versions of their files and applications on different computers, and easing collaboration with others. In 2008 Google released its own Web browser called Chrome, despite many years of collaborating with the Mozilla foundation in supporting the opensource Firefox browser. And in 2009 it previewed its Chrome operating system for cloud computing, a direct assault on Microsoft’s core product, Windows. It hosts health records online. On top of all that, since its beginning in 2004, its Google Books project has scanned millions and millions of volumes and has made many of them available online at no cost, simultaneously appropriating the functions of libraries on the one hand and the rights of publishers on the other. In 2007 Google announced plans for a mobile-phone operating system and attempted, but failed, to change the ways that the United States government allocates radio bandwidth to mobile companies in an attempt to open up competition and improve service.11 And since 2005 the company has been Googlizing the real world through Google Maps, Street View, and Google Earth, a service that allows users to manipulate satellite images to explore the Earth from above.

However, university officials who negotiate contracts with Google often must sign nondisclosure agreements to ensure that Google’s competitors do not have too clear a picture of what the company is doing with its academic partners. 196 TH E G OOGL IZATION OF MEMORY Computing in the cloud is both radically empowering and potentially worrying. One downside involves the tangle of rights claims that a widespread collaboration among individual researchers, university technology-transfer offices, and major computer companies might generate.39 Such a confusing, complicated set of claims not only risks years of litigation among the parties but could attract significant antitrust scrutiny as well. Cloud computing and massive, distributed computation have already been declared the next great intellectual revolution by Wired magazine, which prides itself on predicting such trends. Its editor, Chris Anderson, wrote in June 2008 that the ability to collect and analyze almost unimaginable collections of data renders the standard scientific process of hypothesis, data collection, testing, revision, publication, and further revision almost obsolete.


pages: 319 words: 89,477

The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion by John Hagel Iii, John Seely Brown


Albert Einstein, Andrew Keen, barriers to entry, Black Swan, business process, call centre, Clayton Christensen, cleantech, cloud computing, corporate governance, Elon Musk,, future of work, game design, George Gilder, Isaac Newton, job satisfaction, knowledge economy, knowledge worker, loose coupling, Louis Pasteur, Malcom McLean invented shipping containers, Maui Hawaii, medical residency, Network effects, packet switching, pattern recognition, pre–internet, profit motive, recommendation engine, Ronald Coase, shareholder value, Silicon Valley, Skype, smart transportation, software as a service, supply-chain management, The Nature of the Firm, too big to fail, trade liberalization, transaction costs

Of course, exponential rates like these cannot be sustained forever, but for the foreseeable future the technologists driving innovation in these domains see scant evidence of a flattening of performance-improvement curves for key digital technology components—even if other advances in the labs today, such as quantum computing, might eventually leapfrog today’s technologies altogether. The absence of stabilization in the core technology components suggests that we are not likely to see stabilization in the digital infrastructure either. More than thirty years into this technology revolution, we are just now beginning to explore the contours of cloud computing. The cloud-computing approach suggests that the most efficient way to deliver digital technology is through big centralized data centers that can flexibly deliver computing, storage, and transport services to users. Given all the recent hype surrounding this new development, it is sometimes difficult to keep in mind that only a tiny fraction of the total digital technology resources is today delivered through this kind of infrastructure.

But we’re calling for something that would extend beyond institutional boundaries to connect talent wherever it resides, even outside the firm. These outside-in architectures would get their start working across enterprises, but ultimately they would penetrate back into the enterprise, where their advantages would quickly become apparent. Already we may be seeing the beginnings of this transition in the movement to cloud computing. As companies access more and more of their IT resources from cloud service-providers, these providers will learn to facilitate coordination of activities across large numbers of business partners, each of whom may have different ways of doing business as well as different terminology, policies, and procedures. This will set the stage for further evolution of IT architectures to support more complex, long-lived interactions across networks of diverse participants.12 Pull-based IT platforms represent a very tangible way to amplify the efforts of institutional leaders to move their firms from scalable push to scalable pull.

At minimal cost to SAP—relative to push models—SAP harnessed the collective power of hundreds of thousands of talented individuals to help achieve the company’s strategic goals. 10 For more about this crucial question, see John Hagel III and Marc Singer, “Un-bundling the Corporation,” Harvard Business Review, March 1, 1999, which asserts that most companies are an unnatural bundle of three very different types of businesses: They are customer-relationship businesses, infrastructure-management businesses, and product-development and innovation businesses. 11 See Thomas H. Davenport, Thinking for a Living: How to Get Better Performance and Results from Knowledge Workers (Cambridge: Harvard Business School Press, 2005). 12 Thomas B. Winans and John Seely Brown, “Cloud Computing: A Collection of Working Papers,” July 31, 2009, Deloitte Development. Chapter 7 1 Zoe Baird and James Barksdale et al., “Creating a Trusted Network for Homeland Security,” Markle Foundation, December 2, 2003, 2 See Saxby Chambliss, “Counterterrorism Intelligence Capabilities and Performance Prior to 9-11,” Subcommittee on Terrorism and Homeland Security, A Report to the Speaker of the House of Representatives and the Minority Leader, July 2002, 3 John Franke, “SAP CEO Heir-Apparent Resigns,” March 28, 2007,,,289142,sid21_gci1249379,00.html#. 4 This and other details are drawn from Daniel Roth, “Driven: Shai Agassi’s Audacious Plan to Put Electric Cars on the Road,” Wired, August 18, 2008,


pages: 227 words: 32,306

Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize Roi by Lyndsay Wise


barriers to entry, business intelligence, business process, call centre, cloud computing,, Just-in-time delivery, knowledge worker, Richard Stallman, software as a service, statistical model, supply-chain management, the market place

For instance, it may pay for a company to pay more for software if that software provides outof-the-box capabilities that limit the amount of customization required as opposed to using free software and spending months and multiple resources to get the solution up and running. So Adopting OSBI 35 even though other solutions may be less expensive in the beginning, the overall solution costs may actually be more in the long-term despite the lower initial price point. Broader deployment methods. Outside of the addition of cloud computing, the effects of diversity in deployment have had more of an indirect effect when looking at the OSBI market. Organizations can now select how they want to deploy BI. Choices include desktop, Web, hosted or as a service, and in the cloud. This relates to increased flexibility and autonomy, which transfers the power into the hands of business and technical users. In the past, BI offerings were controlled by solution providers selling their products without focusing on the intrinsic value provided to the customer.

However, it is important to note the fact that for community offerings, IT developers still remain the main access point to OSBI adoption. Obviously, with additional types of deployment available, businesses are able to pick and choose what serves them best. The same can be said within OSBI. IT developers have always been able to create customized solutions without the limitations of traditional software offerings. Add to this cloud computing options and commercial availability and OSBI expands to broader flexibility that compares with broader deployment overall. Proprietary no longer. When solution availability was limited and the market was less mature, many organizations flocked to proprietary offerings due to lack of selection and perceived viability. With few large scale BI vendors and viable industry solutions to choose from, enterprise organizations were stuck implementing large scale BI infrastructures based on integration with other proprietary offerings.

., and find solutions that meet these varying requirements. In addition to market expansion, over the past several years, BI has gone from a multi-dimensional analysis and reporting solution for the select few to an organization-wide solution used to drive business success. Its overall importance within companies keeps growing in relation to C-level executive priority and broad adoption.2 Add to this the increase in cloud computing, big data, virtualization, and expanding OS options, and businesses are now in the position to apply BI 1 For instance, those discussed in Chapter 1, including SaaS or cloud-based offerings. In Gartner’s study, Amplify the Enterprise: the 2012 CIO Agenda, Analytics and BI rate number one on what is important to CIOs minds. This study interviewed over 2300 CIOs., with the actual report being found at: 2 Using Open Source Platforms for Business Intelligence © 2012 Elsevier Inc.


pages: 502 words: 107,510

Natural Language Annotation for Machine Learning by James Pustejovsky, Amber Stubbs


Amazon Mechanical Turk, bioinformatics, cloud computing, computer vision, crowdsourcing, easy for humans, difficult for computers, finite state, game design, information retrieval, iterative process, natural language processing, pattern recognition, performance metric, sentiment analysis, social web, speech recognition, statistical model, text mining

Because so many different online platforms come with ways for users to tag or annotate their data in other ways, SSL techniques don’t require that a researcher create and annotate two separate models over the data, since one of the models is already provided by the users (though there is, of course, always some messiness in user-generated content). NLP Online and in the Cloud The idea of cloud computing has been invading nearly every aspect of people’s lives: from using cloud storage to store music and back up data to the return of the idea of distributed computers. Additionally, there has been a lot of movement to create central repositories, and more efforts to create interoperability standards as well as software that adheres to those standards. In this section we will examine some of the ways that cloud computing can affect NLP and annotation, and ways that the Internet is being used to organize NLP resources. Distributed Computing A common problem with NLP systems is that they are often very processing-intensive.

And Finally... In this chapter our goal was to show you the role that annotation is playing in cutting-edge developments in computational linguistics and machine learning. We pointed out how the different components of the MATTER development cycle are being experimented with and improved, including new ways to collect annotations, better methods for training algorithms, ways of leveraging cloud computing and distributed data, and stronger communities for resource sharing and collaboration. Because of a lack of understanding of the role that annotation plays in the development of computational linguistics systems, there is always some discussion that the role of annotation is outdated; that with enough data, accurate clusters can be found without the need for human-vetted categories or other labels.

., Clustering and Unsupervised Learning–Semi-Supervised Learning K-nearest neighbor, Other Classifiers to Know About Maximum Entropy classifiers (MaxEnt), Maximum Entropy Classifiers Naïve Bayes learning, Naïve Bayes Learning–Sentiment classification Support Vector Machine (SVM), Other Classifiers to Know About classifier algorithms, Classifier Algorithms–Other Classifiers to Know About, Decision Tree Learning–Decision Tree Learning, Other Classifiers to Know About, Other Classifiers to Know About decision tree learning, Decision Tree Learning–Decision Tree Learning macro-averaging, Other Classifiers to Know About micro-averaging, Other Classifiers to Know About closure rules, Refining Your Goal: Informativity Versus Correctness Cloud computing and NLP, NLP Online and in the Cloud–Shared Language Applications, Distributed Computing, Shared Language Resources, Shared Language Applications distributed computing, Distributed Computing shared language resources, Shared Language Resources, Shared Language Applications ClueWeb09 corpus, Corpora Today clustering, Clustering and Unsupervised Learning, Clustering and Unsupervised Learning–Semi-Supervised Learning, Clustering and Unsupervised Learning, Clustering and Unsupervised Learning, Clustering and Unsupervised Learning, Clustering and Unsupervised Learning classification vs., Clustering and Unsupervised Learning–Semi-Supervised Learning exclusive clustering, Clustering and Unsupervised Learning hierarchical clustering, Clustering and Unsupervised Learning overlapping clustering, Clustering and Unsupervised Learning probabilistic clustering, Clustering and Unsupervised Learning clustering algorithms, Clustering Cohen’s Kappa (κ), Cohen’s Kappa (κ)–Cohen’s Kappa (κ), Fleiss’s Kappa (κ), Interpreting Kappa Coefficients–Calculating κ in Other Contexts, Calculating κ in Other Contexts, Confusion Matrices and confusion matrices, Confusion Matrices Fleiss’s Kappa (κ), Fleiss’s Kappa (κ) interpreting, Interpreting Kappa Coefficients–Calculating κ in Other Contexts skewed data, potential for, Calculating κ in Other Contexts collocations, N-grams concordances, Early Use of Corpora, Early Use of Corpora, Early Use of Corpora Corpus Pattern Analysis, Early Use of Corpora Key Word in Context index (KWIC), Early Use of Corpora condition-action pair, Defining Our Learning Task conditional probability, Joint Probability Distributions Conditional Random Field models (CRF), Structured Pattern Induction, Sequence Induction Algorithms Conference on Computational Linguistics (COLING), Organizations and Conferences Conference on Natural Language Learning (CoNLL) Shared Task (Special Interest Group on Natural Language Learning of the Association for Computational Linguistics), NLP Challenges confusion matrix, Cohen’s Kappa (κ), Confusion Matrices consuming tags, Annotate with the Specification corpus analytics, Corpus Analytics–Language Models, Basic Probability for Corpus Analytics–Bayes Rule, Joint Probability Distributions–Joint Probability Distributions, Counting Occurrences–N-grams, Language Models joint probability distributions, Joint Probability Distributions–Joint Probability Distributions language models, Language Models lexical statistics for, Counting Occurrences–N-grams probability principles for, Basic Probability for Corpus Analytics–Bayes Rule (see also probability) corpus linguistics, A Brief History of Corpus Linguistics–A Brief History of Corpus Linguistics, A Brief History of Corpus Linguistics–Corpora Today history of, A Brief History of Corpus Linguistics–A Brief History of Corpus Linguistics Corpus of Contemporary American English (COCA), A Brief History of Corpus Linguistics Corpus Pattern Analysis, Early Use of Corpora corpus, corpora, The Importance of Language Annotation, What Is a Corpus?


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


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, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, linked data, 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

For example, Hilbert and López (2009) estimated that only 25 per cent of data was stored in digital form in 2000, with the remainder being held in analogue forms such as books, magazines, photos and magnetic tapes. By 2007, digital data constituted 94 per cent of stored data. Since then, the relative share of digital data has continued to grow, especially with the development of distributed storage and services through cloud computing and data centres. Cloud computing takes two forms that often work cooperatively: utility clouds and data clouds (Farber et al. 2011). Utility clouds provide IT capabilities as locationindependent, on-demand services accessible via the Internet, including ‘infrastructure as a service’ (IaaS) such as storage, servers and networks, ‘platform as a service’ (PaaS) comprising an execution environment for the development of custom applications and databases, and ‘software as a service’ (SaaS) that enables users to access their applications and to process data remotely (Farber et al. 2011; Hancke et al. 2012).

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.

These include the production of mainframe computers in the 1950s and 60s; the nascent Internet in the 1970s and 80s that linked such computers together; the wide-scale roll-out of personal computers in the 1980s and 90s; the massive growth of the Internet in the 1990s and the development of Web-based industries, alongside a huge growth in mobile phones and digital devices such as games consoles and digital cameras; the development of mobile, distributed and cloud computing and Web 2.0 in the 2000s; the roll-out of ubiquitous and pervasive computing in the 2010s. Throughout this period a number of transformative effects took place: computational power grew exponentially; devices were networked together; more and more aspects and processes of everyday life became mediated by digital systems; data became ever more indexical and machine-readable; and data storage expanded and became distributed.


pages: 421 words: 110,406

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, 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 process, buy low sell high, chief data officer, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk,, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, Khan Academy, Kickstarter, Lean Startup, Lyft, market design, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel,, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, 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, two-sided market, Uber and Lyft, Uber for X, winner-take-all economy, Zipcar

Compare the financial results experienced by two major retailers: traditional giant Walmart and online platform Amazon. Amazon has some thirty-three open APIs as well as over 300 API “mashups” (i.e., combination tools that span two or more APIs), enabling e-commerce, cloud computing, messaging, search engine optimization, and payments. By contrast, Walmart has just one API, an e-commerce tool.14 Partly as a result of this difference, Amazon’s stock market capitalization exceeded that of Walmart for the first time in June 2015, reflecting Wall Street’s bullish view of Amazon’s future growth prospects.15 Other platform businesses have reaped similar benefits from their APIs. Cloud computing and computer services platform Salesforce generates 50 percent of its revenues through APIs, while for travel platform Expedia, the figure is 90 percent.16 The third category of developers who add value to the interactions on a platform are data aggregators.

Consider SAP, the German-based multinational giant that produces software for large enterprises to use in managing their internal operations, customer relationships, and other processes. SAP, which operates a large business processes platform, has partnered with the U.S.-based firm ADP to provide payroll processing services to its users, partly in order to take advantage of ADP’s superior access to cloud computing capabilities. However, ADP has substantial customer relationships of its own and can serve as the platform host linking customers to a number of data/computing/storage partners. Thus, the partnership creates an opportunity for ADP to displace SAP as the primary manager of the customer relationship. This is an instance in which the platform manager (SAP) is in danger of losing control of the customer connection to an extension developer (ADP).

Nalebuff and Adam M. Brandenburger, Co-opetition (London: HarperCollins Business, 1996). 17. Steve Jobs, “Thoughts on Flash,” April 2010, 18. Vardit Landsman and Stefan Stremersch, “Multihoming in Two-Sided Markets: An Empirical Inquiry in the Video Game Console Industry,” Journal of Marketing 75, no. 6 (2011): 39–54. 19. Ming Zeng, “How Will Big Data and Cloud Computing Change Platform Thinking?”, keynote address, MIT Platform Strategy Summit, July 25, 2014, 20. “Top 20 Apps with MAU Over 10 Million,” Facebook Apps Leaderboard, AppData, Accessed October 14, 2015. 21. Carl Shapiro and Hal R. Varian, “The Art of Standards Wars,” California Management Review 41, no. 2 (1999): 8–32. 22. Bill Gurley, “All Revenue Is Not Created Equal: Keys to the 10X Revenue Club,” Above the Crowd, May 24, 2011, 23.


pages: 515 words: 126,820

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, Bretton Woods, business process, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, corporate governance, corporate social responsibility, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, 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, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer lending, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, 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 software, 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, unbanked and underbanked, underbanked, unorthodox policies, X Prize, Y2K, Zipcar

With widespread adoption of the Internet, specifically the World Wide Web, individuals and companies could use their computers to share information—initially as text documents and later as images, videos, other multimedia content, and eventually software apps.3 Sharing began to democratize the information landscape. But it was short-lived. In the 1990s, a new variant of time-sharing appeared, initially called virtual private networks (VPNs) and then cloud computing. Cloud computing enabled users and companies to store and process their software and data in third-party data centers. New technology companies like built fortunes by harnessing the cloud model to save customers the big costs of developing and running their own software. Cloud service providers like Amazon and IBM built ginormous multibillion-dollar businesses. During the 2000s, social media companies like Facebook and Google created services that ran on their own vast data centers.

Summoned by an unknown person or persons with unclear motives, at an uncertain time in history, the genie is now at our service for another kick at the can—to transform the economic power grid and the old order of human affairs for the better. If we will it. Let us explain. The first four decades of the Internet brought us e-mail, the World Wide Web, dot-coms, social media, the mobile Web, big data, cloud computing, and the early days of the Internet of Things. It has been great for reducing the costs of searching, collaborating, and exchanging information. It has lowered the barriers to entry for new media and entertainment, new forms of retailing and organizing work, and unprecedented digital ventures. Through sensor technology, it has infused intelligence into our wallets, our clothing, our automobiles, our buildings, our cities, and even our biology.

He posited that a firm would expand until the cost of performing a transaction inside the firm exceeded the cost of performing the transaction outside the firm.5 Don argued that the Internet would reduce a firm’s internal transaction costs somewhat; but we thought, because of its global accessibility, it would reduce costs in the overall economy even more, in turn lowering barriers to entry for more people. Yes, it did drop search costs, through browsers and the World Wide Web. It also dropped coordination costs through e-mail, data processing applications like ERP, social networks, and cloud computing. Many companies benefited from outsourcing such units as customer service and accounting. Marketers engaged customers directly, even turning consumers into producers (prosumers). Product planners crowdsourced innovations. Manufacturers leveraged vast supply networks. However, the surprising reality is that the Internet has had peripheral impact on corporate architecture. The industrial-age hierarchy is pretty much intact as the recognizable foundation of capitalism.


pages: 215 words: 55,212

The Mesh: Why the Future of Business Is Sharing by Lisa Gansky


Airbnb, Amazon Mechanical Turk, Amazon Web Services, banking crisis, barriers to entry, carbon footprint, cloud computing, credit crunch, crowdsourcing, diversification, Firefox, Google Earth, Internet of things, Kickstarter, late fees, Network effects, new economy, peer-to-peer lending, recommendation engine, RFID, Richard Florida, Richard Thaler, ride hailing / ride sharing, sharing economy, Silicon Valley, smart grid, social web, software as a service, TaskRabbit, the built environment, walkable city, yield management, young professional, Zipcar

Other available assets include cloud computing services, social networks, and national postal services, UPS, and FedEx package services. Leveraging existing, well-established, scaled, and trusted assets significantly lowers the cost and risk of starting a new enterprise. This is a big reason that Mesh businesses are starting to thrive. The enhanced ability to leverage existing platforms, and lower incremental costs, is a big reason that Mesh businesses are starting to thrive. If we were to start Ofoto today, offering the same products and services (reliable network storage, customer order systems, backend systems, printing and shipping facilities), I estimate that it would take 10 percent of the nearly $60 million we raised at the time. Why? The cloud computing networks, tools, talent pool, and software as a service (SaaS) vendors in place today would allow us to go to market faster with far less capital.

These businesses are relatively easy to start and are spreading like wildfire: bike sharing, home exchanges, fashion swap parties, energy cooperatives, shared offices, cohousing, music studios, tool libraries, food and wine cooperatives, and many more. They leverage hundreds of billions of dollars in available information infrastructure—telecommunications, mobile technology, enhanced data collection, large and growing social networks, mobile SMS aggregators, and of course the Web itself. They efficiently employ horizontal business to business services, such as FedEx, UPS, Amazon Web Services, PayPal, and an ever-increasing number of cloud computing services. All the Mesh businesses rely on a basic premise: when information about goods is shared, the value of those goods increases, for the business, for individuals, and for the community. Mesh businesses are legally organized as for-profit corporations, cooperatives, and nonprofit organizations. Once I started looking, I quickly uncovered over 1,500 relevant companies and organizations.


pages: 186 words: 49,251

The Automatic Customer: Creating a Subscription Business in Any Industry by John Warrillow


Airbnb, airport security, Amazon Web Services, asset allocation, barriers to entry, call centre, cloud computing, discounted cash flows, high net worth, Jeff Bezos, Network effects, passive income, rolodex, sharing economy, side project, Silicon Valley, Silicon Valley startup, software as a service, statistical model, Steve Jobs, Stewart Brand, subscription business, telemarketer, time value of money, Zipcar

If Time Warner Cable has to send a technician to a SignatureHome subscriber’s house, he or she will wear specially designed booties to keep the customer’s floors tidy—a small touch designed to make SignatureHome subscribers feel valued. Similarly, Microsoft has also made plays in the area of subscription services with Microsoft Office, the most successful and pervasive software program in history. The folks in Redmond don’t want you buying Office at Staples anymore; today, they want to sell you a subscription to Office 365. Microsoft’s aggressive push into cloud computing has been accelerated by Google Apps, another office productivity suite that is available to businesses exclusively through subscription. Big companies like Apple, Time Warner Cable, Amazon, Target, Microsoft, and Google are not necessarily walking away from their traditional business models entirely. In many cases, they are adding a subscription business to build recurring revenue, expand their relationships with existing customers, and understand what customers want.

Let’s say you make 70% gross profit after paying the expenses of onboarding and any hard costs associated with adding each new subscriber. Using the example above, BVP would express your CAC payback period as approximately 7 months: 500 divided by ($100 × .70). An acceptable CAC payback period depends on how sticky your customers are and how much they spend with you. BVP elaborates on this concept in its white paper “Bessemer’s Top 10 Laws of Cloud Computing”: For SMB (Small & Medium Business) customers with higher churn rates and thus shorter monetization windows, CAC Payback Periods of 6–18 months are typically needed, whereas enterprise businesses with high up sells and long retention periods may be able to subsidize payback periods of 24–36 months. A CAC Payback Period of 36+ months is typically a cause for concern and suggests you may want to slam on the brakes until you can improve sales efficiency, whereas a Payback Period of under 6 months means you should invest more money immediately and step on the gas.1 The concept of a CAC payback period can be described visually.

Reports Q2 2012 Financial Results,”, press release, July 25, 2012. 3. Nunogawa, Matt, “Notes and Summary of Gail Goodman’s ‘The Long Slow SaaS Ramp of Death,’” @amattn, September 11, 2013. CHAPTER 13: THE CASH SUCK VS. THE CASH SPIGOT 1. Botteri, Philippe, et al., “Bessemer’s Top 10 Laws of Cloud Computing and SaaS,” Bessemer Venture Partners, Winter 2010. 2. McDerment, Mike, “An Open Letter from FreshBooks Founder Mike McDerment,”, August 21, 2012. 3. Davidoff, Steven M., “In Venture Capital Deals, Not Every Founder Will Be a Zuckerberg,” New York Times, April 30, 2013. 4.


pages: 133 words: 42,254

Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst


algorithmic trading, bioinformatics, business intelligence, business process, call centre, cloud computing, create, read, update, delete, data acquisition, DevOps, fault tolerance, linked data, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, Watson beat the top human players on Jeopardy!, web application

Currently, Hadoop, an open source software framework derived from Google’s MapReduce and Google File System papers, is being used by several technology vendors to do just that. Hadoop maps tasks across a cluster of machines, splitting them into smaller subtasks, before reducing the results into one master calculation. It’s really an old grid-computing technique given new life in the age of cloud computing. Many of the challenges of yesterday remain today, and technology is just now catching up with the demands of Big Data analytics. However, Big Data remains a moving target. As the future brings more challenges, it will also deliver more solutions, and Big Data has a bright future, with tomorrow delivering the technologies that ease leveraging the data. For example, Hadoop is converging with other technology advances such as high-speed data analysis, made possible by parallel computing, in-memory processing, and lower-cost flash memory in the form of solid-state drives.

See Business intelligence (BI) Big Data and Big Data analytics analysis categories application platforms best practices business case development challenges classifications components defined evolution of examples of 4Vs of goal setting introduction investment in path to phases of potential of privacy issues processing role of security (See Security) sources of storage team development technologies (See Technologies) value of visualizations Big Science BigSheets Bigtable Bioinformatics Biomedical industry Blekko Business analytics (BA) Business case best practices data collection and storage options elements of introduction Business intelligence (BI) as Big Data analytics foundation Big Data analytics team incorporation Big Data impact defined extract, transform, and load (ETL) information technology and in-memory processing limitations of marketing campaigns risk analysis storage capacity issues unstructured data visualizations Business leads Business logic Business objectives Business rules C Capacity of storage systems Cassandra Census data CERN Citi Classification of data Cleaning Click-stream data Cloud computing Cloudera Combs, Nick Commodity hardware Common Crawl Corpus Communication Competition Compliance Computer security officers (CSOs) Consulting firms Core capabilities, data analytics team Costs Counterintelligence mind-set CRUD (create, retrieve, update, delete) applications Cryptographic keys Culture, corporate Customer needs Cutting, Doug D Data defined growth in volume of value of See also Big Data and Big Data analytics Data analysis categories challenges complexity of as critical skill for team members data accuracy evolution of importance of process technologies Database design Data classification Data discovery Data extraction Data integration technologies value creation Data interpretation Data manipulation Data migration Data mining components as critical skill for team members defined examples methods technologies Data modeling Data protection.

See Technologies Sources of data. See Data sources Space program Specificity of information Speed-accuracy tradeoff Spring Data SQL limitations NoSQL Integration scaling Stale data Statistical applications Storage Storm Structured data Success, measurement of Supplementary information Supply chain T Tableau Public Taxonomies Team members Technologies application platforms Cassandra cloud computing commodity hardware decision making processing power security storage Web-based tools worst practices See also Hadoop Telecommunications Text analytics Thin provisioning T-Mobile Training Transportation Trends Trusted applications Turk Twitter U United Parcel Service (UPS) Unstructured data complexity of defined forms growth of project goal setting social media’s collection technologies varieties of U.S. census User analysis Utilities sector V Value, extraction of Variety Velocity Vendor lock-in Veracity Videos Video surveillance Villanustre, Flavio Visualization Volume W Walt Disney Company Watson Web-based technologies Web sites click-stream data logs traffic distribution White-box systems Worst practices Wyle Laboratories X XML Y Yahoo


pages: 234 words: 63,522

Puppet Essentials by Felix Frank


cloud computing, Debian, DevOps, domain-specific language, Infrastructure as a Service, platform as a service, web application

The toolchain of types and providers has been explained, and you can even extend Puppet through your own custom plugins. Designing and structuring manifests through classes, defined types, and modules is becoming natural to you, and you have some more advanced language tools at your disposal as well. It is now time to look from a more practical angle. Let's take a look at designs that are useful in common real-world scenarios. With the general trend of cloud computing, we will focus on some techniques that cater especially to the use of Puppet in cloud environments. This will not be limited to the manifest and module design; you will also learn some generally useful configuration and deployment techniques. These are the topics that we'll cover in this final chapter: • Typical scopes of Puppet • Taking Puppet to the cloud • Building manifests for the cloud • Preparing for autoscaling • Ensuring successful provisioning Configuring Your Cloud Application with Puppet Typical scopes of Puppet Puppet was originally conceived for the automation and centralized maintenance of server configurations.

For example, the purging of authorized SSH keys must be configured through the owning user type instead, because the resources type cannot enumerate them: user { 'rcmd': ensure => present, uid => '2082', purge_ssh_keys => true, } [ 197 ] Configuring Your Cloud Application with Puppet Also, keep in mind that purging will only work for native resources and not instances of defined types. To clean these up, you will have to target their wrapped resources for purging. You did this already in the rcmd example—the file resources with the purge => true parameter took care of purging unmanaged rcmd::command resources by removing the files that the defined type had created. Preparing for autoscaling One advantage of cloud computing over classic data center operations is its ability to minimize the cost for infrastructure. You usually don't need to overprovision your cloud server resources, because you can add instances on short notice. If your workload is fluctuating, predictably or not, you can potentially further minimize the infrastructure through autoscaling features. Let the cloud provider add and remove instances as the load increases and decreases again.

Plan, test, and execute your Puppet deployments. 2. Write reusable and maintainable Puppet code. 3. Handle challenges that might arise in upcoming versions of Puppet. Please check for information on our titles Puppet 3 Cookbook ISBN: 978-1-78216-976-5 Paperback: 274 pages Build reliable, scalable, secure, and high-performance systems to fully utilize the power of cloud computing 1. Use Puppet 3 to take control of your servers and desktops, with detailed step-by-step instructions. 2. Covers all the popular tools and frameworks used with Puppet: Dashboard, Foreman, and more. 3. Teaches you how to extend Puppet with custom functions, types, and providers. Mastering Puppet ISBN: 978-1-78398-218-9 Paperback: 280 pages Pull the strings of Puppet to configure enterprise-grade environments for performance optimization 1.


pages: 138 words: 40,787

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


3D printing, 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, connected car, crowdsourcing, data acquisition,, 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, Network effects, Paul Graham, Ray Kurzweil, RFID, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

Adoption of M2M has been distributed across many markets, and fourteen or fifteen years later, it feels like it has snuck up on us. Why has it taken so long for the world to catch on to what some of us have known for over a decade? It is because in the majority of cases, new technologies that can disrupt business models take much more time to be accepted than anyone in that market wants or expects. In the U.S. market, it took cell phones about twenty years to get to major mass-market penetration. Cloud computing (think Software as a Service, timesharing) can trace its origins back many, many years. With a handful of exceptions, tablets being possibly the best-known outlier, technology adoption takes years. I think we were fooled, like many early market entrants, into thinking we would move right from the visionary customers and early adopters directly into mainstream adoption. The reality, well explained in Geoffrey Moore’s book Crossing the Chasm, is that in order to get across that chasm between the early adopters and the early majority, you need to package that technology into something that is easy for companies to consume.

Since investment in the Internet of Things has until now been more of a futuristic topic, and the understanding and definition of the market varies notably, forecasts are all over the place. For example, IDC, a market research firm, estimates the value of intelligent systems at $1.7 trillion already, growing to $2.4 trillion by 2017.30 It’s interesting if you look at the high-growth markets that are currently developing around cloud computing, big data, and business intelligence. These markets are in the double-digit billions, and are often not counted toward the M2M market. This shows how blurry the borders are, and that we can expect a number of additional growth segments that we do not see or envision today. The question many investors raise is: How does this growth come about? In addition, what are the core growth segments?

As we mentioned in chapter 1, the key macroeconomic trends that will enable this new ecosystem to grow exponentially are described here: First, we see reduction in size and increases in processing power, driven by Moore’s Law, but also by improvements in electric power management. The second important factor is affordability — we see a strong reduction of production costs in areas like fixed and mobile networks, hardware, software, cloud computing, mobile technologies, and robotics. In most areas, technology production costs have decreased by more than 90 percent in the past several years and will continue to fall, also just as predicted by Gordon Moore and his Law. The third crucial trend is de-wireization. As more things are becoming wireless, it means their location can be almost anywhere. The growing ubiquity of cellular and Wi-Fi networks have enabled this trend.


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, cloud computing, crowdsourcing, Daniel Kahneman / Amos Tversky, dematerialisation, deskilling, Elon Musk,, Exxon Valdez, fear of failure, Firefox, Galaxy Zoo, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, industrial robot, Internet of things, Jeff Bezos, John Harrison: Longitude, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, Mahatma Gandhi, 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, 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, technoutopianism, telepresence, telepresence robot, Turing test, urban renewal, web application, X Prize, Y Combinator

“We’re seeing very early indicators that this market is coming into fruition immediately,” says Jon Callaghan, a founding partner in the early-stage tech venture capital firm True Ventures, in that same Entrepreneur article. “It’s super early, but it will hit very, very quickly, and we’ll look back on 2013 . . . as a year for robotics coming into its own.” Genomics and Synthetic Biology Throughout the past few chapters, we’ve been examining exponentials poised to explode over the next three to five years and seeing how these technologies reinforce and empower one another—the rise of cloud computing enables more capable and ubiquitous AI, which in turn allows the average entrepreneur to program robots. To close this chapter, we’re going to examine synthetic biology, a technology that’s a little further out—say, five to ten years—but is still transitioning from deception to disruption. And it’s going to be a sizable disruption. Synthetic biology56 is built around the idea that DNA is essentially software—nothing more than a four-letter code arranged in a specific order.

Put simpler, HLI’s goal is to make one hundred years old the new sixty. We launched HLI with $85 million in seed capital, raised at record speed. Part of the reason for this velocity is that the company sits at the intersection of many of the exponential technologies discussed in this chapter: robotics, which enables lightning-fast sequencing; AI and machine learning, which can make sense of petabytes of raw genomic data; cloud computing and networks for transmitting, handling, and storing that data; and synthetic biology for correcting and rewriting the corrupted genome of our aging stem cells. Couple that with the incredible value proposition of abundant, longer, and healthier lives—there is over $50 trillion locked up in the bank accounts of people over the age of sixty-five—and you understand the potential. And understanding this potential is critical if you’re going to succeed as an exponential entrepreneur.

Moreover, liberation from proximity and prejudice increases access to new ideas. Since creativity is recombinatory—i.e., breakthroughs result from new ideas bumping into old thoughts to produce novel insights—this increased access to ideas amplifies the rate of innovation in communities. In fact, if you combine this amplified rate of innovation with our newfound ability to tap any expert anywhere in the world, the potency of technologies like 3-D printing and cloud computing, and the power of crowdfunding to capitalize such ventures, you find the second key difference in today’s communities: the scale of projects they can now undertake has grown exponentially. Communities are now empowered to tackle jobs far larger in scope and size than anything previously possible. For one example, the online hobbyist community DIY Drones has been able to build military-grade autonomous aircraft; for another, Local Motors is constructing fully customizable automobiles.4 Ten years ago, challenges of this size were the sole province of large corporations and governments.


pages: 284 words: 92,688

Disrupted: My Misadventure in the Start-Up Bubble by Dan Lyons


Airbnb, Bernie Madoff, bitcoin, call centre, cleantech, cloud computing, corporate governance, dumpster diving, fear of failure, Filter Bubble, Golden Gate Park, Google Glasses, Googley, Gordon Gekko, hiring and firing, Jeff Bezos, Lean Startup, Lyft, Mark Zuckerberg, Menlo Park, minimum viable product, new economy, Paul Graham, pre–internet, quantitative easing, ride hailing / ride sharing, Rosa Parks, Sand Hill Road, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Snapchat, software as a service, South of Market, San Francisco, Steve Ballmer, Steve Jobs, Steve Wozniak, telemarketer, tulip mania, Y Combinator, éminence grise

Halligan used to work as a venture capitalist, so he thinks like an investor. Shah, before going to grad school at MIT, built a different software company and sold it. Also, from the perspective of Wall Street, HubSpot ticks all the right boxes. It sells to businesses, rather than to consumers. It’s a cloud computing company and uses a business model called software as a service, or SaaS, which means customers don’t install the software on their own computers but instead connect to it over the Internet and pay a monthly subscription fee. Cloud computing is hot right now. The whole tech industry is moving to this model. Investors love it. Over the years Halligan and Shah have come up with a creation myth about the company, which is that while they were in grad school they had a vision for how companies could transform their marketing departments.

The problem is that HubSpot files its paperwork right after another tech start-up, Box, announces its own plans to go public. Box is a high-profile company in Silicon Valley. It’s seen as a bellwether for other cloud computing companies, including HubSpot. Box has a charming, charismatic, twenty-something CEO, Aaron Levie, and everyone has been under the impression that the company is doing a booming business. But now it has published its financial results and the numbers are underwhelming. Sales are growing, but Box is spending way too much on sales and marketing, and losing huge amounts of money. To be sure, that’s the case for most of the other cloud software companies. But even by the relaxed standards of the second tech bubble, Box’s results are disappointing. Meanwhile, for some reason, shares in cloud computing and “software as a service” companies are starting to swoon. One index of thirty-seven publicly traded cloud-related companies loses $58 billion in market value over the course of two months.


pages: 371 words: 108,317

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


3D printing, 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, 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, Kevin Kelly, Kickstarter, linked data, Lyft, M-Pesa, Marshall McLuhan, means of production, megacity, Minecraft, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, 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, Watson beat the top human players on Jeopardy!, Whole Earth Review

This perfect storm of cheap parallel computation, bigger data, and deeper algorithms generated the 60-years-in-the-making overnight success of AI. And this convergence suggests that as long as these technological trends continue—and there’s no reason to think they won’t—AI will keep improving. As it does, this cloud-based AI will become an increasingly ingrained part of our everyday life. But it will come at a price. Cloud computing empowers the law of increasing returns, sometimes called the network effect, which holds that the value of a network increases much faster as it grows bigger. The bigger the network, the more attractive it is to new users, which makes it even bigger and thus more attractive, and so on. A cloud that serves AI will obey the same law. The more people who use an AI, the smarter it gets. The smarter it gets, the more people who use it.

Dematerialization and decentralization and massive communication all lead to more platforms. Platforms are factories for services; services favor access over ownership. Clouds The movies, music, books, and games that you access all live on clouds. A cloud is a colony of millions of computers that are braided together seamlessly to act as a single large computer. The bulk of what you do on the web and phone today is done on cloud computing. Though invisible, clouds run our digital lives. A cloud is more powerful than a traditional supercomputer because its core is dynamically distributed. That means that its memory and work is spread across many chips in a massively redundant way. Let’s say you were streaming a long movie and suddenly an asteroid smashed one tenth of the machines that made up the cloud. You might not notice any interruption in the movie because the movie file did not reside in any particular machine but was distributed in a redundant pattern across many processors in such a way that the cloud can reconfigure itself if any of those units fail.

Anyone who owns a computer recognizes those burdens: They take up space, need constant expert attention, and go obsolete instantly. Who would want to own their computer? The answer increasingly is no one. No more than you want to own an electric station, rather than buy electricity from the grid. Clouds enable organizations to access the benefits of computers without the hassle of possession. Expandable cloud computing at discount prices has made it a hundred times easier for a young technology company to start up. Instead of building their own complex computing infrastructure, they subscribe to a cloud’s infrastructure. In industry terms, this is infrastructure as service. Computers as service instead of computers as product: access instead of ownership. Gaining cheap access to the best infrastructure by operating on the cloud is a chief reason so many young companies have exploded out of Silicon Valley in the last decade.


pages: 197 words: 35,256

NumPy Cookbook by Ivan Idris


business intelligence, cloud computing, computer vision, Debian,, Eratosthenes, mandelbrot fractal, p-value, sorting algorithm, statistical model, transaction costs, web application

Rosario Acquisition Editor Usha Iyer Lead Technical Editor Ankita Shashi Technical Editors Merin Jose Rohit Rajgor Farhaan Shaikh Nitee Shetty Copy Editor Insiya Morbiwala Project Coordinator Vishal Bodwani Proofreader Clyde Jenkins Indexer Monica Ajmera Mehta Production Coordinators Arvindkumar Gupta Manu Joseph Cover Work Arvindkumar Gupta Manu Joseph About the Author Ivan Idris has an MSc in Experimental Physics. His graduation thesis had a strong emphasis on Applied Computer Science. After graduating, he worked for several companies as a Java Developer, Data Warehouse Developer, and QA Analyst. His main professional interests are business intelligence, big data, and cloud computing. He enjoys writing clean, testable code, and interesting technical articles. He is the author of NumPy 1.5 Beginner's Guide. You can find more information and a blog with a few NumPy examples at I would like to dedicate this book to my family and friends. I would like to take this opportunity to thank the reviewers and the team at Packt for making this book possible. Thanks also goes to my teachers, professors, and colleagues, who taught me about science and programming.

However, as we saw, it is possible to create and test a program locally, and upload it to Python Anywhere. This frees resources on your local machine as well. We can do fancy things such as sending emails based on the stock price, for instance, or schedule our scripts to be activated during trading hours. By the way, this is also possible with Google App Engine, but it is done the Google way; so you will need to learn about their API. Setting up PiCloud PiCloud is another cloud computing provider, which is actually using the EC2 Amazon infrastructure. However, they do offer environments with preinstalled Python software, including NumPy. These environments are just EC2 instances that we can ssh into. In this recipe, we will be using the Python 2.7—Ubuntu Natty 11.04 environment. For the installed packages in this environment, see .


pages: 538 words: 141,822

The Net Delusion: The Dark Side of Internet Freedom by Evgeny Morozov


A Declaration of the Independence of Cyberspace, Ayatollah Khomeini, Berlin Wall, borderless world, Buckminster Fuller, Cass Sunstein, citizen journalism, cloud computing, cognitive dissonance, Columbine, computer age, conceptual framework, crowdsourcing, Dissolution of the Soviet Union, don't be evil, failed state, Fall of the Berlin Wall, Francis Fukuyama: the end of history, global village, Google Earth, illegal immigration, invention of radio, invention of the printing press, invisible hand, John von Neumann, Marshall McLuhan, Naomi Klein, Network effects, new economy, New Urbanism, pirate software, pre–internet, Productivity paradox, RAND corporation, Ronald Reagan, Ronald Reagan: Tear down this wall, Silicon Valley, Silicon Valley startup, Sinatra Doctrine, Skype, Slavoj Žižek, social graph, Steve Jobs, technoutopianism, The Wisdom of Crowds, urban planning, Washington Consensus, WikiLeaks, women in the workforce

Elude the Cat, Empower the Masses What Barbara Streisand Could Teach Nicolae Ceauşescu Russia’s First Pornographer Meets Russia’s Sarah Palin Fifty Cents Gets You a Long Way on the Spinternet Small Doses of Propaganda Are Still Bad for You Darning Mao’s Socks, One SMS at a Time chapter six - Why the KGB Wants You to Join Facebook Never Trust Anyone with a Website Why Databases Are Better Than Stasi Officers Say Hi. You’re on Camera! How to Lose Face on Facebook Think, Search, Cough The Myth of an Overprotected Activist Rainy Days of Cloud Computing On Mobile Phones That Limit Your Mobility chapter seven - Why Kierkegaard Hates Slacktivism Digital Natives of the World, Unite! Poking Kierkegaard Kandinsky and Vonnegut Are Now Friends! Killing the Slacktivist in You On the Increased Productivity of Lonely Warriors, or Why Some Crowds Are Wise ... Everybody Can’t Be Che Guevara Dissidents Without Dissent No Such Thing as Virtual Politics chapter eight - Open Networks, Narrow Minds: Cultural Contradictions of ...

For many antigovernment activists, cybercafés have become the new (and often the only) offices, as authorities keep a close eye on their home and office Internet connections. However, few Internet cafés allow their patrons to install new software or even use browsers other than Internet Explorer, which puts most innovative tools for secure communication out of easy reach. Rainy Days of Cloud Computing Some observers see many security-enhancing benefits to the Internet. For example, dissidents and NGOs can now use multifunctional online working environments to execute all their work remotely—“in the cloud”—without having to install any software or even store any data on poorly protected computers. All one needs is a secure browser and an Internet connection; there’s no need to download any files or carry a portable copy of your favorite word processor on a USB thumb drive.

The fact that many activists and NGOs now conduct all their business activities out of a single online system, most commonly Google—with calendar, email, documents, and budgets all easily available from just one account—means that should their password be compromised, they would lose control over all of their online activities. Running all those operations on their own laptops was not much safer, but at least a laptop could be locked in a safe. The centralization of information under one roof—as often happens in the case of Google—can do wonders from the perspective of productivity, but from the perspective of security it often only increases the risks. On Mobile Phones That Limit Your Mobility Much like cloud computing, the mobile phone is another activist tool that has not been subjected to thorough security analysis. While it has been rightly heralded as the key tool for organizing, especially in countries where access to the Internet and computers is prohibitively expensive, little has been said about the risks inherent to most “mobile activism.” The advantages of such activism are undeniable. Unlike blogging and tweeting, which require an Internet connection, text messaging is cheap and ubiquitous, and it doesn’t require much training.


pages: 523 words: 148,929

Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100 by Michio Kaku


agricultural Revolution, AI winter, Albert Einstein, augmented reality, Bill Joy: nanobots, bioinformatics, blue-collar work, British Empire, Brownian motion, cloud computing, Colonization of Mars, DARPA: Urban Challenge, delayed gratification, double helix, Douglas Hofstadter,, friendly AI, Gödel, Escher, Bach, hydrogen economy, I think there is a world market for maybe five computers, industrial robot, invention of movable type, invention of the telescope, Isaac Newton, John von Neumann, life extension, Louis Pasteur, Mahatma Gandhi, Mars Rover, megacity, Murray Gell-Mann, new economy, oil shale / tar sands, optical character recognition, pattern recognition, planetary scale, postindustrial economy, Ray Kurzweil, refrigerator car, Richard Feynman, Richard Feynman, Rodney Brooks, Ronald Reagan, Search for Extraterrestrial Intelligence, Silicon Valley, Simon Singh, speech recognition, stem cell, Stephen Hawking, Steve Jobs, telepresence, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, trade route, Turing machine, uranium enrichment, Vernor Vinge, Wall-E, Walter Mischel, Whole Earth Review, X Prize

• Mass technology as a utility When technologies become widely dispersed, such as electricity and running water, they eventually become utilities. With capitalism driving down prices and increasing competition, these technologies will be sold like utilities, that is, we don’t care where they come from and we pay for them only when we want them. The same applies for computation. “Cloud computing,” which relies heavily on the Internet for most computing functions, will gradually gain in popularity. Cloud computing reduces computation to a utility, something that we pay for only when we need it, and something that we don’t think about when we don’t need it. This is different from the situation today, when most of us do our typing, word processing, or drawing on a desktop or laptop computer and then connect to the Internet when we want to search for information.

See also Intellectual capitalism Carbon nanotubes, 4.­1, 6.­1 Carbon sequestration Cars driverless electric maglev, 5.­1, 9.­1 Cascio, Jamais Catoms Cave Man Principle biotechnology and computer animations and predicting the future and replicators and, 4.­1, 4.­2 robotics/AI and, 2.­1, 2.­2 sports and Cerf, Vint, 4.­1, 6.­1 Chalmers, David Charles, Prince of Wales Chemotherapy Chernobyl nuclear accident Chevy Volt Chinese Empire, 7.­1, 7.­2 Church, George Churchill, Winston, itr.­1, 8.­1 Cipriani, Christian Civilizations alien civilizations characteristics of various Types entropy and information processing and resistance to Type I civilization rise and fall of great empires rise of civilization on Earth science and wisdom, importance of transition from Type 0 to Type I, itr.­1, 8.­1, 8.­2 Type II civilizations, 8.­1, 8.­2, 8.­3 Type III civilizations, 8.­1, 8.­2 waste heat and Clarke, Arthur C.­ Clausewitz, Carl von Cloning, 3.­1, 3.­2 Cloud computing, 1.­1, 7.­1 Cochlear implants Code breaking Collins, Francis Comets Common sense, 2.­1, 2.­2, 2.­3, 7.­1, 7.­2 Computers animations created by augmented reality bioinformatics brain simulations carbon nanotubes and cloud computing, 1.­1, 7.­1 digital divide DNA computers driverless cars exponential growth of computer power (Moore’s law), 1.­1, 1.­2, 1.­3, 4.­1 fairy tale life and far future (2070) four stages of technology and Internet glasses and contact lenses, 1.­1, 1.­2 medicine and midcentury (2030) mind control of molecular and atomic transistors nanotechnology and near future (present to 2030) optical computers parallel processing physics of computer revolution quantum computers quantum dot computers quantum theory and, 1.­1, 4.­1, 4.­2, 4.­3 scrap computers self-­assembly and silicon chips, limitations of, 1.­1, 1.­2, 4.­1 telekinesis with 3-­D technology universal translators virtual reality wall screens See also Mind reading; Robotics/­AI Condorcet, Marquis de Conscious robots, 2.­1, 2.­2 Constellation Program COROT satellite, 6.­1, 8.­1 Crick, Francis Criminology Crutzen, Paul Culture in Type I civilization Customization of products Cybertourism, itr.­1, itr.­2 CYC project Damasio, Antonio Dating in 2100, 9.­1, 9.­2, 9.­3, 9.­4 Davies, Stephen Da Vinci robotic system Dawkins, Richard, 3.­1, 3.­2, 3.­3 Dawn computer Dean, Thomas Decoherence problem Deep Blue computer, 2.­1, 2.­2, 2.­3 Delayed gratification DEMO fusion reactor Depression treatments Designer children, 3.­1, 3.­2, 3.­3 Developing nations, 7.­1, 7.­2 Diamandis, Peter Dictatorships Digital divide Dinosaur resurrection Disease, elimination of, 3.­1, 8.­1 DNA chips DNA computers Dog breeds Donoghue, John, 1.­1, 1.­2 Dreams, photographing of Drexler, Eric Driverless cars Duell, Charles H.­

Today at airports you see hundreds of travelers carrying laptop computers. Once at the hotel, they have to connect to the Internet; and once they return back home, they have to download files into their desktop machines. In the future, you will never need to lug a computer around, since everywhere you turn, the walls, pictures, and furniture can connect you to the Internet, even if you are in a train or car. (“Cloud computing,” where you are billed not for computers but for computer time, treating computation like a utility that is metered like water or electricity, is an early example of this.) VIRTUAL WORLDS The goal of ubiquitous computing is to bring the computer into our world: to put chips everywhere. The purpose of virtual reality is the opposite: to put us into the world of the computer. Virtual reality was first introduced by the military in the 1960s as a way of training pilots and soldiers using simulations.


pages: 525 words: 116,295

The New Digital Age: Transforming Nations, Businesses, and Our Lives by Eric Schmidt, Jared Cohen


3D printing, access to a mobile phone, additive manufacturing, airport security, Amazon Mechanical Turk, Amazon Web Services, anti-communist, augmented reality, Ayatollah Khomeini, barriers to entry, bitcoin, borderless world, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, crowdsourcing, data acquisition, Dean Kamen, Elon Musk, failed state, fear of failure, Filter Bubble, Google Earth, Google Glasses, hive mind, income inequality, information trail, invention of the printing press, job automation, Julian Assange, Khan Academy, Kickstarter, knowledge economy, Law of Accelerating Returns, market fundamentalism, means of production, mobile money, mutually assured destruction, Naomi Klein, offshore financial centre, peer-to-peer lending, personalized medicine, Peter Singer: altruism, Ray Kurzweil, RFID, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, social graph, speech recognition, Steve Jobs, Steven Pinker, Stewart Brand, Stuxnet, The Wisdom of Crowds, upwardly mobile, Whole Earth Catalog, WikiLeaks, young professional, zero day

Our highly documented pasts will have an impact on our prospects, and our ability to influence and control how we are perceived by others will decrease dramatically. The potential for someone else to access, share or manipulate parts of our online identities will increase, particularly due to our reliance on cloud-based data storage. (In nontechnical language, cloud computing refers to software hosted on the Internet that the user does not need to closely manage. Storing documents or content “in the cloud” means that data is stored on remote servers rather than on local ones or on a person’s own computer, and it can be accessed by multiple networks and users. With cloud computing, online activities are faster, quicker to spread and better equipped to handle traffic loads.) This vulnerability—both perceived and real—will mandate that technology companies work even harder to earn the trust of their users. If they do not exceed expectations in terms of both privacy and security, the result will be either a backlash or abandonment of their product.

A team at Carnegie Mellon demonstrated in a 2011 study that the combination of “off-the-shelf” facial-recognition software and publicly available online data can match a large number of faces very quickly, thanks to technical advancements like cloud computing. In one experiment, unidentified pictures from dating sites (where people often use pseudonyms) were compared with profile shots from social-networking sites, which can be publicly accessed on search engines (i.e., no log-in required), yielding a statistically significant result. It was noted in the study that it would be unfeasible for a human to do this search manually, but with cloud computing, it takes just seconds to compare millions of faces. The accuracy improves regarding people with many pictures of themselves available online—which, in the age of Facebook, is practically everyone.

Data is rarely erased on computers; operating systems tend to remove only a file’s listing from the internal directory, keeping the file’s contents in place until the space is needed for other things. (And even after a file has been overwritten, it’s still occasionally possible to recover parts of the original content due to the magnetic properties of disc storage. This problem is known as “data remanence” by computer experts.) Cloud computing only reinforces the permanence of information, adding another layer of remote protection for users and their information. Such mechanisms of retention were designed to save us from our own carelessness when operating computers. In the future, people will increasingly trust cloud storage—like ATMs in banks—over physical machinery, placing their faith in companies to store some of their most sensitive information, avoiding the risks of hard-drive crashes, computer theft or document loss.


pages: 527 words: 147,690

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman


23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, meta analysis, meta-analysis, Minecraft, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Turing test, Uber and Lyft, Uber for X, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

Sept. 3, 2013. 219 Nandini Balial background and Rabbit experience: Author interviews with Nandini Balial. July and August 2014. 226 Mechanical Turk earnings: Jeremy Wilson. “My Grueling Day as an Amazon Mechanical Turk.” Kernel. Aug. 28, 2013. 228 “a cloud-computing cross”: Quentin Hardy. “Elance Pairs Hunt for Temp Work with Cloud Computing.” Bits, a blog on Sept. 24, 2013. 228 Mechanical Turk survey: Panos Ipeirotis. “Demographics of Mechanical Turk.” Stern School of Business. March 2010. 228 “hyperdata”: Quentin Hardy. “Big Data’s Little Brother.” New York Times. Nov. 10, 2013. 229 “the performance of the workers”: Ayhan Aytes.

The software facilitating this transaction acts as the ultimate mediator: the employee and the employer never have to deal with each other directly. Payment can be unreliable and is wholly contingent on the employer accepting the laborer’s product; if the former doesn’t like what he receives, he can simply reject it and not pay the worker for his time, nor allow him to appeal or revise his work. Online labor markets are often charged with being digital sweatshops or, as one New York Times article put it, “a cloud-computing cross between Facebook and a hiring boss stopping his pickup truck in front of hungry day workers.” Their defenders counter that these markets provide useful, on-demand work for the unemployed, stay-at-home parents, people looking to make a little extra cash, and others who don’t belong to the conventional workforce. A 2010 survey found that most Mechanical Turk workers are in the United States and India, and that while about 70 percent have full-time jobs, they also tend to have low incomes.

In reality, the Internet was a public construction project, a government-funded initiative, in its earliest days, when the Department of Defense launched ARPANET, a communications network between research labs at four U.S. universities. And government involvement in cyberspace has persisted, particularly with the anointing of the Internet as a new battlefield, complete with cyber-weapons, teams of government-directed hackers, and mass surveillance. Cisco and Amazon are major providers of database and cloud-computing services to the CIA and other members of the intelligence community. The U.S. government remains one of Silicon Valley’s most lucrative and reliable clients, and tech companies and telecoms are paid partners in U.S. government surveillance. Even though Barlow’s argument has been debunked over the years, it persists in varying forms, especially in the notion that cyberspace is somehow separate from real life, meaning that it’s a place of freedom and possibility where normal rules don’t apply.


pages: 274 words: 75,846

The Filter Bubble: What the Internet Is Hiding From You by Eli Pariser


A Declaration of the Independence of Cyberspace, A Pattern Language, Amazon Web Services, augmented reality, back-to-the-land, Black Swan, borderless world, Build a better mousetrap, Cass Sunstein, citizen journalism, cloud computing, cognitive dissonance, crowdsourcing, Danny Hillis, data acquisition, disintermediation, don't be evil, Filter Bubble, Flash crash, fundamental attribution error, global village, Haight Ashbury, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, jimmy wales, Kevin Kelly, knowledge worker, Mark Zuckerberg, Marshall McLuhan, megacity, Netflix Prize, new economy, PageRank, paypal mafia, Peter Thiel, recommendation engine, RFID, sentiment analysis, shareholder value, Silicon Valley, Silicon Valley startup, social graph, social software, social web, speech recognition, Startup school, statistical model, stem cell, Steve Jobs, Steven Levy, Stewart Brand, technoutopianism, the scientific method, urban planning, Whole Earth Catalog, WikiLeaks, Y Combinator

Cables Go Offline After Site Switches Servers,” Huffington Post, Dec. 1, 2010, accessed Feb. 9, 2011, 145 “lose your constitutional protections immediately”: Christopher Ketcham and Travis Kelly, “The More You Use Google, the More Google Knows About You,” AlterNet, Apr. 9, 2010, accessed Dec. 17, 2010,,_the_more_google_knows_about_you _?page=entire. 146 “cops will love this”: “Does Cloud Computing Mean More Risks to Privacy?,” New York Times, Feb. 23, 2009, accessed Feb. 8, 2011, 146 the three companies quickly complied: Antone Gonsalves, “Yahoo, MSN, AOL Gave Search Data to Bush Administration Lawyers,” Information Week, Jan. 19, 2006, accessed Feb. 9, 2011, 146 predict future real-world events: Ketcham and Kelly, “The More You Use Google.” 146 “an individual must increasingly give information”: Jonathan Zittrain, The Future of the Internet—and How to Stop It (New Haven: Yale University Press, 2008), 201. 147 “an implicit bargain in our behavior”: John Battelle, phone interview with author, Oct. 12, 2010. 147 “redistribution of information power”: Viktor Mayer-Schonberger, Delete: The Virtue of Forgetting in the Digital Age (Princeton: Princeton University Press, 2009), 107. 148 real-world violence: George Gerbner, “TV Is Too Violent Even Without Executions,” USA Today, June 16, 1994, 12A, accessed Feb. 9, 2011 through LexisNexis. 149 “who tells the stories of a culture”: “Fighting ‘Mean World Syndrome,’ ” GeekMom blog, Wired, Jan. 27, 2011, accessed Feb. 9, 2011, 149 friendly world syndrome: Dean Eckles, “The ‘Friendly World Syndrome’ Induced by Simple Filtering Rules,” Ready-to-Hand: Dean Eckles on People, Technology, and Inference blog, Nov. 10, 2010, accessed Feb. 9, 2011, 149 gravitated toward Like: “What’s the History of the Awesome Button (That Eventually Became the Like Button) on Facebook?”

But if you use Yahoo or Gmail or Hotmail for your e-mail, you “lose your constitutional protections immediately,” according to a lawyer for the Electronic Freedom Foundation. The FBI can just ask the company for the information—no judicial paperwork needed, no permission required—as long as it can argue later that it’s part of an “emergency.” “The cops will love this,” says privacy advocate Robert Gellman about cloud computing. “They can go to a single place and get everybody’s documents.” Because of the economies of scale in data, the cloud giants are increasingly powerful. And because they’re so susceptible to regulation, these companies have a vested interest in keeping government entities happy. When the Justice Department requested billions of search records from AOL, Yahoo, and MSN in 2006, the three companies quickly complied.


pages: 224 words: 64,156

You Are Not a Gadget by Jaron Lanier


1960s counterculture, accounting loophole / creative accounting, additive manufacturing, Albert Einstein, call centre, cloud computing, crowdsourcing, death of newspapers, digital Maoism, Douglas Hofstadter, Extropian, follow your passion, hive mind, Internet Archive, Jaron Lanier, jimmy wales, John Conway, John von Neumann, Kevin Kelly, Long Term Capital Management, Network effects, new economy, packet switching, PageRank, pattern recognition, Ponzi scheme, Ray Kurzweil, Richard Stallman, Silicon Valley, Silicon Valley startup, slashdot, social graph, stem cell, Steve Jobs, Stewart Brand, Ted Nelson, telemarketer, telepresence, The Wisdom of Crowds, trickle-down economics, Turing test, Vernor Vinge, Whole Earth Catalog

Chapter 4 Digital Peasant Chic Chapter 5 The City Is Built to Music Chapter 6 The Lords of the Clouds Renounce Free Will in Order to Become Infinitely Lucky Chapter 7 The Prospects for Humanistic Cloud Economics Chapter 8 Three Possible Future Directions PART THREE The Unbearable Thinness of Flatness Chapter 9 Retropolis Chapter 10 Digital Creativity Eludes Flat Places Chapter 11 All Hail the Membrane PART FOUR Making The Best of Bits Chapter 12 I Am a Contrarian Loop Chapter 13 One Story of How Semantics Might Have Evolved PART FIVE Future Humors Chapter 14 Home at Last (My Love Affair with Bachelardian Neoteny) Acknowledgments Preface IT’S EARLY in the twenty-first century, and that means that these words will mostly be read by nonpersons—automatons or numb mobs composed of people who are no longer acting as individuals. The words will be minced into atomized search-engine keywords within industrial cloud computing facilities located in remote, often secret locations around the world. They will be copied millions of times by algorithms designed to send an advertisement to some person somewhere who happens to resonate with some fragment of what I say. They will be scanned, rehashed, and misrepresented by crowds of quick and sloppy readers into wikis and automatically aggregated wireless text message streams.

Some of the better-known figures in this tradition include the late Joseph Weizenbaum, Ted Nelson, Terry Winograd, Alan Kay, Bill Buxton, Doug Englebart, Brian Cantwell Smith, Henry Fuchs, Ken Perlin, Ben Schneiderman (who invented the idea of clicking on a link), and Andy Van Dam, who is a master teacher and has influenced generations of protégés, including Randy Pausch. Another important humanistic computing figure is David Gelernter, who conceived of a huge portion of the technical underpinnings of what has come to be called cloud computing, as well as many of the potential practical applications of clouds. And yet, it should be pointed out that humanism in computer science doesn’t seem to correlate with any particular cultural style. For instance, Ted Nelson is a creature of the 1960s, the author of what might have been the first rock musical (Anything & Everything), something of a vagabond, and a counterculture figure if ever there was one.

CHAPTER 4 Digital Peasant Chic ANOTHER PROBLEM WITH the philosophy I am criticizing is that it leads to economic ideas that disfavor the loftiest human avocations. In this and the following sections I will address an orthodoxy that has recently arisen in the world of digital culture and entrepreneurship. Problems associated with overly abstract, complex, and dangerous financial schemes are connected with the ideals of “open” or “free” culture. Ruining an Appointment with Destiny The ideology that has overtaken much of the cloud-computing scene—exemplified by causes like free or open culture—has the potential to ruin a moment that has been anticipated since at least as far back as the nineteenth century. Once technological advances are sufficient to potentially offer all people lives filled with health and ease, what will happen? Will only a tiny minority benefit? While the relative number of desperately poor people is decreasing, income differences between the rich and the poor are increasing at an accelerating rate.


pages: 25 words: 5,789

Data for the Public Good by Alex Howard


23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, Network effects, openstreetmap, Silicon Valley, slashdot, social software, social web, web application

Advocates, watchdogs and government officials now have new tools for data journalism and open government. Globally, there’s a wave of transparency that will wash over every industry and government, from finance to healthcare to crime. In that context, open government is about much more than open data — just look at the issues that flow around the #opengov hashtag on Twitter, including the nature identity, privacy, security, procurement, culture, cloud computing, civic engagement, participatory democracy, corruption, civic entrepreneurship or transparency. If we accept the premise that Gov 2.0 is a potent combination of open government, mobile, open data, social media, collective intelligence and connectivity, the lessons of the past year suggest that a tidal wave of technology-fueled change is still building worldwide. The Economist’s support for open government data remains salient today: “Public access to government figures is certain to release economic value and encourage entrepreneurship.


pages: 441 words: 136,954

That Used to Be Us by Thomas L. Friedman, Michael Mandelbaum


3D printing, Affordable Care Act / Obamacare, Albert Einstein, Amazon Web Services, American Society of Civil Engineers: Report Card, Andy Kessler, Ayatollah Khomeini, bank run, barriers to entry, Berlin Wall, blue-collar work, Bretton Woods, business process, call centre, carbon footprint, Carmen Reinhart, Cass Sunstein, centre right, Climatic Research Unit, cloud computing, collective bargaining, corporate social responsibility, Credit Default Swap, crowdsourcing, delayed gratification, energy security, Fall of the Berlin Wall, fear of failure, full employment, Google Earth, illegal immigration, immigration reform, income inequality, job automation, Kenneth Rogoff, knowledge economy, Lean Startup, low skilled workers, Mark Zuckerberg, market design, more computing power than Apollo, Network effects, obamacare, oil shock, pension reform, Report Card for America’s Infrastructure, rising living standards, Ronald Reagan, Rosa Parks, Saturday Night Live, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, the scientific method, Thomas L Friedman, too big to fail, University of East Anglia, WikiLeaks

Keeping up with the demand requires frantic expansion: Each day, Jassy’s operation adds enough computing muscle to power one whole circa 2000, when it was a $2.8 billion business. The physical expansion of all that data takes place in Amazon’s huge, specially designed buildings—the biggest can reach 700,000 square feet, or the equivalent of roughly 16 football fields. These interconnected facilities, scattered all over the world, are where AWS conducts its business: cloud computing. The “cloud” refers to the amorphous, out-of-sight, out-of-mind mess of computer tasks that happen on someone else’s equipment. Though the cloud is still in its infancy, in 2009 alone global data flows grew by 50 percent thanks in part to its emergence, along with wireless connectivity. “The more people are connected, the more people connect,” said Hewlett-Packard’s CEO, Léo Apotheker, “so you get these network effects, and that is just flattening the world even more every day.”

A company in Uruguay specializing in pacemakers built the prototype. This is the latest in venture investing: a lean start-up whose principals are rarely in the same place at the same time and which takes advantage of all the tools of the connected world—teleconferencing, e-mail, the Internet, Facebook, Twitter, and faxes—to make use of the best expertise and low-cost, high-quality manufacturing. We’ve described cloud computing. This is cloud manufacturing. The early clinical trials for EndoStim were conducted in India and Chile and are now being expanded into Europe. “What they have in common,” said Hogg, “is superb surgeons with high levels of skill, enthusiasm for the project, an interest in research, and reasonable costs.” What’s in it for America? As long as the venture money, core innovation, and key management comes from this country—a lot.

The whole system is being run out of a little house and garage with a dozen employees, a bunch of laptops, and cheap Internet connectivity. Not surprisingly, the Sinha team began building its own core software with some free, open source code downloaded from the cloud. Realizing that they did not have the capital themselves to invest in large-scale hardware, they run their whole business on cloud-computing servers hosted at a data center in Noida, a suburb of Delhi. The core idea of the business, says Abhishek, is “to close the last mile—the gap where government services end and the consumer begins.” There is a huge business in closing that last mile for millions of poor Indians, who, without it, can’t get proper health care, education, or insurance. Eko, Abhishek added, “leveraged existing telecom networks and existing distribution networks” and with relatively little capital invested is now able to serve more than 700,000 low-income customers across eight Indian states.


pages: 606 words: 157,120

To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov


3D printing, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, augmented reality, Automated Insights, Berlin Wall, big data - Walmart - Pop Tarts, Buckminster Fuller, call centre, carbon footprint, Cass Sunstein, choice architecture, citizen journalism, cloud computing, cognitive bias, crowdsourcing, data acquisition, Dava Sobel, disintermediation, East Village,, Fall of the Berlin Wall, Filter Bubble, Firefox, Francis Fukuyama: the end of history, frictionless, future of journalism, game design, Gary Taubes, Google Glasses, illegal immigration, income inequality, invention of the printing press, Jane Jacobs, Jean Tirole, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Kickstarter, license plate recognition, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Narrative Science, Nicholas Carr, packet switching, PageRank, Paul Graham, Peter Singer: altruism, Peter Thiel,, placebo effect, pre–internet, Ray Kurzweil, recommendation engine, Richard Thaler, Ronald Coase, Rosa Parks, self-driving car, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Slavoj Žižek, smart meter, social graph, social web, stakhanovite, Steve Jobs, Steven Levy, Stuxnet, technoutopianism, the built environment, The Chicago School, The Death and Life of Great American Cities, the medium is the message, The Nature of the Firm, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, transaction costs, urban decay, urban planning, urban sprawl, Vannevar Bush, WikiLeaks

In 2010 Wolf penned something of a manifesto for this nascent movement, which was published—not bad for a manifesto—in the New York Times Magazine, launching the Quantified Self movement not just nationally but globally. In his article, Wolf identifies four factors that explain the meteoric rise of self-tracking over the last few years. First, electronic sensors shrank in size and became more powerful. Second, once they entered our smartphones, they became ubiquitous. Third, social media—from Facebook to Twitter—made sharing seem normal. Fourth, the idea of cloud computing made it possible (and acceptable) to offload one’s data onto distant servers, where, merged with the data of other users, it can be expected to yield better results. (Wolf, of course, doesn’t put it this way; in the tradition of Wired mysticism, he invokes a spiritual dimension, writing of “the rise of a global superintelligence known as the cloud.”) The sharing and cloud aspects are particularly important: revealing one’s own measurements can provide additional motivation (e.g., many geeks desperate to lose weight are now buying electronic scales that automatically tweet their weight to their Twitter followers—yet another example of a solutionist intervention not available just ten years ago) while also fostering the same sense of community that propels well-established programs like Weight Watchers or Alcoholics Anonymous.

For the urban dweller, the end of the process of garbage disposal is the moment when the bag is thrown into the hole.” To know what’s inside our smart trash bins—which is what projects like BinCam seek to tell us—is not the same as to know what happens to our garbage once it leaves them. The latter is much more important to environmental reform than the former. We know as little about garbage disposal as we do about cloud computing; only rarely do we ask what exactly it entails, why we do it the way we do, and how we can do it differently. Monitoring how much garbage we throw away, how much water we consume, and how much information we upload and download from “the cloud” doesn’t get us any closer to understanding how these complex systems function. “Numeric imagination” enables us to think in numbers—that is, to ponder how much we can consume and, in the best of all cases, what we can unplug—but it never challenges us to think of how a different set of numbers might be generated.

Our world is ridden with conflict and antagonism—often a good thing, for it does not allow one particular group to enjoy near-universal hegemony for too long—and our laws are imperfect by design and in need of constant revision and reinterpretation. All our actions have unpredictable consequences, but instead of shying away from this predicament, we should try to rebuild our social and political structures accordingly. We are suckers for various technologies—even the most inconsequential—but we rarely recognize that their use is only made possible by vast sociotechnological systems, like water supply and now cloud computing, that mostly remain invisible to us but have consequences much more significant than our own use of the technologies these systems make possible. This understanding of the human condition lends itself to a very different set of technological fixes. Contrast our usual suspect, metered electricity, with an approach pioneered by Swedish designers from the Interactive Institute under the name of “erratic appliances.”


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, computer age, computer vision, conceptual framework, corporate governance, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter,, Erik Brynjolfsson, Filter Bubble, Frank Levy and Richard Murnane: The New Division of Labor, 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, lump of labour, Marshall McLuhan, Narrative Science, natural language processing, Network effects, optical character recognition, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, semantic web, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, 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!, young professional

Kurzweil checks his own homework in ‘How My Predictions are Faring’, Oct. 2010 <> (accessed 27 March 2015). 27 See e.g. Joel Garreau, Radical Evolution (2005), and ‘Coming To an Office Near You’, Economist, 18 Jan. 2014. 28 See e.g. the work of Singularity University at <> (accessed 23 March 2015). 29 For a clear introduction to the cloud and cloud computing, and a clear indication of its mounting signifiance, see Kuan Hon and Christopher Millard, ‘Cloud Technologies and Services’, in Cloud Computing Law, ed. Christopher Millard (2013). 30 John Kelly and Steve Hamm, Smart Machines (2013). 31 Nick Bostrom, Superintelligence (2014). 32 See e.g. Tim Bradshaw, ‘Scientists and Investors Warn on AI’, Financial Times, 12 Jan. 2015. 33 Kelly and Hamm, Smart Machines, and Kieron O’Hara et al., Web Science: Understanding the Emergence of Macro-Level Features of the World Wide Web (2013). 34 Soshana Zuboff, In the Age of the Smart Machine (1988), 9. 35 Zuboff, In the Age of the Smart Machine, 10. 36 Some writers treat ‘machine learning’ as yet another synonym.

Those who object often demand that the people and systems that replace the professions should attain a level of moral virtuosity, for example, or a degree of empathy that palpably outstrips those who currently work in the professions. As Voltaire would caution, in reforming or transforming the professions, we should not let the best be the enemy of the good.29 Frequently, the question that should be asked of a proposed new system or service is not how it compares to traditional service, but whether it would be better than nothing at all. 1 See e.g. Christopher Millard (ed.), Cloud Computing Law (2013) and Ian Lloyd, Information Technology Law (2014). 2 See Misha Glenny, DarkMarket: Cyberthieves, Cybercops and You (2011), or Jamie Bartlett, The Dark Net (2014). 3 A classic difficulty in relation to professional service is that the value derived from any advice or guidance drawn from professional work can be unclear and difficult for recipients to figure out for themselves. Does a student succeed at school because of the support of a particular teacher, or was his or her own ability and effort the cause?

Hobsbawm, Eric, and George Rudé, Captain Swing (London: Phoenix Press, 1969). Hodkinson, Paul, ‘E-auctions: Reviewing the Review’, Legal Week, 9 June 2005. Hoftstadter, Douglas, and Daniel Dennett (eds.), The Mind’s I (New York: Basic Books, 1982). Holmes, Andrew, Commoditization and the Strategic Response (Aldershot: Gower, 2008). Hon, Kuan, and Christopher Millard, ‘Cloud Technologies and Services’, in Cloud Computing Law, ed. Christopher Millard (Oxford: Oxford University Press, 2013). Horn, Michael, and Curtis Johnson, Disrupting Class (New York: McGraw-Hill, 2008). House, Patrick, ‘The Electronic Holy War’, New Yorker, 15 Mar. 2014. Tara Hovarth, Hana Azman, Gail Kennedy, and George Rutherford, ‘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).


pages: 528 words: 146,459

Computer: A History of the Information Machine by Martin Campbell-Kelly, William Aspray, Nathan L. Ensmenger, Jeffrey R. Yost


Ada Lovelace, air freight, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Apple's 1984 Super Bowl advert, barriers to entry, Bill Gates: Altair 8800, borderless world, Buckminster Fuller, Build a better mousetrap, Byte Shop, card file, cashless society, cloud computing, combinatorial explosion, computer age, deskilling, don't be evil, Douglas Engelbart, Dynabook, fault tolerance, Fellow of the Royal Society, financial independence, Frederick Winslow Taylor, game design, garden city movement, Grace Hopper, informal economy, interchangeable parts, invention of the wheel, Jacquard loom, Jacquard loom, Jeff Bezos, jimmy wales, John von Neumann, linked data, Mark Zuckerberg, Marshall McLuhan, Menlo Park, natural language processing, Network effects, New Journalism, Norbert Wiener, Occupy movement, optical character recognition, packet switching, PageRank, pattern recognition, pirate software, popular electronics, prediction markets, pre–internet, QWERTY keyboard, RAND corporation, Robert X Cringely, Silicon Valley, Silicon Valley startup, Steve Jobs, Steven Levy, Stewart Brand, Ted Nelson, the market place, Turing machine, Vannevar Bush, Von Neumann architecture, Whole Earth Catalog, William Shockley: the traitorous eight, women in the workforce, young professional

Companies and organizations, which in the past tended to maintain their own data locally, increasingly are contracting with specialists such as,, EMC, IBM, Google, and other leaders in the rapidly growing field of cloud computing—using remote servers for various data and software applications needs. This allows the staff of client firms and organizations to readily access and share data with colleagues, customers, suppliers, and other authorized users—and to benefit from suppliers’ economies of scale and expertise in data storage and delivery. SOCIAL NETWORKING: FACEBOOK AND TWITTER Cloud computing is also at the heart of online social networking. Web-based social networking generally facilitates users’ ability to create a profile on the web and interact with others. For most individuals, social networking has been the most life-changing aspect of Web 2.0.

That year Google achieved revenue of $16.6 billion and net income of $4.2 billion. Google continues to dominate the search field with 1.7 trillion annual searches (in 2011, representing roughly a two-thirds share). While search-based advertising revenue remained its primary source of income, Google successfully moved into e-mail services (Gmail), maps and satellite photos, Internet video (with its 2006 acquisition of YouTube), cloud computing, digitizing books, and other endeavors. More recently, Google has also been an important participant in open-source mobile platforms that are transforming computing. GOING MOBILE From shortly after the advent of personal computing, computers have become increasingly mobile. In 1968 Alan Kay first conceptualized the notion of a portable computer, ideas formalized as the “Dynabook” concept at Xerox PARC in 1972.

See Vacuum tubes CBS television network, 110–112 CD-ROM disks and drives, 267–269, 273–274 Cellphones, 216, 304 Census data processing, 13–18, 24–25, 34, 99–100, 102, 109, 114 Central Telegraph Office (UK), 12–13, 88 (photo) Charge cards, 157, 159 Chase, George, 55 Chat rooms, 272 Check processing, 136 Checkless and cashless society, 158 Checks, bank, 9–10, 160, 161 Chemical Bank, 158 Chips, silicon, 194 (photo), 196, 216, 221, 222, 232, 296 See also Integrated circuits Chu, Jeffrey Chuan, 124 Church, Alonzo, 59, 60 Circuit boards, digital, 217 Cirrus ATM network, 161 Civil engineering tables, 4 Clark, Jim, 289 Clearing, check and credit card, 158, 159, 160 Clearing houses, 8–11, 18, 29, 136, 158 Clerks in bank clearing houses, 9–10 as human computers, 3–6, 50–51, 52–54, 65, 67–68, 71 record-keeping duties of, 25 as typewriter operators, 22, 24–25 See also Female clerical labor Cloud computing, 300 COBOL, 174, 183, 185, 191, 192 Code breaking, 61, 69, 80, 81–82, 103 Coding. See Programming Cold War, 137, 149–151, 152 Colmar, Thomas de, 27 Colossus computer, 81–82 Columbia University, 55, 104 Committee on Data Systems and Languages (CODASYL), 174 Commodore Business Machines, 241, 242 Commodore PET, 241 Compact Disk-Read Only Memory (CD-ROM), 267–269, 273–274 Compaq, 197, 248, 250, 251 Compatible-range concept, 125–126, 130–133 Compilers, 171, 173, 174, 175 Comptometers, 18, 27–29, 53 CompuServe, 271–273, 290–291 Computer, use of term, 3 Computer Associates, 188 Computer control systems, 134–135 Computer games, 218, 243, 272 Computer industry, 19, 21, 25, 31, 68–70, 135–138 Computer liberation movement, 233–235, 237, 238, 239 Computer magazines, 238 Computer modeling, 137 Computer programmers.


pages: 317 words: 84,400

Automate This: How Algorithms Came to Rule Our World by Christopher Steiner


23andMe, Ada Lovelace, airport security, Al Roth, algorithmic trading, backtesting, big-box store, Black-Scholes formula, call centre, cloud computing, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, Donald Trump, Douglas Hofstadter, dumpster diving, Flash crash, Gödel, Escher, Bach, High speed trading, Howard Rheingold, index fund, Isaac Newton, John Maynard Keynes: technological unemployment, knowledge economy, late fees, Mark Zuckerberg, market bubble, medical residency, Narrative Science, PageRank, pattern recognition, Paul Graham, prediction markets, quantitative hedge fund, Renaissance Technologies, ride hailing / ride sharing, risk tolerance, Sergey Aleynikov, side project, Silicon Valley, Skype, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, transaction costs, upwardly mobile, Watson beat the top human players on Jeopardy!, Y Combinator

And those with the means are already rich. It’s a foible of capitalism that is hardly new. But without the pressure applied by our financial markets, there’s no denying that our communications networks, be they word of mouth, pigeons, telegraphs, telephones, television, the Web, or dedicated strands of dark fiber, would have been developed at a slower pace. Without light-speed communication, there would be no cloud computing. Without cloud computing, which allows remote servers and computers to extend their processing power almost anywhere, all-knowing algorithms wouldn’t be possible. In 1815, Nathan Rothschild was one of the richest people in the world, and he regularly used his access to technology to add to his fortune. Along with his four brothers, he ran banks in London, Paris, Vienna, Naples, and Frankfurt. The brothers often used carrier pigeons carrying tiny rolls of encoded messages to communicate from bank to bank.

., 128, 130, 186, 190, 192, 198 algorithmic trading in, 40, 46, 49, 51 communication between markets in New York and, 42, 113–18, 123–24 options trading in, 27 Chicago, University of, 23, 140, 186, 191 Chicago Board Options Exchange, 27, 36, 38, 40, 114 Chicago Cubs, 142 Chicago Mercantile Exchange, 40, 51–52, 133 Chicago Research and Trading, 40, 46 Chicago Tribune, 8 chimpanzees, humans’ divergence from, 161 Cho, Rich, 142 Chopin, Frederic, 96, 98 chorales, 93 chords, musical, 82, 106–10 Cielo Networks, 124 Cincinnati Stock Exchange, 46 Citadel, 190 Citi Capital Markets, 200 Citigroup, 186, 192 Civil War, 122 classical music, algorithms and, 89–103 Clinton, Bill, 176 cloud computing, 120–21 Cloudera, 206, 216 Clue, 135 CNBC, Dow crash and, 2–3 CNN, 137 Codecademy, 9–10 cognitive science, 97 Cold War, 136, 168, 169 collateralized debt obligations (CDOs), 189, 209 Columbia Records, 87 Columbia University, 162 Combinet, 131 Come Away with Me, 82–83 Comes the Fiery Night (Cope), 100–101 commerce, personality types in, 163 commodities, golden mean and, 57 commodities options, 22 commodities trading, 20–25, 27, 51, 130 communication: human, 170–71 under stress, 145 voice, 195 communications networks, financial markets and, 120–25 communism, 136 competition, stock prices and, 27 computer code, 73 computer dating, algorithms for, 143–45 computer languages, 74 computers, 73 circuitry of, 74 early home, 28 early office use of, 19–20 handheld, 36–39, 41, 44–45 improvements in, 48 Peterffy’s early trading via, 12–16 computer science, 71, 157, 188, 200, 201, 213 Cope’s algorithmic music and, 91 congestive heart failure, 159 consumer data, 192–93 Conway, Kelly, 177, 180–83, 186–88, 190, 191–97, 198 coordinated algorithms, 5 Cope, David, 89–102 Emmy created by, 93–99 hostility toward the algorithmic music of, 90–91, 95, 96–99 on question of authorship, 95 Cornell University, 213 coronary bypass surgery, 158 correlative risk, 65 Correlator (algorithm), 42–45 Cosby, Bill, 34 cosines, 106 cowboy bets, 30 Cramer, Jim, 3, 4 creativity, by algorithms, 76–77 credit default swaps (CDSs), 65 Credit Suisse, 116, 186 Credit Suisse First Boston, 189 crude oil trades, 51 Cuba, 153 currency rates, fluctuations in, 54 customer service, 178 fraudulent calls by, 193 personality types in, 163, 164, 180–83, 195, 214 cytotechnologists, 153 Dalhousie University, 105 dark fiber, 114–20, 122 data: gathering of, 203–5 sifting of, 62, 206–7 data feeds, hacking of, 15, 17 data mines, 206 Da Vinci Code, The (Brown), 57 decision trees: algorithms as, 6 binary, 26, 171 declarative statements, 180 Deep Blue, 126–27, 129, 133, 141 Defense Department, U.S., 73 Office of Net Assessment at, 140 delta neutral trades, 33 Dennett, Daniel, 97 Deo, 81–82 derivatives, 60 values of, 41–42 Deutsche Bank, 190 deviations, 63 differential equations: in options trading, 22 partial, 23 digital files, 81 Disney studios, 76 disruptors, in music composition, 102–3 divisors, algorithm for, 55 “DJ Got Us Fallin’ in Love,” 89 DNA, 70, 159 algorithmic analysis of, 160–61 atomic structure of, 56 Dodge, Anne, 156–57 Donino, Tom, 4 dot-com crash, 188 Dow Jones, news service for trading bots by, 48 Dow Jones Industrial Average, 2–4, 191 driving, algorithms for, 214–16 Dropbox, 199 drought, 130 drugs: anesthetic, 160 in PDR, 146 Duke University, 189, 198 DuPont, 29–30 Durant, Kevin, 142 Eagles, the, 78 Eastern Europe, 193, 218 eBay, 188 economy: growth sectors in, 218–20 troubled recent, 189, 208, 210–11 Edison, Thomas, 123 education: in math and science, 218–19 personality types in, 195 in programming, 9–10 Education Department, New York City, 147–48 Egypt, 140 eHarmony, 144 Einhorn, David, 128 Eisen, Michael, 1 elections, of 1992, 176 electronic trading networks, 185 Elements (Euclid), 55 Elizabeth Wende Breast Clinic, 154 eLoyalty, 177, 180–83, 186–88, 191–97 e-mail, 195–96, 204 language patterns and social influence in, 212–14 EMI, 87 Emily Howell (algorithm), 99 Emmy (algorithm), 90, 94–99 recording contract for, 95–96 Emory University, 189 emotions-driven people, 172–73, 174, 175, 176, 180, 187, 194, 197 empathy, 176 engineering, financial, 209 engineers, 62 algorithms and, 6 career goals of, 189–90, 198, 200, 210–11, 218–20 at Facebook, 70 at Google, 47 in intelligence analysis, 139–40 music algorithms and, 78, 79 Peterffy as, 32, 48 in sports management, 142 on Wall Street, 13, 23, 24, 46, 47, 49, 119, 185, 202, 207, 211 England, 72 English-French translation software, 178–79 entrepreneurs, 208–11 online, 53 Epagogix, 75 Epstein, Theo, 142 equity exchanges, 38 Erasmus of Rotterdam, 69 Euclid, 55 Euclidean algorithm, 55 Euler, Leonhard, 64, 65, 68–71, 105, 111 Euler’s formula, 70–71 Euphrates Valley, 55 Europe: algorithmic trading in, 47, 49 pop charts in, 79 Evanston, Ill., 3, 218 “Explanation of Binary Arithmetic” (Leibniz), 58 ExxonMobil, 50 Facebook, 198–99, 204–6, 214 graph theory and, 70 face-reading algorithms, 129, 161 Falchuk, Myron, 157 Farmville, 206 fat tails, 63–64 FBI, 137 FedEx, 116 Ferguson, Lynne, 87 Fermat, Pierre, 66–67 fiber: dark, 114–20, 122 lit, 114 fiber optic cables, 117, 124, 192 Fibonacci, Leonardo, 56–57 Fibonacci sequence, 57 Fidelity, 50 finance, probability theory and, 66 financial markets, algorithms’ domination of, 24 financial sector, expansion of, 184, 191 see also Wall Street Finkel, Eli, 145 Finland, 130 First New York Securities, 4 Fisher, Helen, 144 Flash Crash of 2010, 2–5, 48–49, 64, 184 Forbes magazine, 8 foreign exchange, golden mean and, 57 Fortran, 12, 38 Fortune 500 companies, Kahler’s methods at, 176 Fourier, Joseph, 105–6 Fourier series, 105–7 Fourier transforms, 82 401K plans, 50 Fox News, 137 fractal geometry, 56 France, 61, 66, 80, 121, 147 Frankfurt, 121 fraud, eLoyalty bots and, 193 French-English translation software, 178–79 From Darkness, Light, 99 galaxies, orbital patterns of, 56 gambling: algorithms and, 127–35 probability theory and, 66, 67 game theory, 58 algorithms and, 129–31 and fall of Soviet Union, 136 in organ donor networks, 147–49 in politics, 136 sports betting and, 133–35 terrorism prevention by, 135–40 gastroenterology, 157 Gauss, Carl Friedrich, 61–65 Gaussian copula, 65, 189 Gaussian distributions, 63–64 Gaussian functions, 53 GE, 209, 213 Geffen, 87 General Mills, 130 General Motors, 201 genes, algorithmic scanning of, 159, 160 geometry, 55 of carbon, 70 fractal, 56 George IV, king of England, 62 Germany, 26, 61, 90 West, 19 Getco, 49, 116, 118 Glenn, John, 175 gluten, 157 Gmail, 71, 196 Gödel, Escher, Bach: An Eternal Golden Braid (Hofstadter), 97 gold, 21, 27 Gold and Stock Telegraph Company, 123 Goldberg, David, 219 golden mean, 56–57 Goldman Sachs, 116, 119, 204, 213 bailout of, 191 engineering and science talent hired by, 179, 186, 187, 189 Hull Trading bought by, 46 Peterffy’s buyout offer from, 46 Gomez, Dominic, 87 goodwill, 27 Google, 47, 71, 124, 192, 196, 207, 213, 219 algorithm-driven cars from, 215 PageRank algorithm of, 213–14 Gorbachev, Mikhail, 136 Göttingen, 122 Göttingen, University of, 59, 65 grain prices, hedging algorithm for, 130 grammar, algorithms for, 54 Grammy awards, 83 graph theory, 69–70 Great Depression, 123 Greatest Trade Ever, The (Zuckerman), 202 Greece, rioting in, 2–3 Greenlight Capital, 128 Greenwich, Conn., 47, 48 Griffin, Blake, 142 Griffin, Ken, 128, 190 Groopman, Jerome, 156 Groupon, 199 growth prospects, 27 Guido of Arezzo, 91 guitars: Harrison’s twelve–string Rickenbacker, 104–5, 107–9 Lennon’s six–string, 104, 107–8 hackers: as algorithm creators, 8, 9, 178 chat rooms for, 53, 124 as criminals, 7–8 for gambling, 135 Leibniz as, 60 Lovelace as, 73 online, 53 poker played by, 128 Silicon Valley, 8 on Wall Street, 17–18, 49, 124, 160, 179, 185, 201 Wall Street, dawn of hacker era on, 24–27 haiku, algorithm-composed, 100–101 Haise, Fred, 165–67 Hal 9000, 7 Hammerbacher, Jeffrey, 201–6, 209, 216 Handel, George Frideric, 68, 89, 91 Hanover, 62 Hanto, Ruthanne, 151 Hardaway, Penny, 143 “Hard Day’s Night, A,” opening chord of, 104–10 hardware: escalating war of, 119–25 Leibniz’s binary system and, 61 Harrah’s, 135 Harrison, George, 103–5, 107–10 on Yahoo!


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Technical Blogging: Turn Your Expertise Into a Remarkable Online Presence by Antonio Cangiano


Albert Einstein, anti-pattern, bitcoin, bounce rate, cloud computing,, John Gruber, Lean Startup, Network effects, revision control, search engine result page, slashdot, software as a service, web application

Dedicated servers: A server is entirely dedicated to you. Just like VPS hosting, dedicated servers come in managed and unmanaged forms, depending on the provider. Some people even go so far as to provide their own machines that are hosted in a local data center as part of a so-called colocation arrangement. Cloud computing: Computing resources are provided and billed based on usage. You could rent three instances (think the equivalent resources of three dedicated servers) an hour and switch back to a single instance an hour later when the traffic spike is gone. The value of cloud computing mainly resides in the ability to easily scale your computing needs without requiring a datacenter investment upfront. The cost scales accordingly with the resources you need. Unless you already rent web servers and have experience working with them, start with shared hosting.

It’s also worth noting the official list of recommended WordPress hosting companies at For unmanaged VPS, Linode is hard to beat.[25] For managed VPS, both ServInt and LiquidWeb are decent choices (albeit fairly expensive ones).[26] How about dedicated servers? You don’t really need to look at these options quite yet; nevertheless, SoftLayer (unmanaged) and again ServInt (managed) are both excellent choices.[27] Finally, the king of cloud computing is Amazon AWS,[28] with other providers such as Rackspace and SoftLayer also offering popular cloud-based solutions.[29] An honorable mention goes to companies that specialize in WordPress hosting and provide you with simplicity and convenience despite allowing virtually the same degree of flexibility you’ll find with self-hosted WordPress. WP Engine, ZippyKid, and are reputable choices,[30] but they offer a premium service that is priced accordingly.


pages: 308 words: 84,713

The Glass Cage: Automation and Us by Nicholas Carr


Airbnb, Andy Kessler, Atul Gawande, autonomous vehicles, business process, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cloud computing, David Brooks, deliberate practice, deskilling, Elon Musk, Erik Brynjolfsson, Flash crash, Frank Gehry, Frank Levy and Richard Murnane: The New Division of Labor, Frederick Winslow Taylor, future of work, global supply chain, Google Glasses, Google Hangouts, High speed trading, indoor plumbing, industrial robot, Internet of things, Jacquard loom, Jacquard loom, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, knowledge worker, Lyft, Mark Zuckerberg, means of production, natural language processing, new economy, Nicholas Carr, Norbert Wiener, Oculus Rift, pattern recognition, Peter Thiel, place-making, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, RAND corporation, randomized controlled trial, Ray Kurzweil, recommendation engine, robot derives from the Czech word robota Czech, meaning slave, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, software is eating the world, Stephen Hawking, Steve Jobs, TaskRabbit, technoutopianism, The Wealth of Nations by Adam Smith, Watson beat the top human players on Jeopardy!

The technology of the 1990s was not up to making the world machine-readable, and after the dot-com crash, investors were in no mood to bankroll the installation of expensive microchips and sensors everywhere. But much has changed in the succeeding fifteen years. The economic equations are different now. The price of computing gear has fallen sharply, as has the cost of high-speed data transmission. Companies like Amazon, Google, and Microsoft have turned data processing into a utility. They’ve built a cloud-computing grid that allows vast amounts of information to be collected and processed at efficient centralized plants and then fed into applications running on smartphones and tablets or into the control circuits of machines.14 Manufacturers are spending billions of dollars to outfit factories with network-connected sensors, and technology giants like GE, IBM, and Cisco, hoping to spearhead the creation of an “internet of things,” are rushing to develop standards for sharing the resulting data.

Brin is mistaken, though, in suggesting that Glass and other such devices represent a break from computing’s past. They give the established technological momentum even more force. As the smartphone and then the tablet made general-purpose, networked computers more portable and personable, they also made it possible for software companies to program many more aspects of our lives. Together with cheap, friendly apps, they allowed the cloud-computing infrastructure to be used to automate even the most mundane of chores. Computerized glasses and wristwatches further extend automation’s reach. They make it easier to receive turn-by-turn directions when walking or riding a bike, for instance, or to get algorithmically generated advice on where to grab your next meal or what clothes to put on for a night out. They also serve as sensors for the body, allowing information about your location, thoughts, and health to be transmitted back to the cloud.

., 122 cancer, 70–71 capital investments, 18, 28, 30, 31 capitalism, 21–22, 24, 28, 31, 109, 116, 160 Carlsen, Magnus, 82 cars and driving, 3–18, 34, 46 accidents, 7, 70, 91, 153, 154–55, 207, 208 author’s experience with, 3–6, 13–14, 80, 81 automation bias and, 69–70 GPS in, 128, 130, 136–37 luxury, 8 manual vs. automatic transmission in, 3–6 paper maps and, 130 self-driving, 6–8, 10, 12, 13, 120, 153–56, 183–87, 193, 204, 207, 208 while sleepy, 71–72 Cartesian dualism, 148–49 Cartlidge, John, 77 cartoons, 19, 33 Caruthers, Felix P., 174 cascading failures, 155 Centers for Disease Control, 220 Cerner Corporation, 96 Chabris, Christopher, 201 Chapanis, Alphonse, 158 Checklist Manifesto, The (Gawande), 104 Cheng, Britte Haugan, 73 chess playing, 12, 121 China, 31, 167 Churchill, Winston, 139 CIA, 120 Cisco, 195 City University London, 70 Clark, Andy, 149–51 Clarke, Arthur C., 197–98 cloud computing, 195, 202, 209 cognition, cognitive skills, 11–12, 56–58, 71–74, 81, 120, 121, 148–51, 165 of doctors, 105 embodied, 149–51, 213 cognitive map, 129–30, 135 cognitive psychologists, 72–76, 81, 129–30 Colgan Air, 45 communication, 36, 163, 198 doctor-patient, 103–6 Communist Manifesto (Marx and Engels), 225 computer-aided design (CAD), 138–42, 144, 145, 167, 219, 229–30 computer games, 75, 177–80, 219 computer programmers, 161, 162, 168 computers, 1, 2, 17, 33, 37, 38, 40, 159 architecture and design and, 138–47 automation and, 36, 43, 50–58, 62, 66–67, 69, 90, 91, 202–3 aviation and, 43, 46, 50–52, 54, 55, 57, 62, 153, 168, 170, 172–73 avocations and, 12 benefits of transferring work to, 17–18 boundary between humans and, 10–12 brain compared with, 119, 151 capabilities of, 8–9 in cars, 7, 8–9 costs of transferring work to, 18, 28, 30, 66–67 dependency on, 12–13 effects on workload of, 90, 91 ergonomics and, 164–68 expectation of aid of, 193–95 health care and, 93–106 human compared with, 153 as media devices, 219 memory experiment and, 79 mental processes and, 74 monitoring of, 17 oracle machine, 119–20 satellite-linked, 125–37 speed of, 118–22, 139, 156, 164, 173, 219 vocations and, 12 wearable, 12, 201 white-collar, 93–106 computer scientists, 156 computer simulation models, 93, 97 concentration, 200 Concours de la Sécurité en Aéroplane, 46 consciousness, 83, 119n, 121, 148–49, 150, 187 Continental Connection, 43–45, 54, 154 corporate auditors, 115 Cowen, Tyler, 31 craft workers, 23, 106, 109 Crawford, Kate, 122–23 Crawford, Matthew, 147–48 creativity, 10, 12, 14, 143, 144, 167, 206, 229 Cross, Nigel, 143–44 Csikszentmihalyi, Mihalyi, 14–16, 18, 85, 228–29 Cukier, Kenneth, 122 culture, 124, 131, 196, 198, 217, 220, 226 Curtiss C-2 biplane, 46–47 cutting grass, 215–16 Cybernetics, or Control and Communication in the Animal and the Machine (Wiener), 38–39 cyborgs, 2 dancing mice, 87–92 Dancing Mouse, The (Yerkes), 85–86 DARPA (Department of Defense laboratory), 165 Dassault, 140 data, 113, 114, 117, 119–22, 136, 167, 248n data fundamentalism, 122–23 data processing, 17, 195 decision aids, automated, 113–15, 166 drawbacks to, 77 decision making, 160, 166, 168 decision trees, 113–14 declarative knowledge, 9, 10–11, 83 Deep Blue, 12 degeneration effect, 65–85 automation complacency and bias and, 67–72 Whitehead’s views and, 65–67 dementia, 135–37 dependency, 130, 133, 136, 146, 203, 225 depression, 220 Descartes, René, 148, 216 design, designers, 137–47 computer-aided (CAD), 138–42, 144, 145, 167, 219, 229–30 human- vs. technology-centered automation and, 158–62, 164–65, 167–70, 172 parametric, 140–41 system, 155–57 video games as model for, 178–82 Designerly Ways of Knowing (Cross), 143–44 desire, 15, 17, 20, 83, 161, 206–7, 210 to understand the world, 123–24 deskilling, 55, 100, 106–12, 115 Dewey, John, 148, 149, 220 diabetes, 245n–46n diagnostic testing, 70–71, 99, 102 DiFazio, William, 27–28 Digital Apollo (Mindell), 60, 61 disease, 70–71, 113, 135–37, 245n–46n dislocation, 133 Do, Ellen Yi-Luen, 167 Doctor Algorithm, 154, 155 doctors, 12, 32, 70, 93–106, 114–15, 120, 123, 147, 155, 166, 173, 219 evidence-based medicine (EBM) and, 114, 123 patient’s relationship with, 103–6 primary-care, 100–104, 154 document discovery, 116 Dodson, John Dillingham, 88–89 Dorsey, Jack, 203 Dorsey, Julie, 167–68 Dostrovsky, Jonathan, 133 dot-com bubble, 117, 194, 195 drawing and sketching, 142–47 Dreyfus, Hubert, 82 driving, see cars and driving drone strikes, 188 drugs, prescription, 220–21 Drum, Kevin, 225 Dyer-Witheford, Nick, 24 Dyson, Freeman, 175 Dyson, George, 20, 113 Eagle, Alan, 176 Ebbatson, Matthew, 55–56, 58 ebook, 29 economic growth, 22, 27, 30 economic stability, 20 Economist, 225 economists, 9, 18, 22, 29, 30, 32–33, 109 economy, economics, 20, 25–33, 117 e-discovery, 116 education, 113, 120, 153 efficiency, 8, 17, 26, 58, 61, 114, 132, 139, 159, 173, 174, 176, 219 EMR and, 101, 102 factories and, 106–8 electric grid, 195–96 electronic medical records (EMR), 93–106, 114, 123, 245n–46n embodied cognition, 149–51, 213 Emerson, Ralph Waldo, 16, 232 End of Work, The (Rifkin), 28 engagement, 14, 165 Engels, Friedrich, 225 Engineering a Safer World (Leveson), 155–56 engineers, 34, 36–37, 46, 49, 50, 54, 59, 69, 119, 120, 139, 157–60, 162, 164, 168, 174, 175, 194, 196 Enlightenment, 159–60 entorhinal cortex, 134, 135 equilibrium, of aircraft, 61–62 ergonomics (human-factors engineering), 54, 158–60, 164–68 Ericsson, K.


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Utopia Is Creepy: And Other Provocations by Nicholas Carr


Air France Flight 447, Airbnb, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, Donald Trump, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, low skilled workers, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator

This past spring, it rolled out the latest enhancement, which tailors suggestions to the searcher’s whereabouts. Google Suggest, and the similar services offered by other search engines, streamlines the discovery of information. When you click on a suggestion, you arrive at a page of search results, and the accompanying advertisements, a little faster than you would have had you typed out the query yourself. At a technical level, Google Suggest is remarkable. It testifies to the power of cloud computing—the serving up of software and information from big, distant data centers rather than from your computer’s own hard drive. When I typed that first “p,” the letter was beamed across the internet to a Google server in a building hundreds of miles away. The server read the letter, gathered ten popular search terms beginning with “p,” and shot the list back to my screen. The intricate data processing exercise took less than a second.

It has become the web’s central clearinghouse for information and one of the internet’s principal tollgates. As people spend more time and do more things online, they also perform more Google searches and click on more Google ads—and the business’s coffers swell. But the company’s recent history is not quite as buoyant as its bottom line suggests. While it has introduced several attractive products, such as the Android operating system for smartphones and the Google Apps suite of cloud-computing programs, it has failed to discover strong new sources of profit. Many of its most hyped services—Google Base, Google Wave, Google Buzz, Google Health—have fizzled. Designed by engineers, they proved too complicated for mere mortals. Its ambitious Google Books initiative has run into a wall of litigation, due in part to Page’s arrogance in rushing to scan copyrighted books without considering their owners’ interests.

., 191 Centers for Disease Control and Prevention, 304 centrifugal force, 67 centripetal force, 66 Chambers, John, 134 Chen, Steve, 29 Chief Officers of State Library Agencies, 272 Chin, Denny, 269, 272 China, censored searches in, 283 Christian, Rebecca, 80 citation, allusion vs., 87–88 Clash, 63–64 classical music, 43–44 Claude Glass, 131–32 Clinton, Bill, 315 Clinton, Hillary, 314, 315, 317–18 clocks, changes wrought by, 235–36 clones, virtual, 26–27 cloud computing programs, 264, 283 cloud storage, 163, 168, 185, 225 physical archives vs., 326 CNET, 55 Coachella festival, 126 Coca-Cola, marketing of, 53–54 cocaine, 262 cochlear implants, 332 cognitive bias, 321 cognitive control, 96 cognitive function: effect of internet on, 199–200, 231–42 effect of video games on, 93–97 “flow” state in, 297 memory and, 98–99 neuroengineering of, 332 reading and, 248–52 cognitive surplus, 59–60 avoidance of, 74 Coleridge, Samuel Taylor, 251 Collaborative Consumption, 84–85, 148 Columbia Records, 43–44 commercialism: anticonsumerism and, 83–85 culture transformed by, xvii–xxii, 3, 9, 150, 177, 198, 214–15 in innovation, 172 of libraries, 270–71 media as tool of, 106, 213, 240, 244–45, 257–58, 320 in virtuality, 25–27, 72 commodes, high-tech, 23–24 communication: between computers, 167 computer vs. human, 152–54 evolution of, 53 loneliness and, 159 mass, 67–68 speed of, 223, 320 thought-sharing in, 214–15 Communist Manifesto (Marx and Engles), 308 “Complete Control,” 63–64 Computer Power and Human Reason (Weizenbaum), 236 computers: author’s early involvement with, xix–xi benefits and limitations of, 322–23 in education, 134 effect on paper consumption of, 287–88 evolution of, xix–x, 165 future gothic scenarios for, 112–15 human hybridization with, 37–38, 332 human partnership with, 321–24 as impediment to knowledge perception, 303–4 minds uploaded to, 69 revivification through, 69–70 written word vs., 325–28 concentration, diffusion of, 231–33, 236–37 Confession d’un Enfant du Siècle, La (Musset), xxiii Congress, U.S., 275–77 consumer choice, 44–45 Consumer Electronics Show (CES), 32, 56 consumerism: counterculture co-opted by, 72 distraction and, 65 media as tool of, 106, 132, 219 consumption, self-realization vs., 64–65 contemplation, 241, 246 through work, 298–99 conversation, computer streaming of, 152–54 CopyBot controversy, 25–27 copyright laws: history of, 275–76 in online library controversies, 269–71, 275–78, 283 in virtual world, 25–27 Corporate Communalists, 83 corporate control, through self-tracking, 163–65 correspondence courses, 133–34 cosmetic surgery, 331, 334 Costeja González, Mario, 190–92, 194 Coupland, Douglas, 102, 103 Courant, Paul, 270, 272 courtesy: decline of, 157 inefficiency of, 152–54 Cowen, Tyler, 116 Crawford, Matthew, 265 creativity, 49, 64 before the virtual world, 60–61 economics of, 8–9 in music, 44–45, 294 stifled by iPad, 76–78 see also innovation “crisis of control,” 188–89 CRISPR, 334–35 crowdsourcing, 37 Cruz, Ted, 314 cultural memory, archiving of, 325–28 cutouts (remaindered record albums), 122 CyberLover, 55 cybernetics, 37–38, 214 cyberpunk, 113 cyberspace, xvii, 127 early idealism of, 85 “Cyborg Manifesto” (Haraway), 168–69 cyborgs, 131 cynicism, 158 Daedalus, 336, 340 Darnton, Robert, 270–75, 278 DARPA, 332 Dash Express, 56 data-mining, 186, 212, 255–59 data-protection agencies, 190–91 Data Protection Directive, 191, 193 Davidson, Cathy, 94 Davies, Alex, 195 Davies, William, 214–15 Dean, Jeff, 137 death, as hardware failure, 115 Declaration of Independence, 278, 325 “Declaration of the Independence of Cyberspace” (Barlow), 85 deep reading, 241 deletionists, 18–20, 58 democratization, xvi, xviii, 28, 86, 89, 115, 208, 271 internet perceived as tool for, 319–20 depression, 304 Derry, N.H., 296–97 Descartes, René, 301, 330 Dewey, John, 304 “digital dualism,” 129 “digital lifestyle,” 32–33 digital memory, 327 digital preservation, 325–28 Digital Public Library of America (DPLA), 268, 271–78 “Digital Republic of Letters,” 271 discovery, adventure of, 13–15 Disenchanted Night (Schivelbusch), 229 displaced agency, 265 distraction, xix, 14, 316 in consumerism, 65 video games and, 19 diversity, 65 DNA, 69–70, 334–35 Doctorow, Cory, 76–77 “Does the ‘New Economy’ Measure Up to the Great Inventions of the Past?”


pages: 349 words: 95,972

Messy: The Power of Disorder to Transform Our Lives by Tim Harford


affirmative action, Air France Flight 447, Airbnb, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Atul Gawande, autonomous vehicles, banking crisis, Barry Marshall: ulcers, Basel III, Berlin Wall, British Empire, Broken windows theory, call centre, Cass Sunstein, Chris Urmson, cloud computing, collateralized debt obligation, crowdsourcing, deindustrialization, Donald Trump, Erdős number, experimental subject, Ferguson, Missouri, Filter Bubble, Frank Gehry, game design, global supply chain, Googley, Guggenheim Bilbao, high net worth, Inbox Zero, income inequality, Internet of things, Jane Jacobs, Jeff Bezos, Loebner Prize, Louis Pasteur, Mark Zuckerberg, Menlo Park, Merlin Mann, microbiome, out of africa, Paul Erdős, Richard Thaler, Rosa Parks, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, Steven Levy, Stewart Brand, telemarketer, the built environment, The Death and Life of Great American Cities, Turing test, urban decay

Viewed in isolation, Amazon looked laughable and amateurish—as did Rommel’s thrust across Cyrenaica. But step back and consider the entire marketplace and it becomes clear that, however messily, Amazon had outflanked its rivals. By Christmas 2009, Amazon had a market share in e-books of around 90 percent.34 One can tell almost exactly the same story about Amazon’s initially baffling venture into cloud computing: a crazy rush, a series of early technical problems, a loss-making price. Then within a few years, Amazon, a mere bookseller, was the dominant player in cloud computing, and analysts were pronouncing that Amazon Web Services was a more valuable business than Amazon’s online retailing operation. The opportunity had been there to take, but the titans of the industry, IBM, Google, Apple, and Microsoft, had all hesitated at the prospect of a costly battle with the upstart.35 Again and again, we see Amazon moving quickly, losing money, struggling to cope with the demand it created, and in the end, dominating a market.

Instead, over the next few years, Amazon launched products as disparate as the Kindle (which immediately and repeatedly sold out, as Amazon struggled to manufacture it), Mechanical Turk (an unsettlingly named global clearinghouse for labor, which pioneered crowdsourcing but was criticized as being a sweatshop), the Fire Phone (widely reviewed as ugly, weird, and disappointing), Marketplace (where competitors to Amazon would use Amazon’s own product listings to advertise their own cheaper alternatives), and Amazon Web Services. AWS in particular was a bold stroke—a move into cloud computing in 2006, four years ahead of Microsoft’s Azure and six years ahead of Google Compute. As Bezos liked to say during the crunches of 1998 and 1999, “If you are planning more than twenty minutes ahead in this environment, you are wasting your time.”15 He was a man in a hurry. No wonder he created such an almighty mess. • • • Come the Second World War, the Italians were the Germans’ allies, but they seemed as prone as ever to losing battles.


pages: 234 words: 57,267

Python Network Programming Cookbook by M. Omar Faruque Sarker


business intelligence, cloud computing, Debian, DevOps, Firefox, inflight wifi, RFID, web application

A software engineer at heart, he is experienced in over 10 programming languages, but most recently, he is busy designing and writing applications in Python, Ruby, and Scala for several customers. He is also an open source evangelist and activist. He contributed and maintained several open source projects on the Web. Ahmed is a co-founder of Cloud Niners Ltd., a software and services company focusing on highly scalable cloud-based applications that have been delivering private and public cloud computing services to customers in the MEA region on different platforms and technologies. A quick acknowledgment to some of the people who changed my entire life for the better upon meeting or working with them; this gratitude does not come in a specific order but resembles a great appreciation for their support, help, and influence through my personal life and professional career. I would also like to thank Prof.

Vishrut Mehta has been involved in open source development since two years and contributed to various organizations, such as Sahana Software Foundation, GNOME, and E-cidadania; he has participated in Google Summer of Code last year. He is also the organization administrator for Google Code-In and has been actively involved in other open source programs. He is a dual degree student at IIIT Hyderabad, and now he is pursuing his research under Dr. Vasudeva Varma on topics related to Cloud Computing, Distributed Systems, Big Data, and Software Defined Networks. I would like to thank my advisors, Dr. Venkatesh Choppella and Dr. Vasudeva Varma, who showed me the direction in my work and helped me a lot. I would also like to thank my Google Summer of Code mentor, Patirica Tressel. Tom Stephens has worked in software development for nearly 10 years and is currently working in embedded development dealing with smartcards, cryptography, and RFID in the Denver metro area.


pages: 171 words: 54,334

Barefoot Into Cyberspace: Adventures in Search of Techno-Utopia by Becky Hogge, Damien Morris, Christopher Scally


A Declaration of the Independence of Cyberspace, back-to-the-land, Berlin Wall, Buckminster Fuller, Chelsea Manning, citizen journalism, cloud computing, corporate social responsibility, disintermediation, Douglas Engelbart, Fall of the Berlin Wall, game design, Hacker Ethic, informal economy, Jacob Appelbaum, jimmy wales, Julian Assange, Kevin Kelly, Menlo Park, Mother of all demos, Naomi Klein, Network effects, New Journalism, Norbert Wiener, Richard Stallman, Silicon Valley, Skype, Socratic dialogue, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, technoutopianism, Telecommunications Act of 1996, Vannevar Bush, Whole Earth Catalog, Whole Earth Review, WikiLeaks

* * * Back in May, when I was talking to Ethan at the Frontline Club about pseudo-public spaces, about the dangers of seeing virtual town squares where only virtual shopping malls exist, it all seemed so abstract. Well thanks to WikiLeaks, in early December, it got a whole lot less abstract. Most people know Amazon as the worlds biggest online retailer. But since about 2007 it has been hawking something altogether different to the tech-savvy hacker – machines. Amazons S3 cloud computing service is used by most hardcore data geeks I know as a quick and easy way to add more computing power to their programs, services and experiments. As it happened, in December WikiLeaks were also using Amazons S3 service, a fact that did not go unnoticed by the US authorities. On 30 November, Senator Joe Lieberman had a quiet word with Amazon. On 1 December, the website was taken offline. Amazons official line was that WikiLeaks had violated its Terms of Service by publishing information (the cables) to which it didnt own the rights.

bulletin board systems (bbs): A precursor to the modern form of the World Wide Web, a system that allowed users to dial in to a central computer over a phone line using a modem in order to read news bulletins and swap messages with other users cache: A software component that stores data so that future requests for that data can be served faster c-Base: Berlin hackspace and nightclub CCC: Chaos Computer Club or Chaos Communications Congress chipping : Installing a small electronic device used to modify or disable built-in restrictions and limitations of computers cloning: In the context of phones, transferring the identity of one mobile to another cloud computing: Computational resources accessible via a computer network rather than from a local computer copyleft: A play on the word ‘copyright’ used to describe the practice of using copyright law to offer the right to distribute copies and modified versions of a work CRC: Censorship Research Center cryptography: The practice and study of hiding information culture-jamming: A tactic used by many anti-consumerist social movements to disrupt or subvert mainstream cultural institutions, including corporate advertising cyberpunk: A postmodern and science fiction genre noted for its focus on high tech and low life DARPA: The Defense Advanced Research Projects Agency, an agency of the United States Department of Defense data-mining: The process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management DoS / DDoS: A denial-of-service attack (DoS attack) or distributed denial-of-service attack (DDoS attack) is an attempt to make a computer resource unavailable to its intended users, usually by flooding it with traffic or requests.


pages: 168 words: 50,647

The End of Jobs: Money, Meaning and Freedom Without the 9-To-5 by Taylor Pearson


Airbnb, barriers to entry, Black Swan, call centre, cloud computing, Elon Musk,, Frederick Winslow Taylor, future of work, Google Hangouts, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, loss aversion, low skilled workers, Lyft, Mark Zuckerberg, market fragmentation, means of production, Oculus Rift, passive income, passive investing, Peter Thiel, remote working, Ronald Reagan: Tear down this wall, sharing economy, side project, Silicon Valley, Skype, software as a service, software is eating the world, Startup school, Steve Jobs, Steve Wozniak, Stewart Brand, telemarketer, Thomas Malthus, Uber and Lyft, unpaid internship, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog

Those are three specific examples, but this is true for all the different tools required to start a business. The advantages are profound: Dramatic reduction in risk and cost—you’re often paying just 1% of the cost to get started compared to ten years ago. Dramatic increase in potential—because you can only buy as much as you need, you can buy best-in-class software. Venture capitalist Ben Horowitz, the CEO of the first cloud computing company, Loudcloud, said his customers were paying approximately $150,000 a month in 2000 to run a basic Internet application. Running that same application today in Amazon’s cloud costs about $1,500 a month. If the same decrease had happened to cars and homes, a $50,000 luxury car would cost $500 today and a half million dollar home would cost $5,000. Because technology develops faster than biological systems (like our brains), we’re not very good at understanding these kind of changes, but they happen all the time in the modern world.

Ramit found that that if he could get people to earn $1,000 on the side, then many of them would gain the confidence and resources to “stair step” their way further into entrepreneurship. Once they get $1,000 month, it felt possible to double it to $2,000 per month, and once their side income replaces their corporate income, most of them choose to leave their jobs. Because of services like cloud computing, SaaS and contractors make it much easier to keep expenses down. Millions of niches like invoicing software are now viable step one businesses, where you can build up a skillset and cash flow with very little competition to launch into bigger opportunities. It also means that you have to stair step up. The market targeted by the invoicing software simply wasn’t big enough to support a ten thousand dollar a month business.


pages: 236 words: 50,763

The Golden Ticket: P, NP, and the Search for the Impossible by Lance Fortnow


Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Claude Shannon: information theory, cloud computing, complexity theory, Erdős number, four colour theorem, Gerolamo Cardano, Isaac Newton, John von Neumann, linear programming, new economy, NP-complete, Occam's razor, P = NP, Paul Erdős, Richard Feynman, Richard Feynman, smart grid, Stephen Hawking, traveling salesman, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, William of Occam

In the 1980s and 1990s cryptographers developed very general techniques whereby any game played with a trusted adversary can be played without a trusted adversary over the Internet. These methods use both encryptions and zero-knowledge proofs. These protocols are quite complicated and rarely used in practice. In the real world, people rely either on trusted websites or on protocols tailored for a specific purpose. Secretly Computing in the Cloud Suppose Alice needs computation done on sensitive data and Bob runs a cloud computing service. Alice can send her data to Bob using Bob’s public key. Bob decrypts the data, does the computation, and sends the results back to Alice using Alice’s public key. Assuming that Alice and Bob use a secure public-key protocol, no eavesdropper will see Alice’s data. That’s fine as long as Alice trusts Bob. What if Alice wants to keep her data secret even from Bob? To solve this problem, we need something called fully homomorphic cryptography.

., 83–84 baseball, 16–19 A Beautiful Mind (Nasar), 49 Bell Labs, 146 Bennett, Charlie, 148, 150 Bennett-Brassard protocol, 148–49 Berge, Claude, 35 big data, 155, 158–59 biology, NP problems in, 47–48 bit, 114, 144 Blum, Manuel, 76, 78 Borov, Minsk, 12 brain, in hand control, 5–6 Brassard, Gilles, 148, 150 A Brief History of Time (Hawking), x Brown, George, 26 brute force, for NP-complete problems, 90–92, 91 byte, size of, 2 Caesar cipher, 123, 123–24 Cambridge University, 73 cancer, curing, 14–15 Cardano, Gerolamo, 119–20 card game protocols, 137 cell phones, 161 CERN (European Organization for Nuclear Research), 158 Chaitlin, Gregory, 83 Chaplin, Charlie, and Kevin Bacon, 31–32 Charlie and the Chocolate Factory (Dahl), 1–2, 157 check deposit, online, 21–22, 22 Chomsky, Noam, 75 Church, Alonzo, 49 Churchill, Winston, 126 circuit complexity, 79–80 circuits, 113, 113–18, 114, 115, 116 classical music, automated creation of, 24–25 Clay Mathematics Institute, 7, 14 cliques: algorithm for, 12–14, 120; approximating, 101–4, 102, 103; circuit computation of, 115, 115–18, 116; example of, 8–9, 52, 52–54; Facebook as, 8–9; finding, 36–37, 45; logical expressions for, 52–54; parallel computation of, 157; quantum approach to, 146; satisfiability and, 54, 55; small solutions for, 97, 97–99, 98 cloud computing, 138–39 Cobham, Alan, 76, 77 Coca-Cola bottling plants, 56 Cocks, Clifford, 128 CODIS (U.S. Combined DNA Index System), 25–26 coin-toss protocol, 136–37 Cold War, competitiveness in science during, 71–72 Colossus, 125–26 Columbus principle, 86 Communications of the ACM, x complete, 58 “The Complexity of Theorem-Proving Procedures” (Cook), 52 computation: as natural, 86–87; with Turing machine, 73–74; wire in, 114, 114 computational complexity, 76, 78, 80 computation theory: Eastern development of, 78–85; Western development of, 72–78 computer(s): capabilities of, ix; in cryptography, 126; defining, 72–73 computer networks: computation power of, 160; as future challenge, 155–56, 159–60; security of, 127 computer security, changing the problem in, 106 context-free grammar, 75, 75–76 Cook, Steve, 6, 51–52, 77, 166 Cook-Levin theorem, 85 CPUs, capabilities of, 90–92 creativity, automating, 23–25 criminal profiling, 25–26 cryptography: Cardano and, 120; challenges in, 140–41; fully homomorphic, 138–39; history of, 123–26; modern, 126–29; NP-complete problems in, 140–41, 162; if P = NP, 129–30; quantum, 130, 148–49; randomness in, 140; zero-knowledge proofs and, 135–36 cutting-plane method, 91, 91 Dahl, Roald, 1–2, 157 Dantzig, Georg, 69 data: amounts of, as challenge, 155, 158–59; copying, 148 Deepwater Horizon, 161 Deolalikar, Vinay, 118–19 Descartes, René, 20 dice-rolling protocol, 137 Diffie, Whitfield, 126, 127 Dilbert, 82, 109 Discourse of the Method (Descartes), 20 DNA: in cancer treatment, 14–15; sequencing, 47–48, 158 dodecahedron, 41, 41 dominating set problem, 59 Doyle, Arthur Conan, 124 DVRs, quantum, 143–47 D-Wave, 147 economics, NP problems in, 49 Edmonds, Jack, 35–36, 76–77 efficiency: of algorithms, 36; defining, 76–78 efficient computation.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan


23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, 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,, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, Internet Archive, Internet of things, Khan Academy, Kickstarter, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer lending, personalized medicine, post scarcity, prediction markets, 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, unbanked and underbanked, underbanked, web application, WikiLeaks

Another significant technical challenge and requirement is that a full ecosystem of plug-and-play solutions be developed to provide the entire value chain of service delivery. For example, linked to the blockchain there needs to be secure decentralized storage (MaidSafe, Storj), messaging, transport, communications protocols, namespace and address management, network administration, and archival. Ideally, the blockchain industry would develop similarly to the cloud-computing model, for which standard infrastructure components—like cloud servers and transport systems—were defined and implemented very quickly at the beginning to allow the industry to focus on the higher level of developing value-added services instead of the core infrastructure. This is particularly important in the blockchain economy due to the sensitive and complicated cryptographic engineering aspects of decentralized networks.

Looking ahead, reconfiguring all of business and commerce with smart contracts in the Bitcoin 2.0 era could likely be complicated and difficult to implement, with many opportunities for service providers to offer implementation services, customer education, standard setting, and other value-added facilitations. Some of the many types of business models that have developed with enterprise software and cloud computing might be applicable, too, for the Bitcoin economy—for example, the Red Hat model (fee-based services to implement open source software), and SaaS, providing Software as a Service, including with customization. One possible job of the future could be smart contract auditor, to confirm that AI smart contracts running on the blockchain are indeed doing as instructed, and determining and measuring how the smart contracts have self-rewritten to maximize the issuing agent’s utility.


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, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, 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

Moreover, digitalization means that jobs can be broken down into smaller parts, which people can then bid to work on from across the globe, although this often means that price, alongside quality, is driven down to the point where skills become mere commodities. One issue to watch seriously is what this all means for intellectual property. As more and more becomes digitalized and virtualized, there is greater opportunity for abuse, although I would expect the area of copyright eventually to catch up with this. Another example of dematerialization is cloud computing—rather than physically owning or storing something at a set physical location you can simply pay to gain access to it “from the air” on any device you like whenever you need it. This might be business information or it could be films, games, photographs and many other items that used to be physically owned and kept by individuals or institutions. Hence, a more general shift away from individual ownership to shared access, which, coincidently, links with a shift from products in general to the more ethereal world of experiences.

May one day be linked to unique personal identification numbers (PINs) or passwords. Carbon capture and sequestration Technologies and techniques that attempt to prevent the release or leakage of CO2 into the atmosphere from the use of fossil fuels. Claytronics The merging of computing and nanoscale robotics (and possibly artificial intelligence) to create shape-shifting materials or 3D programmable matter. Cloud computing The remote hosting, or storage, of data, which is usually accessed on an on-demand basis. In other words, letting someone else, somewhere else, store your data, which can then be accessed any time, anywhere on any device, via the Internet. Cloud whitening Techniques and technologies intended to modify clouds to reduce the impact of global warming. Sometimes referred to as cloud reflectivity enhancement or modification.


pages: 170 words: 51,205

Information Doesn't Want to Be Free: Laws for the Internet Age by Cory Doctorow, Amanda Palmer, Neil Gaiman


Airbnb, barriers to entry, Brewster Kahle, cloud computing, Dean Kamen, Edward Snowden, game design, Internet Archive, John von Neumann, Kickstarter, optical character recognition, Plutocrats, plutocrats, pre–internet, profit maximization, recommendation engine, rent-seeking, Saturday Night Live, Skype, Steve Jobs, Steve Wozniak, Stewart Brand, transfer pricing, Whole Earth Catalog, winner-take-all economy

There are game servers that allow multiple players to play together. There are voice-over-IP companies that allow for in-game chat or video conferencing. There are ad brokerages that supply advertising to ad-supported sites and programs. There are domain registrars, which sell Internet domains like There are payment processors like PayPal, MasterCard, and AmEx, which help get money from customers to suppliers. And in the age of “cloud computing,” there are companies that host massive arrays of raw computing power, supplying bandwidth, storage, and processing. All of these intermediaries can play a critical role in any commercial creative venture. In fact, it’s nearly impossible to imagine doing anything of consequence without recourse to one or more of them. Even a “solitary” project like writing a novel will involve an operating-system vendor, a word-processing vendor, an email-hosting company (to communicate with your editor and agent), an ISP (so you can access the email), an email-software vendor, and probably a few online file lockers for previewing cover art, exchanging unwieldy electronic galleys, and the like.

Though SOPA, PIPA, ACTA, the TPP, the WCT, and their ilk differ in their specifics, they share certain broad themes that represent the legislative agenda for the entertainment lobby. And if you wanted to sum up that agenda in a single sentence, it would be this: More intermediary liability, with fewer checks and balances. 2.12 More Intermediary Liability, Fewer Checks and Balances THE INTERNET HAS a lot of intermediaries. At present, treaties like the WCT focus on controlling one class of middlemen: web hosts, be they cloud-computing providers, file lockers, video hosts, or social-media services. Their liability is limited as long as they’re willing to respond to a takedown notice. Beyond that, intermediaries aren’t required to police their customers’ uploads. What the entertainment lobby wants is to expand which intermediaries are liable for their role in an infringement, and what responsibilities intermediaries have when it comes to proactively policing their services.


pages: 66 words: 9,247

MongoDB and Python by Niall O’Higgins


cloud computing, Debian, fault tolerance, semantic web, web application

GridFS allows you to store binary data in MongoDB. Capped Collections are a special type of collection, which look like a circular buffer and are great for log data. With these features at your disposal, Python and MongoDB are extremely powerful tools to have in your toolbox when developing an application. Going Further | 53 About the Author Niall O’Higgins is a software consultant specializing in mobile, tablet, and cloud computing. His accomplishments include designing and implementing the platform backend using MongoDB, Python, and Pylons. Catch is one of the most popular apps on Android. Prior to Catch, he was a software engineer at Metaweb Technologies, where he worked on (now owned by Google). He is the founder and organizer of both the San Francisco Python Web Technology Meet-up, PyWebSF, and the Bay Area Tablet Computing Group, We Have Tablets.


pages: 266 words: 67,272

Fun Inc. by Tom Chatfield


Alexey Pajitnov wrote Tetris, Any sufficiently advanced technology is indistinguishable from magic, cloud computing, cognitive dissonance, computer age, credit crunch, game design, invention of writing, Silicon Valley, Skype, stem cell, upwardly mobile

It won’t be long before the first games are released for e-book readers like Amazon’s Kindle: the idea of any media platform in possession of a marketplace lacking games seems unlikely to last for long. In fact, perhaps the most significant challenge to the console model of gaming is not so much competition from PCs as the more radical possibility of removing most of the hardware from the homes of individual consumers entirely. Much like ‘cloud computing’, where the remote use of powerful central computers via the internet is already revolutionising many people’s relationship with traditional suites of applications on their computers, this kind of system could offer gamers a simple two-way streaming service in the place of a traditional, expensive console: an inexpensive box able to stream sounds and images in one direction, and relay their instructions in the other, with a central piece of hardware doing all the intensive work, just like the machinery that powers an internet search engine or any other remote service.

Index 3D modelling 115, 116 9/11 attacks (2001) 80 2001: a Space Odyssey (film) 113 Acel Group 216 achievement 4 Acorn Computers ix addiction 71–8, 223 ‘adventure’ games x advertising 30, 32, 33, 114, 210, 217, 219 Alderman, Naomi 80 alienation 78 Amazon 90, 219 America 69, 222 America’s Army 190–91, 194 Amstrad 95 Anatomy of Care 196–7 Apple 213 App Store 213, 214 Arcade (film) 87 arcade games 19, 21 Aristotle 125 Assyrians 1 Atari 18, 19, 21, 22 400 home computer 10 ST ix Australia 69 Austria 229 Avatar (film) 44 avatars 43–4, 90, 141, 143, 168–9, 225 Aykroyd, Dan 137 Baer, Ralph 19 Bakker, Keith 77–8 Balicer, Ran D 174–5 Ballard, J G 45 Bartle, Richard 45–9, 51, 101 ‘Bartle quotient’ 48 ‘Bartle Test of Gamer Psychology’ 48 BBC Micro Model B ix Beatles, the 135, 136 Beatles: Rock Band, The 135 Bebo 89, 212 Berry, Dani Bunten 10 Bhagavad Gita 44 Bhagavata Purana 44 Bioshock 119 BitTorrent 216 Blair, Charles 176 Blitz Games Studios 114–15 TruSim division 198 Blu-ray 27, 137, 218 board games 9, 13, 62, 91 Boom Blox 138 brain-training games 202, 205, 206 Brouwer, Adam 95–102 BSkyB 218 bullying cyber-bullies 63 school 77 Bushnell, Nolan 18 Byron, Dr Tanya: Safer Children in a Digital World report 84 calculators 28 Cameron, James 44–5 Campbell, Joseph 46 Canada 69 Cartoon Network 49 Castronova, Edward 166–74, 177, 226 ‘Virtual Worlds: A First-Hand Account of Market and Society on the Cyberian Frontier’ 167 casual gaming 33–7, 210–12 CDs 218 censorship 70, 224 Chen, Jenova 120–25 Cheshire, Bob 115 chess 5 child abusers 63 children and censorship of violent media 70 as video game players 58, 62, 63–5, 75, 79 China 221, 222, 229 Chronotron 129 cinema 20, 57, 111–12, 227, 228 Kubrick’s inventions 113–14 civilisation 229, 230 Clarke, Arthur C 13, 14–15 clay modelling 115 Climax 119 Cloud 121 ‘cloud computing’ 219–20 Codemaster 119 collaboration x, 3, 4, 177 collecting 164 communication(s) 4, 55, 78, 97, 108, 109, 189, 209 competition 3, 4, 11, 139, 163, 199, 206, 207, 228 increased foreign 222 computers ability to run games/programs 23–4 browser-based fun 219 computing activity conventions 155–6 constantly evolving 31 double clicking 156 drop-down menus 155 freedom to browse the internet 24 gaming profits 24 interaction with 155–60 programming 15 slow, steady rise of 23 software 156 static as work environments 154–5 comScore 216, 217 concept art 115, 116, 123 Consolarium 201, 203 conversation 85, 103 cooperation 11, 60, 108, 139, 163, 179 copyright protection 28 ‘corrupted blood plague’ 174, 176 Council of Stellar Management (in EVE Online) 106–7 Crouse, Jeff 143 Csikszentmihalyi, Mihaly 42 customisation 164, 165 cyber-bullies 63 Czechoslovakia 229 Dabney, Ted 18 Dante’s Inferno 87 Darfur is Dying 182–7 data mining 138 databases 155 depression 78 Diablo II 80 Diagnostic and Statistical Manual of Mental Disorders (DSM) 71, 73, 74 Dibbell, Julian: Play Money 148–9 digital age 28, 209, 226, 227 digital distribution 32 digital literacy 155 ‘digital natives’ 210 digital revolution 38 Discworld 118 Disney, Walt: 12 basic principles of animation 115 Doom 188–9 dopamine 72 downloads 222 Dr Kawashima’s Brain Training 202, 206 Dragon Kill Points (DKP) 177–9 ‘drone’ aircraft (Reapers) 193–4 dry neural sensor technology 158 Duhamel, Georges: Scenes from the Life of the Future 55–7 DVD drive 157 DVDs 27, 218 e-book readers 219 East Lothian council 204 eBay 60 economics 166, 170, 174 education 199–208, 223 see also learning; training educational aids 153 Electronic Arts 31, 49 email clients 155 email surveys 35 embodiment 44, 46, 141–2 emergency medicine games 197–9 emergent behaviours 10, 11, 130 ‘end game’ 94 energy costs 161–3 engagement 181, 186 Entertainment and Leisure Software Publishers Association 64 Entertainment Software Association of America 61 Entertainment Software Rating Board 62–3 environmental storytelling 119 Epidemiology journal 174 ergodic texts 200 Europe 222, 223 European Parliament 109 European Union (EU) 69 EVE Online 106–7, 129–31 EverQuest 103, 104–5, 167–8, 177, 178 exchanges, gaming 164–5 Facebook 33–4, 37, 89, 155, 162, 212, 216 fair play 229 fantasy scenarios 140 Far Cry 2, 68 feedback 35–7, 42, 72, 117, 164 real-time sensory 211 Fefferman, Nina H 175 Ferguson, Dr Christopher John: ‘The Good, the Bad and the Ugly: A Meta-analytic Review of Positive and Negative Effects of Violent Video Games’ 66 financial crisis (2008-date) 151, 166 flow 42–3, 51, 122, 163–4, 171 flOw 121, 122 Flower 121, 123–4, 126, 129 football 2, 5, 6 ‘Four Keys to releasing emotions during play’ 49–51 altered states 50–51 easy fun 50 hard fun 50 the people factor 51 full-body projections 14 fun browser-based 219 Castronova on 170 defined 8–9 easy 50 and engagement 181, 186 hard 50 modern games as 23 Seggerman on 181 serious 10 gambling 73, 74, 75, 77 Game Developers Conferences 121, 220 gamerDNA 48 games history of xii, 1 rule-making 2, 3 the universal urge to play 1 Games for Change 181, 187 ‘games for change’ 186, 193 games charts 114 games consoles 210 advancement in sudden leaps 31 ‘console wars’ 21 console-based television service 218–19 copyright protection 28 graphical and processing capacities 21 interface 157 and Japanese firms 21 Lovell on 215–16 the most valuable sector for gaming 33 Nintendo DS 202, 205–8 Nintendo Wii 23, 37, 91, 138, 156, 158, 160, 215, 217–18 Sony PlayStation 22 Sony PlayStation III 215, 218 Super Nintendo 200 ‘walled gardens’ 24 Xbox 360 14, 215 Games for Health conference (Baltimore, 2008) 175 games-based learning 199–208 gaming industry digital distribution 32 growth of 27–8, 30, 38, 113, 210–11 invention of new methods and technology 114 mid-priced movement 32, 33 profitability 31–2 publishers vs. developers 30–31 regional variation 221–3 risk 31, 32 social and casual gaming 33–7 gaming mechanisms 164–5 Gator Six 195–6 Gentile, Dr Douglas A: ‘Pathological Video Game Use among Youth 8 to 18: A National Study’ 73–5, 76, 79 Germany 67, 229 Ghostbusters 137 Ghostbusters films 137 Glow broadband network for schools 205 Goh, Oliver 161 gold farming 145, 146, 147, 149 Google 27, 162, 164, 211 governments 225 GPS-enabled gamers 211 Grand Theft Auto series 82–3 Grand Theft Auto IV (GTA IV) 29, 30, 81–2 ‘grandma gaming’ 210 grandparents 62 graphics card 157 Great Purge 229 Greenfield, Susan 76 iD: The Quest for identity in the 21st Century 72–3 griefing 176 group play 51 guilds 95–8, 100, 101, 104, 105, 175 Guinness World Records 191 Guitar Hero 91, 136, 156, 157, 203, 204 Hallybone, Dawn 206, 208 haptic devices 159 ‘hard-core’ gaming 129 Harris polls 74 Harry Potter & The Deathly Hallows (Rowling) 29 Harvard Business Review 98–9 headsets 97, 158 hedonics 174 high-school shootings 67–9 Hitchhiker’s Guide to the Galaxy, The xii home game machine, world’s first 19 hostage recovery scenarios 189 How Big is Your Brain?


pages: 242 words: 71,938

The Google Resume: How to Prepare for a Career and Land a Job at Apple, Microsoft, Google, or Any Top Tech Company by Gayle Laakmann Mcdowell


barriers to entry, cloud computing, game design, information retrieval, job-hopping, side project, Silicon Valley, Steve Jobs, why are manhole covers round?

It is consequently extremely frugal, and refrains from providing the lavish perks that others software companies might. Additionally, some employees have suggested that the company does not value technical innovation for its own sake, and instead looks for an immediate and causal link to profits. But, do not let that deter you too much; indeed, Amazon is leading in multiple industries (retail, cloud computing, etc.) largely because of its technical innovation. The company moves at a rapid pace and pending deadlines often mean late nights. Apple is just as secretive inside as it is outside. When your innovation lies so heavily in your look and feel and your market share depends on beautifully orchestrated hype, it’s no wonder. The company can’t afford to let its secrets slip. Employees are die-hard fans, just as one would expect, but rarely know what coworkers from other teams are working on.

Without a tangible skill, you’ll likely blend in with everyone else—everyone else who’s waiting at the door to be let in. Learn about technology. If you think you want to work at a tech company but don’t know much about technology, now is a great time to start reading web sites like TechCrunch and CNET, as well as company-specific blogs. Think about what the major topics are—social networking, mobile applications, cloud computing—and ask yourself, who are the leaders in this field, and why? In what ways are these fields changing technology, and therefore the world? Academics You know Google—that company famous for wanting Ivy Leaguers with at least a 3.7 GPA? When I joined Google, my team of eight people consisted of three people without a college degree. And our next college hire, well, his GPA wasn’t too hot, from what I hear.


pages: 270 words: 79,068

The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers by Ben Horowitz


Airbnb, business intelligence, cloud computing, financial independence, Google Glasses, hiring and firing, Isaac Newton, Jeff Bezos, Mark Zuckerberg, move fast and break things, new economy, nuclear winter, Peter Thiel, Productivity paradox, random walk, Ronald Reagan, Silicon Valley, six sigma, Steve Ballmer, Steve Jobs

Along with our revenue, our stock price rose from its floor of $0.35 per share as well as we traded between $6 per share and $8 per share, sometimes trading at a market capitalization of more than $800 million. Still, everything was not rosy. Every quarter was tough, and the competitive and the technology landscapes changed rapidly. A technology called virtualization was taking the market by storm and changing the way customers thought about automating their environments. In fact, it looked to me like virtualization might be the technological breakthrough that finally enabled the cloud computing business model to work. Beyond that, being a public company was still never going to get easy. At one point, a shareholder activist named Rachel Hyman decided that my ego was out of control, and she demanded that the board remove me and sell the company immediately. This was despite the fact that we were trading at $7 per share, which was ten times the original price of her shares. Nonetheless, I was not looking for the exits.

Bell curves and random walks define what the future is going to look like. The standard pedagogical argument is that high schools should get rid of calculus and replace it with statistics, which is really important and actually useful. There has been a powerful shift toward the idea that statistical ways of thinking are going to drive the future.” —PETER THIEL When I was attempting to sell the cloud computing services part of the Loudcloud business, I met with Bill Campbell to update him on where I was with the deal. The deal was critical, because without it, the company would almost certainly go bankrupt. After I carefully briefed him on where we were with both interested parties, IBM and EDS, Bill paused for a moment. He looked me in the eyes and said, “Ben, you need to do something in addition to working on this deal.


pages: 288 words: 66,996

Travel While You Work: The Ultimate Guide to Running a Business From Anywhere by Mish Slade


Airbnb, Atul Gawande, business process, Checklist Manifesto, cloud computing, crowdsourcing, Firefox, Google Chrome, Google Hangouts, Inbox Zero, job automation, Lyft, remote working, side project, Skype, speech recognition

If you have a traditional card with a magnetic strip, it shouldn't be much of a problem in stores and restaurants (where someone will be able to swipe it for you), but it could be a tad trickier at ticket vending kiosks, gas stations or other places featuring automated payment machines. If possible, see if your bank will provide you with a chip-and-pin card. The future of credit/debit cards? A new way of banking is on the horizon – one that makes the most of advances in cloud computing, smartphones and social networking. Check out Number26 ( and Supercard ( for more information. I won't write about them too much here because they're both still very new at the time of writing – and only available in Europe and the UK respectively. But they're worth keeping a close eye on because they could make transaction fees and ATM fees a thing of the past.

I decided that I wanted to go back to what I'd been doing in previous roles but that I really needed to get a better kind of balance between work and creative projects. I wanted to travel more and do work that I believed in rather than doing things that were "good for my career" (which often seemed to be the stuff other people didn't seem to want to do either). If you're single and going to spend 12 hours a day working, you need to enjoy what you do. I also spent a lot of time looking at how cloud computing and apps like Dropbox were breaking the stranglehold of IT departments ("Server Huggers" as one of my friends calls them). Being able to work remotely just seemed to be an evolving solution to what I wanted to do. How do you stay productive? Staying productive is a challenge. I'm very good with client deadlines. I try to set myself artificial deadlines for admin tasks and non-client projects just to stop me drifting.


pages: 233 words: 66,446

Bitcoin: The Future of Money? by Dominic Frisby


3D printing, altcoin, bank run, banking crisis, banks create money, barriers to entry, bitcoin, blockchain, capital controls, Chelsea Manning, cloud computing, computer age, cryptocurrency, disintermediation, ethereum blockchain, fiat currency, friendly fire, game design, Isaac Newton, Julian Assange, litecoin, M-Pesa, mobile money, money: store of value / unit of account / medium of exchange, Occupy movement, Peter Thiel, Ponzi scheme, prediction markets, price stability, quantitative easing, railway mania, Ronald Reagan, Satoshi Nakamoto, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, Stephen Hawking, Steve Jobs, Ted Nelson, too big to fail, transaction costs, Turing complete, War on Poverty, web application, WikiLeaks

Someone hacked into the administrator account of the bitcoin exchange MtGox and issued sell orders for hundreds of thousands of fake bitcoins, driving the price down from $17.50 to $0.01, albeit temporarily. Fraud concerning PayPal purchases of bitcoins meant that service was discontinued (although the connection with WikiLeaks may have been the real reason). The world’s third largest exchange, Bitomat in Poland, lost its wallet and, with it, 17,000 bitcoins they were holding for clients. The wallet had been stored with Amazon’s cloud computing servers and just ‘disappeared’. New developments continued to spring up – a smartphone wallet, then an iPad app. A payment was made by near field communication – a form of radio communication between smart phones. The first decentralized mining pool, P2Pool, mined a block. August saw the first Bitcoin conference in the US, and the following November Europe had its first conference in Prague.

But what about the 2010s? What is the great bull market of this decade? US stocks, maybe? Biotech, perhaps, or London property? Well, no. So far it’s been Bitcoin. And I think the next phase will be one of its offshoots. We’ll call it block chain tech. Block chain tech is going to change everything – not just money and banking, but the law, accounting, social media, email, gambling, web hosting, cloud computing, stock markets even. It could be more earth-shattering than the World Wide Web. As we’ve seen with Ethereum, now that Bitcoin is up and running, developers are extending the technology of the block chain into all sorts of other applications. You have Bitmessage – a decentralized system of sending and receiving emails without Google or Hotmail or whoever your email service provider might be having access to your messages.


Data Mining: Concepts and Techniques: Concepts and Techniques by Jiawei Han, Micheline Kamber, Jian Pei


bioinformatics, business intelligence, business process, Claude Shannon: information theory, cloud computing, computer vision, correlation coefficient, cyber-physical system, database schema, discrete time, distributed generation, finite state, information retrieval, iterative process, knowledge worker, linked data, natural language processing, Netflix Prize, Occam's razor, pattern recognition, performance metric, phenotype, random walk, recommendation engine, RFID, semantic web, sentiment analysis, speech recognition, statistical model, stochastic process, supply-chain management, text mining, thinkpad, web application

One important direction toward improving the overall efficiency of the mining process while increasing user interaction is constraint-based mining. This provides users with added control by allowing the specification and use of constraints to guide data mining systems in their search for interesting patterns and knowledge. ■ Integration of data mining with search engines, database systems, data warehouse systems, and cloud computing systems: Search engines, database systems, data warehouse systems, and cloud computing systems are mainstream information processing and computing systems. It is important to ensure that data mining serves as an essential data analysis component that can be smoothly integrated into such an information processing environment. A data mining subsystem/service should be tightly coupled with such systems as a seamless, unified framework or as an invisible function.

■ Parallel, distributed, and incremental mining algorithms: The humongous size of many data sets, the wide distribution of data, and the computational complexity of some data mining methods are factors that motivate the development ofparallel and distributed data-intensive mining algorithms. Such algorithms first partition the data into “pieces.” Each piece is processed, in parallel, by searching for patterns. The parallel processes may interact with one another. The patterns from each partition are eventually merged. Cloud computing and cluster computing, which use computers in a distributed and collaborative way to tackle very large-scale computational tasks, are also active research themes in parallel data mining. In addition, the high cost of some data mining processes and the incremental nature of input promote incremental data mining, which incorporates new data updates without having to mine the entire data “from scratch.”

A systematic development of such techniques will facilitate the promotion of human participation for effective and efficient data analysis. ■ Distributed data mining and real-time data stream mining: Traditional data mining methods, designed to work at a centralized location, do not work well in many of the distributed computing environments present today (e.g., the Internet, intranets, local area networks, high-speed wireless networks, sensor networks, and cloud computing). Advances in distributed data mining methods are expected. Moreover, many applications involving stream data (e.g., e-commerce, Web mining, stock analysis, intrusion detection, mobile data mining, and data mining for counterterrorism) require dynamic data mining models to be built in real time. Additional research is needed in this direction. ■ Privacy protection and information security in data mining: An abundance of personal or confidential information available in electronic forms, coupled with increasingly powerful data mining tools, poses a threat to data privacy and security.


pages: 541 words: 109,698

Mining the Social Web: Finding Needles in the Social Haystack by Matthew A. Russell


Climategate, cloud computing, crowdsourcing,, fault tolerance, Firefox, full text search, Georg Cantor, Google Earth, information retrieval, Mark Zuckerberg, natural language processing, NP-complete, profit motive, Saturday Night Live, semantic web, Silicon Valley, slashdot, social graph, social web, statistical model, Steve Jobs, supply-chain management, text mining, traveling salesman, Turing test, web application

It's only recentl ecently that members of the hardcore open source and free software advocacy co ntally changing the context in which open source exists, and that it hasn't do er in favor of understanding how the open source community actually communicat y remind people to attend OSCON, the open Source Convention, where the long te he long term thinking that drives my open source position is leading us to cov n is leading us to cover topics like open source and cloud computing, open sou ike open source and cloud computing, open source hardware, and many other topi ks than you can count), I do have an open source bully pulpit. It just isn't t Reilly to Keynote at Computerworld's open Source Business Conference http://bi hasn't built a personal brand in the open source space such that his company i trum auction and their launch of the open Handset Alliance are among the compa ng their phone even further from the open web.

This example shows some output from Tim’s Buzz feed that should make it pretty apparent that returning scored bigrams is immensely more powerful than only returning tokens because of the additional context that grounds the terms in meaning. Example 7-10. Sample results from Example 7-9 annalee saxenian nexus one. cafe standards certainly true eric schmidt olive oil open source 1/4 cup free software andy rubin front page mr. o’reilly o’reilly said. steve jobs tech support long term web 2.0 "mr. o’reilly personal brand came back cloud computing, meaningful use Keeping in mind that no special heuristics or tactics that could have inspected the text for proper names based on Title Case were employed, it’s actually quite amazing that so many proper names and common phrases were sifted out of the data. There’s still a certain amount of inevitable noise in the results because we have not yet made any effort to clean punctuation from the tokens, but for the small amount of work we’ve put in, the results are really quite good.


pages: 380 words: 118,675

The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone


3D printing, airport security, AltaVista, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, call centre, centre right, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, Douglas Hofstadter, Elon Musk, facts on the ground, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, Kevin Kelly, Kodak vs Instagram, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Network effects, new economy, optical character recognition,, Ponzi scheme, quantitative hedge fund, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas L Friedman, Tony Hsieh, Whole Earth Catalog, why are manhole covers round?

Narrowly avoiding disaster and defying a wave of skepticism about its prospects that coincided with the dot-com bust of 2000 and 2001, it then mastered the physics of its own complex distribution network and expanded into software, jewelry, clothes, apparel, sporting goods, automotive parts—you name it. And just when it had established itself as the Internet’s top retailer and a leading platform on which other sellers could hawk their wares, Amazon redefined itself yet again as a versatile technology firm that sold the cloud computing infrastructure known as Amazon Web Services as well as inexpensive, practical digital devices like the Kindle electronic reader and the Kindle Fire tablet. “To me Amazon is a story of a brilliant founder who personally drove the vision,” says Eric Schmidt, the chairman of Google and an avowed Amazon competitor who is personally a member of Amazon Prime, its two-day shipping service. “There are almost no better examples.

During this time, Bezos relentlessly advocated for taking risks outside of Amazon’s core business. Between 2003 and 2005, Amazon started its own search engine and devised a way to allow customers to search for phrases inside books on the site. Bezos also helped to pioneer the modern crowd-sourcing movement with a service called Mechanical Turk and laid the groundwork for Amazon Web Services—a seminal initiative that ushered in the age of cloud computing. Bezos battled a reaction that he dubbed the institutional no, by which he meant any and all signs of internal resistance to these unorthodox moves. Even strong companies, he said, tended to reflexively push back against moves in unusual directions. At quarterly board meetings, he asked each director to share an example of the institutional no from his or her own past. Bezos was preparing his overseers to approve what would be a series of improbable, expensive, and risky bets.

Amazon was now free to resume discounting new and bestselling e-books. I asked Bezos about it but he didn’t care to gloat. “We are excited to be allowed to lower prices” was all he said. In December, Amazon held its first conference for customers of Amazon Web Services at the Sands Expo Center in Las Vegas. Six thousand developers showed up and listened intently as AWS executives Andy Jassy and Werner Vogels discussed the future of cloud computing. The size and passion of the crowd was an emphatic validation of Amazon’s unlikely emergence as a pioneer in the field of enterprise computing. On the second day of the conference, Bezos himself took the stage and in a freewheeling discussion with Vogels gave a rare window into his personal projects, like the Clock of the Long Now, that mechanical timepiece designed to last for millennia that engineers are preparing to build inside a remote mountain on Bezos’s ranch in Texas.


pages: 514 words: 152,903

The Best Business Writing 2013 by Dean Starkman


Asperger Syndrome, bank run, Basel III, call centre, clean water, cloud computing, collateralized debt obligation, Columbine, computer vision, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, Erik Brynjolfsson, eurozone crisis, Exxon Valdez, factory automation, full employment, Goldman Sachs: Vampire Squid, hiring and firing, hydraulic fracturing, income inequality, jimmy wales, job automation, late fees, London Whale, low skilled workers, Mahatma Gandhi, market clearing, Maui Hawaii, Menlo Park, Occupy movement, oil shale / tar sands, price stability, Ray Kurzweil, Silicon Valley, Skype, sovereign wealth fund, stakhanovite, Steve Jobs, Stuxnet, the payments system, too big to fail, Vanguard fund, wage slave, Y2K

In their TED book, the Khannas boldly declare that “mastery in the leading technology sectors of any era determines who leads in geoeconomics and dominates in geopolitics.” Technology is all, the alpha and the omega. How to Run the World, which appeared last year, already contained strong hints about what would happen once he embraced the shiny world of technobabble with open arms (and, one presumes, open pockets). There we learned that “cloud computing—not big buildings and bloated bureaucracies—is the future of global governance,” and, my favorite, “everyone who has a BlackBerry—or iPhone or Nexus One—can be their own ambassador.” Of their own country of one, presumably. Hybrid Reality contains few surprises. Khanna and his wife fashion themselves as successors to Alvin and Heidi Toffler, an earlier fast-talking tech-addled couple who thrived on selling cookie-cutter visions of the future one paperback, slogan, and consulting gig at a time.

Amazon tech support gave them the ability to see a piece of information—a partial credit card number—that Apple used to release information. In short, the very four digits that Amazon considers unimportant enough to display in the clear on the web are precisely the same ones that Apple considers secure enough to perform identity verification. The disconnect exposes flaws in data-management policies endemic to the entire technology industry and points to a looming nightmare as we enter the era of cloud computing and connected devices. This isn’t just my problem. Since Friday, August 3, when hackers broke into my accounts, I’ve heard from other users who were compromised in the same way, at least one of whom was targeted by the same group. Moreover, if your computers aren’t already cloud-connected devices, they will be soon. Apple is working hard to get all of its customers to use iCloud. Google’s entire operating system is cloud-based.

Google’s entire operating system is cloud-based. And Windows 8, the most cloud-centric operating system yet, will hit desktops by the tens of millions in the coming year. My experience leads me to believe that cloud-based systems need fundamentally different security measures. Password-based security mechanisms—which can be cracked, reset, and socially engineered—no longer suffice in the era of cloud computing. I realized something was wrong at about five p.m. on Friday. I was playing with my daughter when my iPhone suddenly powered down. I was expecting a call, so I went to plug it back in. It then rebooted to the setup screen. This was irritating, but I wasn’t concerned. I assumed it was a software glitch. And my phone automatically backs up every night. I just assumed it would be a pain in the ass, and nothing more.


pages: 411 words: 114,717

Breakout Nations: In Pursuit of the Next Economic Miracles by Ruchir Sharma


3D printing, affirmative action, Albert Einstein, American energy revolution, anti-communist, Asian financial crisis, banking crisis, Berlin Wall, BRICs, British Empire, business climate, business process, business process outsourcing, call centre, capital controls, Carmen Reinhart, central bank independence, centre right, cloud computing, collective bargaining, colonial rule, corporate governance, crony capitalism, deindustrialization, demographic dividend, Deng Xiaoping, eurozone crisis, Gini coefficient, global supply chain, housing crisis, income inequality, indoor plumbing, inflation targeting, informal economy, Kenneth Rogoff, knowledge economy, labor-force participation, labour market flexibility, land reform, M-Pesa, Mahatma Gandhi, market bubble, megacity, Mexican peso crisis / tequila crisis, new economy, oil shale / tar sands, oil shock, open economy, Peter Thiel, planetary scale, quantitative easing, reserve currency, Robert Gordon, Shenzhen was a fishing village, Silicon Valley, software is eating the world, sovereign wealth fund, The Great Moderation, Thomas L Friedman, trade liberalization, Watson beat the top human players on Jeopardy!, working-age population

U.S. dependence on foreign energy has steadily fallen from 30 percent a decade ago to 22 percent today, owing to new discoveries of oil and gas trapped in shale rock and the development of new technologies to extract it. The United States has now overtaken Russia as the number one producer of natural gas, and could reemerge as a major energy exporter in the next five years. Basic American strengths—including rapid innovation in a highly competitive market—are producing the revival of its energy industry and extending its lead in technology; all the hot new things from social networking to cloud computing seem to be emerging once again from Silicon Valley or from rising tech hotspots like Austin, Texas. As some of the big emerging markets lose their luster over the next decade, the United States could appear quite resilient in comparison. For a truly rounded view of emerging markets, my approach is to monitor everything from per capita income levels to the top-ten billionaire lists, the speeches of radical politicians, the prices of black-market money changers, the travel habits of local businessmen (for example, whether they are moving money home or offshore), the profit margins of big monopolies, and the size of second cities (oversized capital cities often indicate excessive power in the hands of the political elite).

This is why Amazon is now the world’s biggest bookseller; why Netflix is now the world’s largest video service; why the surviving telecom and music companies are the ones that transformed themselves into software companies; and why the fastest-growing video game company is one that delivers games online, Zynga. Andreessen makes a powerful case that this same transformation—the spread of useful software to new industries—is now about to hit new fields such as defense, agriculture, education, and schools, in ways that go beyond the dabbling we have seen so far. All the hottest new things, from tablet PCs to cloud computing to social networking, are emerging largely from the United States. China is one of the few other countries that has its own social networking sites, largely because of language barriers and other imposed media restrictions. America is the leader in Internet search, in business networking, in online commerce. All of these services are attracting millions of users, revolutionizing the way we interact with the Web—and one another—and threatening established businesses.

Leading skeptics about America’s productivity boom, such as Northwestern University economist Robert Gordon, say the computer and the Internet, even when rendered mobile in handheld devices, do less to raise productivity than inventions from previous technology revolutions—particularly the emergence in the late nineteenth century of electricity, the combustion engine, and indoor plumbing. The technology bulls say we haven’t seen anything yet. Everyone knows that today’s PCs are faster than machines that three decades ago would fill a warehouse. Not everyone is fully aware that the next step—cloud computing—will allow home PCs to tap the computing power of an army of warehouse-size supercomputers. It’s hard to imagine just what gains will emerge from this awesome capacity, but as a demonstration to provoke interest, Google recently used its cloud to decode the human genome . . . in eleven seconds. This shift—from merely crunching data to analyzing information—was illustrated in a viewer-friendly way by an IBM computer named “Watson” when, in early 2011, it dominated the most successful human champion of the popular American TV quiz show Jeopardy!


pages: 1,085 words: 219,144

Solr in Action by Trey Grainger, Timothy Potter


business intelligence, cloud computing, conceptual framework, crowdsourcing, data acquisition,, failed state, fault tolerance, finite state, full text search, glass ceiling, information retrieval, natural language processing, performance metric, premature optimization, recommendation engine, web application

In chapters 5 and 6, we focus on how documents get indexed, covering document schema design, field types, and text analysis. Understanding these core aspects of indexing will help you throughout the rest of the book. Chapter 1. Introduction to Solr This chapter covers Characteristics of data handled by search engines Common search engine use cases Key components of Solr Reasons to choose Solr Feature overview With fast-growing technologies such as social media, cloud computing, mobile applications, and big data, these are exciting, and challenging, times to be in computing. One of the main challenges facing software architects is handling the massive volume of data consumed and produced by a huge, global user base. In addition, users expect online applications to always be available and responsive. To address the scalability and availability needs of modern web applications, we’ve seen a growing interest in specialized, nonrelational data storage and processing technologies, collectively known as NoSQL (Not only SQL).

To handle more documents, you split the index into smaller chunks called shards, then distribute the searches across the shards. Scaling out with virtualized commodity hardware One trend in modern computing is building software architectures that can scale horizontally using virtualized commodity hardware. Add more commodity servers to handle more traffic. Fueling this trend toward using virtualized commodity hardware are cloud-computing providers such as Amazon EC2. Although Solr will run on virtualized hardware, you should be aware that search is I/O and memory intensive. Therefore, if search performance is a top priority for your organization, you should consider deploying Solr on higher-end hardware with high-performance disks, ideally solid-state drives (SSDs). Hardware considerations for deploying Solr are discussed in chapter 12.

SolrCloud You may have heard of SolrCloud and wondered what the difference is between Solr 4 and SolrCloud. Technically, SolrCloud is the code name for a subset of features in Solr 4 that makes it easier to configure and run a scalable, fault-tolerant cluster of Solr servers. Think of SolrCloud as a way to configure a distributed installation of Solr 4. Also, SolrCloud doesn’t have anything to do with running Solr in a cloud-computing environment like Amazon EC2, although you can run Solr in the cloud. We presume that the “cloud” part of the name reflects the underlying goal of the SolrCloud feature set to enable elastic scalability, high availability, and the ease of use we’ve all come to expect from cloud-based services. We cover SolrCloud in depth in chapter 13. Let’s get started by downloading Solr from the Apache website and installing it on your computer. 2.1.


pages: 390 words: 96,624

Consent of the Networked: The Worldwide Struggle for Internet Freedom by Rebecca MacKinnon


A Declaration of the Independence of Cyberspace, Bay Area Rapid Transit, Berlin Wall, business intelligence, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, cognitive dissonance, collective bargaining, conceptual framework, corporate social responsibility, Deng Xiaoping, digital Maoism, don't be evil, Filter Bubble, Firefox, future of journalism, illegal immigration, Jaron Lanier, Jeff Bezos, Julian Assange, Mark Zuckerberg, Mikhail Gorbachev, national security letter, online collectivism, pre–internet, race to the bottom, Richard Stallman, Ronald Reagan, sharing economy, Silicon Valley, Silicon Valley startup, Skype, Steve Crocker, Steven Levy, WikiLeaks

In 2011, the government moved to extend these censorship and surveillance mechanisms, as well as to improve their coordination. In March 2011, spooked by the Arab Spring, the central government established a new overarching government agency responsible for controlling all Internet platforms and services. The number of censored foreign websites, social networking platforms, and even data-hosting and “cloud computing” services expanded dramatically. Surveillance systems were upgraded to more aggressively track and identify Chinese citizens who managed to circumvent the blockages to use tools like Twitter. It became commonplace for Twitter users to be questioned about their postings, and at least one person was arrested for no other reason than a tweet she had sent out. AUTHORITARIAN DELIBERATION At 5 a.m.

Disclosure: I served on its board of directors for one year in 2007. 230 Diaspora: See “Taking a Look at Social Network Diaspora,” NY Convergence, March 14, 2011, 230 Crabgrass: 230 StatusNet: 230 FreedomBox: see Jim Dwyer, “Decentralizing the Internet So Big Brother Can’t Find You,” New York Times, February 15, 2011,; and “Freedom in the Cloud: Software Freedom, Privacy, and Security for Web 2.0 and Cloud Computing—A Speech Given by Eben Moglen at a Meeting of the Internet Society’s New York Branch on Feb. 5, 2010,” Software Freedom Law Center, 232 Chaos Computer Club:; for a colorful description of the CCC’s characters and culture, see Becky Hogge, Barefoot into Cyberspace: Adventures in Search of Techno—Utopia (London: Rebecca Hogge, 2011). 232 Chaos Communication Camp: 232 yearly winter conferences: See 232 “A Declaration of the Independence of Cyberspace”: 233 Douglas Rushkoff called on the netizens of the world to unite: Douglas Rushkoff, “The Next Net,”, January 3, 2011,


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen


3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, cuban missile crisis, David Brooks, disintermediation, 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, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Occupy movement, packet switching, PageRank, Paul Graham, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, 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 medium is the message, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

It is the information technology revolution,” explains the Cambridge University political scientist David Runciman.11 We are the brink of a foreign land—a data-saturated place that the British writer John Lanchester calls a “new kind of human society.”12 “The single most important trend in the world today is the fact that globalization and the information technology revolution have gone to a whole new level,” adds the New York Times columnist Thomas Friedman. Thanks to cloud computing, robotics, Facebook, Google, LinkedIn, Twitter, the iPad, and cheap Internet-enabled smartphones, Friedman says, “the world has gone from connected to hyper-connected.”13 Runciman, Lanchester, and Friedman are all describing the same great economic, cultural, and, above all, intellectual transformation. “The Internet,” Joi Ito, the director of the MIT Media Lab, notes, “is not a technology; it’s a belief system.”14 Everything and everyone are being connected in a network revolution that is radically disrupting every aspect of today’s world.

Harford suspects 2014 might be the year that computers finally become self-aware, a prospect that he understandably finds “sobering” because of its “negative impact of . . . on the job market.”22 He is particularly concerned with how increasingly intelligent technology is hollowing out middle-income jobs such as typists, clerks, travel agents, and bank tellers. Equally sobering is the involvement of dominant Internet companies like Google and Amazon in a robot-controlled society that the technology writer Nicholas Carr foresees in his 2014 book about “automation and us,” The Glass Cage. Carr’s earlier 2008 work, The Big Switch, made the important argument that, with the increasingly ubiquity of cloud computing, the network has indeed become a giant computer, with the World Wide Web thus being “The World Wide Computer.”23 And with automation, Carr warns in The Glass Cage, the World Wide Computer is now designing a society that threatens to discard human beings. “The prevailing methods of computerized communication pretty much ensure that the role of people will go on shrinking,” Carr writes in The Glass Cage.


pages: 459 words: 103,153

Adapt: Why Success Always Starts With Failure by Tim Harford


Andrew Wiles, banking crisis, Basel III, Berlin Wall, Bernie Madoff, Black Swan, car-free, carbon footprint, Cass Sunstein, charter city, Clayton Christensen, clean water, cloud computing, cognitive dissonance, complexity theory, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, Dava Sobel, Deep Water Horizon, Deng Xiaoping, double entry bookkeeping, Edmond Halley,, Erik Brynjolfsson, experimental subject, Fall of the Berlin Wall, Fermat's Last Theorem, Firefox, food miles, Gerolamo Cardano, global supply chain, Isaac Newton, Jane Jacobs, Jarndyce and Jarndyce, Jarndyce and Jarndyce, John Harrison: Longitude, knowledge worker, loose coupling, Martin Wolf, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Netflix Prize, New Urbanism, Nick Leeson, PageRank, Piper Alpha, profit motive, Richard Florida, Richard Thaler, rolodex, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, South China Sea, special economic zone, spectrum auction, Steve Jobs, supply-chain management, the market place, The Wisdom of Crowds, too big to fail, trade route, Tyler Cowen: Great Stagnation, web application, X Prize

Imagine that the governments of the world’s major fossil fuels producers agreed to the following approach: that each of them would levy a tax of about $50 per tonne of carbon contained in any fossil fuel mined or extracted in its territory – roughly $14 per tonne of carbon dioxide. This would be, roughly, an extra $5 per barrel of oil, and nearly $40 per tonne of coal.* That decision might appear to have nothing to do with a carbon-calculating phone app, but in fact it has everything to do with it. The carbon tax would piggyback on the system of market prices, which acts as a vast analogue cloud computer, pulling and pushing resources to wherever they have the highest value. A $50 carbon tax would increase the price of gasoline by about 12 cents a gallon, creating a small incentive to drive less, and more efficiently, and to buy more efficient cars. It would increase the price of a kilowatt hour of electricity – by about a cent and a half if the energy came from coal, but only by three quarters of a cent if the energy came from natural gas.

(The differences between a carbon permit scheme and a carbon tax are insignificant relative to the differences between having some kind of carbon price and not having one.) Carbon pricing tries to harness Orgel’s law by focusing on what we think the ultimate goal is: a reduction of the greenhouse gas emitted into the atmosphere, at the lowest possible cost. To put it another way, carbon pricing hitches a ride on an amazing decentralised cloud computer – the markets that make up the world’s economy – to provide feedback to billions of individual experiments, all aimed at cutting carbon emissions, because cutting carbon emissions saves money. Of course, it’s not that simple. The carbon price proposal raises many questions. Fortunately, because the idea has been around for a while, an army of policy wonks has had plenty of time to figure out some answers.


pages: 378 words: 94,468

Drugs 2.0: The Web Revolution That's Changing How the World Gets High by Mike Power


air freight, banking crisis, bitcoin, blockchain, Buckminster Fuller, Burning Man, cloud computing, credit crunch, crowdsourcing, death of newspapers, double helix, fiat currency, Firefox, Fractional reserve banking, frictionless, Haight Ashbury, Kevin Kelly, means of production, Menlo Park, Mother of all demos, Network effects, packet switching, pattern recognition, pre–internet, RAND corporation, Satoshi Nakamoto, Skype, Stephen Hawking, Steve Jobs, Stewart Brand, trade route, Whole Earth Catalog, Zimmermann PGP

What’s more, there are vendors in many countries so there’s no need to worry about international postal or customs issues: users in the US or UK or the Netherlands – or indeed, in dozens of countries worldwide – can buy drugs from dealers in their own countries, removing the danger of border staff targeting their packages. Technically, while the Tor network is now small, meaning its pages load more slowly than those on normal websites, in coming years the power of cloud computing means that more relays carrying the service will be able to be set up cheaply. In November 2011 Amazon’s cloud servers started hosting Tor bridges. For three dollars a month, users click and support the project, with no knowledge of the technology required. And in late 2012, the Noisebridge group of online activists made supporting the Tor network as easy as clicking on a donate button at

., 1 Götz, Wolfgang, 1 Goulão, João, 1 Granquist, Lamont, 1 Grateful Dead, 1 Grey, Briane, 1 Guardian, 1, 2 Guatemala, 1 Gungell, Kathy, 1 hagigat, 1 Haight-Ashbury, 1 Hancyez, Laszlo, 1 harm reduction, 1, 2, 3, 4 Harrigan, Martin, 1 Hartelius, Jonas, 1 hashish, see marijuana Haupt Hansen, Dannie, 1, 2, 3 Hawaiian Baby Woodrose, 1 headshops, 1, 2, 3, 4, 5, 6, 7, 8 health supplements, 1 Heffter, Arthur, 1 Herbal Ecstasy, 1 heroin, 1, 2, 3, 4, 5 analogues, 1, 2 and decriminalization debate, 1, 2, 3 intravenous use, 1, 2 and Mexican drugs war, 1 online sales, 1, 2 Hitchens, Peter, 1 HIV, 1, 2 Hive, the, 1, 2, 3, 4 Hofmann, Albert, 1 Holder, Eric, 1 Holland, see Netherlands Hollis, Tim, 1 Home Affairs Select Committee (HASC), 1 Hong Kong, 1, 2, 3 House of Commons, 1, 2 House of Lords, 1, 2, 3 HTML, 1, 2, 3 Huffington Post, 1 Huffman, John William, 1, 2, 3 hushmail, 1, 2 Huson, Hobart, 1 Huxley, Aldous, 1, 2, 3 Hyperreal Drug Archives, 1 Ibiza, 1, 2 Independent Drug Monitoring Unit, 1 Independent Scientific Committee on Drugs, 1 India, 1, 2, 3 Indopan, 1 Institute of Drugs and Drug Addiction, 1 International Foundation for Advanced Study, 1 International Opium Convention, 1, 2 internet arrival of world wide web, 1 the Backbone Cabal, 1 and cloud computing, 1 Dark Web, 1, 2, 3 domain name system, 1 early development, 1 growth of drug sales, 1 speeds, 1 user numbers, 1 value of ecommerce, 1 Web 2.0 era, 1 Invisible Touch, 1 iPhone, 1 Iran, 1 Ireland, closure of headshops, 1 isosafrole, 1 Israel, 1, 2 iTunes, 1 Iversen, Les, 1 Ivory Wave, 1, 2 Japan, 1 Jefferson Airplane, 1 Jenkins, Floridian Jeffrey (Eleusis/Zwitterion), 1 JLF Poisonous Non-Consumables, 1, 2 Jobs, Steve, 1 Johnson, Alan, 1 Jones, Grace, 1 Jones, Lloyd, 1 Journal of Medicinal Chemistry, 1 JWH-018, 1, 2, 3 JWH-073, 1, 2 JWH-200, 1 K2, 1 Kelly, Kevin, 1 Kentish Gazette, 1 Kesey, Ken, 1, 2 ketamine, 1, 2, 3, 4, 5, 6, 7, 8 online sales, 1, 2 khat, 1 Kinetic, 1, 2 King, Les, 1 Kleinrock, Leonard, 1 kratom, 1 krebbe, 1 Kushlick, Danny, 1 Laing, R.


pages: 416 words: 106,582

This Will Make You Smarter: 150 New Scientific Concepts to Improve Your Thinking by John Brockman


23andMe, Albert Einstein, Alfred Russel Wallace, banking crisis, Barry Marshall: ulcers, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, butterfly effect, Cass Sunstein, cloud computing, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Exxon Valdez, Flash crash, Flynn Effect, hive mind, impulse control, information retrieval, Isaac Newton, Jaron Lanier, John von Neumann, Kevin Kelly, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, open economy, place-making, placebo effect, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Schrödinger's Cat, security theater, Silicon Valley, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, the scientific method, Thorstein Veblen, Turing complete, Turing machine, Walter Mischel, Whole Earth Catalog

While information technology can reveal truths, it can also create stronger illusions than we are used to. For instance, sensors all over the world, connected through cloud computing, can reveal urgent patterns of change in climate data. But endless chains of online retelling also create an illusion for masses of people that the original data is a hoax. The illusion of Platonic information plagues finance. Financial instruments are becoming multilevel derivatives of the real actions on the ground, which finance is ultimately supposed to motivate and optimize. The reason to finance the buying of a house ought to be at least in part to get the house bought. But an empire of specialists and giant growths of cloud computers showed, in the run-up to the Great Recession, that it is possible for sufficiently complex financial instruments to become completely disconnected from their ultimate purpose.


pages: 309 words: 95,495

Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe by Greg Ip


Affordable Care Act / Obamacare, Air France Flight 447, air freight, airport security, Asian financial crisis, asset-backed security, bank run, banking crisis, Bretton Woods, capital controls, central bank independence, cloud computing, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, Daniel Kahneman / Amos Tversky, diversified portfolio, double helix, endowment effect, Exxon Valdez, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, full employment, global supply chain, hindsight bias, Hyman Minsky, Joseph Schumpeter, Kenneth Rogoff, London Whale, Long Term Capital Management, market bubble, moral hazard, Network effects, new economy, offshore financial centre, paradox of thrift,, Ponzi scheme, quantitative easing, Ralph Nader, Richard Thaler, risk tolerance, Ronald Reagan, savings glut, technology bubble, The Great Moderation, too big to fail, transaction costs, union organizing, Unsafe at Any Speed, value at risk

Ordinarily, that is not a recipe for survival. But in those rarefied times, it was: the following year, though the company was still losing money and the Nasdaq bubble was deflating, Amazon borrowed $870 million in euros, also convertible to stock. In effect, Amazon exploited the irrational exuberance of the dot-com bubble to stay afloat long enough to become a colossus, revolutionizing not just retailing but book publishing and cloud computing. Between 2004 and 2008, it paid back all its bondholders, some at a premium, except those who had converted their bonds to shares. Dot-com stocks were the most famous players during the technology bubble, but more money was lost in a different sector. A host of existing and start-up telecommunications companies persuaded investors there was a mint to be made laying the fiber-optic networks that would carry booming Internet traffic between cities and continents.

Though investors in the fiber-optic boom lost their shirts, the glut of fiber had an unexpected benefit: ridiculously cheap bandwidth made possible countless new business models that had been impossible when capacity was limited. Internet service providers in emerging markets could offer their customers access to the global Internet by buying cheap capacity on cables laid during the dot-com boom. Cheap bandwidth made cloud computing possible: companies could rent space at massive data processing centers thousands of miles away, giving them almost unlimited processing power without costly investment in equipment of their own. Facebook members around the world communicate instantly and seamlessly with one another thanks to the long-term leases that Facebook has on these underground networks. And an astonishing share of those networks were built by now-bankrupt companies: 63 percent of transatlantic fiber-optic capacity, 35 percent of trans-Pacific, and 39 percent of the capacity between the United States and Latin America, according to Stronge.


pages: 275 words: 84,418

Dogfight: How Apple and Google Went to War and Started a Revolution by Fred Vogelstein


Apple II, cloud computing, disintermediation, don't be evil, Dynabook, Firefox, Google Chrome, Google Glasses, Googley, Jony Ive, Mark Zuckerberg, Peter Thiel, pre–internet, Silicon Valley, Silicon Valley startup, Skype, software patent, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Tim Cook: Apple, web application

It was much more customizable than the iPhone. However, it didn’t work with iTunes, the entertainment software of choice. You couldn’t even sync it to your computer easily, like an iPhone. Instead, to get your information from your computer to the G1, you had to let the phone sync with Google’s cloud, then sync your PC to Google’s cloud as well. That may be a virtue today, but back then, before cloud computing was mainstream, it was a hassle. Googlers were even tougher on the G1 than consumers. That year Google gave G1s to employees instead of the standard companywide Christmas bonus. Employees were not happy about it. I asked a few back then how they liked theirs and got answers such as “Great. Do you want mine?” or “Count how many are for sale on eBay. That’s your answer.” In subsequent Friday company meetings, Googlers openly asked why the company was wasting its time with Android.

He has been thinking about these issues and watching them evolve for more than twenty years, and he has been doing it from one of the best vantage points in the world—with the access to people and information only available to a select few Silicon Valley insiders. At the moment he and his partner, Ben Horowitz, are known as two of the top VCs in technology. But many have forgotten that Andreessen was also the cocreator of the first Internet browser, Mosaic, which became Netscape Communications in 1994. He helped sell it to America Online for $4 billion in 1999—despite losing the browser wars to Microsoft. Then in 2000 he cofounded one of the first cloud-computing companies, Loudcloud. It nearly failed when the Internet bubble popped. But he and Horowitz changed the name to Opsware, rebuilt it, and sold it to Hewlett-Packard for $1.6 billion in 2007. Most of the best-known VCs took a decade or more to make a splash. Andreessen and Horowitz have become two of the top VCs in four years. Andreessen says, In 1993 it was very obvious what the world would be like if everyone had a high-speed Internet connection and a big screen because at the University of Illinois [where he was at college] we had those things.


pages: 296 words: 86,610

The Bitcoin Guidebook: How to Obtain, Invest, and Spend the World's First Decentralized Cryptocurrency by Ian Demartino


3D printing, AltaVista, altcoin, bitcoin, blockchain, buy low sell high, capital controls, cloud computing, corporate governance, crowdsourcing, cryptocurrency, distributed ledger, Edward Snowden, Elon Musk, ethereum blockchain, fiat currency, Firefox, forensic accounting, global village, GnuPG, Google Earth, Haight Ashbury, Jacob Appelbaum, Kevin Kelly, Kickstarter, litecoin, M-Pesa, Marshall McLuhan, Oculus Rift, peer-to-peer lending, Ponzi scheme, prediction markets, ransomware, Satoshi Nakamoto, self-driving car, Skype, smart contracts, Steven Levy, the medium is the message, underbanked, WikiLeaks, Zimmermann PGP

In 1999, he posted about the “God Protocol,” a concept that borrowed heavily from Wei Dai’s B-money proposal.11 This was offered by Dai on the Cypherpunk mailing list in 1998.12 It suggested using hashcash—a system that prevents email spam by requiring extra computational power to be used to send emails, making spam too expensive—to create rarity in cryptocurrencies, one of the most important features used in Bitcoin today. It is rarity that allows Bitcoin to have a supply-and-demand dynamic. The God Protocol was a proposal to replace a third-party central server with an automated virtual third party. It used early concepts of cloud computing and, had it been implemented, would have likely become a proto-version of today’s autonomous corporation—a digital corporation that can function with little or no human input—which many people imagine is next in Bitcoin. The God Protocol was intended as a solution for smart contracts—another concept later revived by Bitcoin. Szabo writes in his blog: [Network security theorists] have developed protocols that create virtual machines between two or more parties.

There is a Bitcoin-like coin in Ethereum, called Ether, that makes the system run, secures the network and settles contracts. What has really made headlines, however, is that major technology companies, banks and financial institutions around the world have announced they are working on projects using Ethereum. Details are thin at this point, but UBS and Barclays have both announced an interest in Ethereum, and Microsoft is offering Ethereum in some capacity on its cloud computing service, making it easy for developers to create Ethereum apps. This support from the outside world is unheard of for cryptocurrencies not named Bitcoin and that, more than anything, is the biggest sign that Ethereum will have some success going forward. It has a long way to go before it becomes the next Bitcoin, which is still light-years ahead in support from both inside and outside the community.


pages: 103 words: 32,131

Program Or Be Programmed: Ten Commands for a Digital Age by Douglas Rushkoff


banking crisis, big-box store, citizen journalism, cloud computing, East Village, financial innovation, Firefox, hive mind, Howard Rheingold, invention of the printing press, Kevin Kelly, Marshall McLuhan, Silicon Valley, statistical model, Stewart Brand, Ted Nelson, WikiLeaks

It’s not that Benjamin despises popular culture—it’s that he sees real art and artifacts being absorbed by a bigger spectacle, and audiences losing the ability and desire to tell the difference between that spectacle and real world. Strangely enough, as we migrate from his world of mass-produced objects to the realm of even more highly abstracted digital facsimiles, we nostalgically collect the artifacts of midcentury mass production as if they were works of art. Each Philco radio, Heywood Wakefield dresser, or Chambers stove is treasured as if it were an original. We can only wonder if cloud computing may make us nostalgic one day for having a real “file” on the hard drive of one’s own computer—or if silicon brain implants may make us wax poetic for the days when one’s computing happened on a laptop. In the march toward increasing abstraction, whatever we had previously will seem like the real thing. By recognizing the abstracting bias of digital technologies, however, we can use it to our advantage.


pages: 102 words: 29,596

The Alliance: Managing Talent in the Networked Age by Reid Hoffman, Ben Casnocha, Chris Yeh


Airbnb, Amazon Web Services, centralized clearinghouse, cloud computing, Jeff Bezos, Jony Ive, new economy, pre–internet, Silicon Valley, Silicon Valley startup, software as a service, Steve Jobs

And that’s how Lasseter ended up back at Disney as its chief creative officer of Disney Animation Studios.9 Disney’s management hired an entrepreneurial talent like Lasseter, but they treated him as a commodity rather than an ally, and in the process, they lost their chance to develop a multibillion-dollar business. Lasseter would have been happy to develop that business within Disney, but his managers wouldn’t let him. Benjamin Black and Amazon Web Services Amazon didn’t make the same mistake as Disney. Recently, it used the principles of the alliance to generate a new multibillion-dollar business. Amazon has become a leader in the field of cloud computing, thanks to Amazon Web Services (AWS), which allows companies to rent online storage and computing power, rather than buying and operating their own servers. Companies ranging from Fortune 500 giants to one-person start-ups run their businesses on AWS. What most people don’t realize is that the idea for AWS didn’t come from Amazon’s famed entrepreneurial founder and CEO, Jeff Bezos, or even from a member of his executive team, but rather from an “ordinary” employee.


pages: 272 words: 19,172

Hedge Fund Market Wizards by Jack D. Schwager


asset-backed security, backtesting, banking crisis, barriers to entry, Bernie Madoff, Black-Scholes formula, British Empire, Claude Shannon: information theory, cloud computing, collateralized debt obligation, commodity trading advisor, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, diversification, diversified portfolio, family office, financial independence, fixed income, Flash crash, hindsight bias, implied volatility, index fund, James Dyson, Long Term Capital Management, margin call, market bubble, market fundamentalism, merger arbitrage, oil shock, pattern recognition,, Ponzi scheme, private sector deleveraging, quantitative easing, quantitative trading / quantitative finance, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Sharpe ratio, short selling, statistical arbitrage, Steve Jobs, systematic trading, technology bubble, transaction costs, value at risk, yield curve

I felt comfortable with it. I wouldn’t feel comfortable with something like this. [He brings up the chart for FFIV, a cloud computing company.] I would never buy that stock. [The chart shows a long, nearly unbroken uptrend, followed by a huge downside gap not far from the high, and then a rebound about two-thirds of the way back to the high.] This is a stock I would short. Tomorrow, if the market is up, I will probably be a seller. Why specifically are you so negative on this chart? It is a broken stock. It broke on big volume. The indexes have made new highs, and the stock can’t get above its 50-day moving average. All the investors had been riding the stock all the way up. Although cloud computing is a great story, it is overplayed. Current prices way outstrip any growth potential for the next few years.

Are there mistakes you learned from as a trader? As an equity trader, I learned the short-selling lessons relatively early. There is no high for a concept stock. It is always better to be long before they have already moved a lot than to try to figure out where to go short. What are examples of concept stocks? The Internet stocks in the 1990s and biotech stocks in the late 1990s to early 2000s. How about a current example? The cloud computing companies. When P/E multiples get to 50, 60, or 70, you are in the realm of concept stocks. I understand that you do both position trading and short-term trading. Is there something about the way prices move intraday that is helpful in short-term trading? Yes. Do you know what happens in a bull market? Prices open up lower and then go up for the rest of the day. In a bear market, they open up higher and go down for the rest of the day.


pages: 798 words: 240,182

The Transhumanist Reader by Max More, Natasha Vita-More


23andMe, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, Bill Joy: nanobots, bioinformatics, brain emulation, Buckminster Fuller, cellular automata, clean water, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, conceptual framework, Conway's Game of Life, cosmological principle, data acquisition, discovery of DNA, Drosophila,, experimental subject, Extropian, fault tolerance, Flynn Effect, Francis Fukuyama: the end of history, Frank Gehry, friendly AI, game design, germ theory of disease, hypertext link, impulse control, index fund, John von Neumann, joint-stock company, Kevin Kelly, Law of Accelerating Returns, life extension, Louis Pasteur, Menlo Park, meta analysis, meta-analysis, moral hazard, Network effects, Norbert Wiener, P = NP, pattern recognition, phenotype, positional goods, prediction markets, presumed consent, Ray Kurzweil, reversible computing, RFID, Richard Feynman, Ronald Reagan, silicon-based life, Singularitarianism, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, technological singularity, Ted Nelson, telepresence, telepresence robot, telerobotics, the built environment, The Coming Technological Singularity, the scientific method, The Wisdom of Crowds, transaction costs, Turing machine, Turing test, Upton Sinclair, Vernor Vinge, Von Neumann architecture, Whole Earth Review, women in the workforce

Michael Nielsen is one of the pioneers of quantum computing. He is an essayist, speaker, and advocate of open science. His most recent book is Reinventing Discovery: The New Era of Networked Science (2012). Ravi Pandya is Systems Software Architect, Microsoft. He co-authored with Sergey Bykov, Alan Geller, Gabriel Kliot, et al. “Orleans: Could Computer for Everyone” (ACM Symposium on Cloud Computing, 2011); and with Sergey Bykov, Alan Geller, Gabriel Kliot, et al. “Orleans: A Framework for Cloud Computing” (Microsoft Research, 2010). Giulio Prisco, is a physicist, and former Senior Manager, European Space Agency. He authored “Transcendent Engineering” (The Journal of Personal Cyberconsciousness 6, 2011); “Let a Thousand Turtles Fly” (Quest for Joyful Immortality, 2012); and “Transhumanist Avatars Storm Second Life” (H + Magazine, 2011).

In principle it might have been doable given the technology of that era, but it would have been insanely difficult – whereas by the time the Web came about in the 1990s it seemed almost a natural consequence of the technological infrastructure existing at that time. Similarly, in the 1960s, even if someone had come up with a workable design for human-level AGI, it would have been extraordinarily difficult to get it implemented and working using the hardware and software tools available. But now, with cloud computing, multiprocessor machines with terabytes of RAM, powerful algorithm libraries and debuggers, and a far more mature theory of cognitive science, we are in a whole different position. The conceptual and technological ecosystem is poised for AGI, in the same sense that it was poised for the Web in the 1990s. And just as the Web spread faster than almost anybody foresaw – so, once it gets started, will AGI.


pages: 834 words: 180,700

The Architecture of Open Source Applications by Amy Brown, Greg Wilson


8-hour work day, anti-pattern, bioinformatics,, cloud computing, collaborative editing, combinatorial explosion, computer vision, continuous integration, create, read, update, delete, Debian, domain-specific language,, fault tolerance, finite state, Firefox, friendly fire, linked data, load shedding, locality of reference, loose coupling, Mars Rover, MVC pattern, premature optimization, recommendation engine, revision control, side project, Skype, slashdot, social web, speech recognition, the scientific method, The Wisdom of Crowds, web application, WebSocket

Roy Bryant (Snowflock): In 20 years as a software architect and CTO, Roy designed systems including Electronics Workbench (now National Instruments' Multisim) and the Linkwalker Data Pipeline, which won Microsoft's worldwide Winning Customer Award for High-Performance Computing in 2006. After selling his latest startup, he returned to the University of Toronto to do graduate studies in Computer Science with a research focus on virtualization and cloud computing. Most recently, he published his Kaleidoscope extensions to Snowflock at ACM's Eurosys Conference in 2011. His personal web site is Russell Bryant (Asterisk): Russell is the Engineering Manager for the Open Source Software team at Digium, Inc. He has been a core member of the Asterisk development team since the Fall of 2004. He has since contributed to almost all areas of Asterisk development, from project management to core architectural design and development.

He is a lead developer of the VisTrails system, and a senior software architect at VisTrails, Inc. Hairong Kuang (HDFS) is a long time contributor and committer to the Hadoop project, which she has passionately worked on currently at Facebook and previously at Yahoo!. Prior to industry, she was an Assistant Professor at California State Polytechnic University, Pomona. She received Ph.D. in Computer Science from the University of California at Irvine. Her interests include cloud computing, mobile agents, parallel computing, and distributed systems. H. Andrés Lagar-Cavilla (Snowflock): Andrés is a software systems researcher who does experimental work on virtualization, operating systems, security, cluster computing, and mobile computing. He has a B.A.Sc. from Argentina, and an M.Sc. and Ph.D. in Computer Science from University of Toronto, and can be found online at

Footnotes "Be conservative in what you do, be liberal in what you accept from others" Somehow I suspect that using Unicode for configuration would not prove popular. The Architecture of Open Source Applications Amy Brown and Greg Wilson (eds.) ISBN 978-1-257-63801-7 License / Buy / Contribute Chapter 18. SnowFlock Roy Bryant and Andrés Lagar-Cavilla Cloud computing provides an attractively affordable computing platform. Instead of buying and configuring a physical server, with all the associated time, effort and up front costs, users can rent "servers" in the cloud with a few mouse clicks for less than 10 cents per hour. Cloud providers keep their costs low by providing virtual machines (VMs) instead of physical computers. The key enabler is the virtualization software, called a virtual machine monitor (VMM), that emulates a physical machine.


pages: 476 words: 132,042

What Technology Wants by Kevin Kelly


Albert Einstein, Alfred Russel Wallace, Buckminster Fuller,, carbon-based life, Cass Sunstein, charter city, Clayton Christensen, cloud computing, computer vision, Danny Hillis, dematerialisation, demographic transition, double entry bookkeeping,, Exxon Valdez, George Gilder, gravity well, hive mind, Howard Rheingold, interchangeable parts, invention of air conditioning, invention of writing, Isaac Newton, Jaron Lanier, John Conway, John von Neumann, Kevin Kelly, knowledge economy, Lao Tzu, life extension, Louis Daguerre, Marshall McLuhan, megacity, meta analysis, meta-analysis, new economy, out of africa, performance metric, personalized medicine, phenotype, Picturephone, planetary scale, RAND corporation, random walk, Ray Kurzweil, recommendation engine, refrigerator car, Richard Florida, Silicon Valley, silicon-based life, Skype, speech recognition, Stephen Hawking, Steve Jobs, Stewart Brand, Ted Kaczynski, the built environment, the scientific method, Thomas Malthus, Vernor Vinge, Whole Earth Catalog, Y2K

Computers have already absorbed calculators, spreadsheets, typewriters, film, telegrams, telephones, walkie-talkies, compasses and sextants, television, radio, turntables, draft tables, mixing boards, war games, music studios, type foundries, flight simulators, and many other vocational instruments. You can no longer tell what a person does by looking at their workplace, because they all look the same: a personal computer; 90 percent of employees are using the same tool. Is that the desk of the CEO, the accountant, the designer, or the receptionist? This convergence is amplified by cloud computing, where the actual work is done on the net as a whole and the tool at hand merely becomes a portal to the work. All portals have become the simplest possible window: a flat screen of some size. This convergence is temporary. We are still in the early stages of computerization—or rather, intelligenation. Everywhere we currently apply our own personal intelligence (in other words, everywhere we work and play) we are rapidly applying artificial and collective intelligence as well, and rapidly overhauling our tools and expectations.

Caspari, Rachel Cavendish, Henry cell phones Celtic tribes Chaisson, Eric chimpanzees China chlorophyll choices affluence and in cities collective consequences of convergent inventions and enforced expansion of as historical contingency in intentional domain limited, of Amish mistaken of others paradox of within preordained development quantum willing chromosomes cities evolutionary beauty of global population of green historical homesteading in increased choices offered by megalopolises slums of, see slums civilization as devolution as ecumenopolis freedom and tribal wars against civilization, collapse of death toll of in postcollapse period see also anticivilizationists Clarke, Arthur C. clocks clothing cloud computing coal power coevolution Cole, John Colonial America compass, magnetic complex adaptive systems complexity future scenarios of as long-term trend specialization and computer chips transistors in see also Moore’s Law computers digital storage in DNA increased software complexity of invention of multiple functions of obsolete specialty computer simulations computer viruses contingency choices in in convergent inventions convergence see also inventions, convergence of “Convergent Evolution” (McGhee) conviviality Conway, John Cooke, William corals Bryozoa cornets Correns, Karl Erich crafts Crichton, Michael Cro-Magnons, see Sapiens crossbows cryptochromes customization, personal Daguerre, Louis Darwin, Charles Davies, Paul Davis, Mike Dawkins, Richard DDT Dean, Bashford decentralization de Duve, Christian deforestation demographic transition Dennett, Daniel Denton, Michael desert environments de Vries, Hugo Diamond, Jared Didion, Joan dinosaurs convergent lineages of diversity cultural differences in of ethnic and social preferences excessive choices offered by fringe of intelligence as long-term trend uniformity in DNA invented alternatives to mutation rate in mysterious origins of self-organization of synthesis of DNA sequencing Dobe tribe dolphins intelligence of domestication animal crop independent inventions of double-entry bookkeeping du Chaillu, Paul Dunn, Mark Dyson, Freeman Earth First!


pages: 574 words: 164,509

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom


agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, anti-communist, artificial general intelligence, autonomous vehicles, barriers to entry, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, demographic transition, Douglas Hofstadter, Drosophila, Elon Musk,, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, Gödel, Escher, Bach, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John von Neumann, knowledge worker, Menlo Park, meta analysis, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Norbert Wiener, NP-complete, nuclear winter, optical character recognition, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, transaction costs, Turing machine, Vernor Vinge, Watson beat the top human players on Jeopardy!, World Values Survey

The only difficulty involved is gaining access to additional computing power. There are several ways for a system to expand its hardware base, each relevant over a different timescale. In the short term, computing power should scale roughly linearly with funding: twice the funding buys twice the number of computers, enabling twice as many instances of the software to be run simultaneously. The emergence of cloud computing services gives a project the option to scale up its computational resources without even having to wait for new computers to be delivered and installed, though concerns over secrecy might favor the use of in-house computers. (In certain scenarios, computing power could also be obtained by other means, such as by commandeering botnets.13) Just how easy it would be to scale the system by a given factor depends on how much computing power the initial system uses.

Alternatively, the AI might be able to use its hacking superpower to escape confinement. If the AI does not possess these capabilities, it might first need to use its intelligence amplification superpower to develop the requisite proficiency in social manipulation or hacking. A superintelligent AI will presumably be born into a highly networked world. One could point to various developments that could potentially help a future AI to control the world—cloud computing, proliferation of web-connected sensors, military and civilian drones, automation in research labs and manufacturing plants, increased reliance on electronic payment systems and digitized financial assets, and increased use of automated information-filtering and decision support systems. Assets like these could potentially be acquired by an AI at digital speeds, expediting its rise to power (though advances in cybersecurity might make it harder).


pages: 1,025 words: 150,187

ZeroMQ by Pieter Hintjens


anti-pattern, carbon footprint, cloud computing, Debian, distributed revision control, domain-specific language, factory automation, fault tolerance, fear of failure, finite state, Internet of things, iterative process, premature optimization, profit motive, pull request, revision control, RFC: Request For Comment, Richard Stallman, Skype, smart transportation, software patent, Steve Jobs, Valgrind, WebSocket

If there’s no request from a client within, say, two seconds, the server can detect this and destroy any state it’s holding for that client. Worked Example: Inter-Broker Routing Let’s take everything we’ve seen so far and scale things up to a real application. We’ll build this step-by-step over several iterations. Suppose our best client calls us urgently and asks for a design of a large cloud computing facility. He has this vision of a cloud that spans many data centers, each a cluster of clients and workers, and that works together as a whole. Because we’re smart enough to know that practice always beats theory, we propose to make a working simulation using ØMQ. Our client, eager to lock down the budget before his own boss changes his mind, and having read great things about ØMQ on Twitter, agrees.

Symbols 0MQ, ØMQ in a Hundred Words (see ZeroMQ) A ABNF, Using ABNF AMQP, Why We Needed ØMQ, Authentication Using SASL authentication for, Authentication Using SASL messaging used by, Why We Needed ØMQ APIs, A High-Level API for ØMQ–The CZMQ High-Level API, Step 3: Decide on the Contracts, Initial Design Cut: The API, Public API–Public API, Designing the API–Designing the API contracts as, Step 3: Decide on the Contracts for discovery, Designing the API–Designing the API for FileMQ project, Initial Design Cut: The API, Public API–Public API high-level, for ZeroMQ, A High-Level API for ØMQ–The CZMQ High-Level API assertions, Handling Errors and ETERM, On Assertions, Protocol Assertions–Protocol Assertions (see also testing) best practices for, On Assertions protocol assertions, Protocol Assertions–Protocol Assertions asserts, removed by optimizer, Handling Errors and ETERM asynchronous client/server pattern, The Asynchronous Client/Server Pattern–The Asynchronous Client/Server Pattern asynchronous disconnected network, Disconnected Reliability (Titanic Pattern)–Disconnected Reliability (Titanic Pattern) Asynchronous Majordomo pattern, Asynchronous Majordomo Pattern–Asynchronous Majordomo Pattern authentication, State Machines, Authentication Using SASL–Authentication Using SASL SASL for, Authentication Using SASL–Authentication Using SASL state for, State Machines B Benevolent Tyrant role, The Benevolent Tyrant binary logging protocol, Binary Logging Protocol–Binary Logging Protocol Binary Star pattern, High-Availability Pair (Binary Star Pattern)–Binary Star Reactor, Detailed Requirements–Detailed Requirements, Preventing Split-Brain Syndrome, Binary Star Reactor–Binary Star Reactor, Adding the Binary Star Pattern for Reliability–Adding the Binary Star Pattern for Reliability adding to Clone pattern, Adding the Binary Star Pattern for Reliability–Adding the Binary Star Pattern for Reliability for reactor class, Binary Star Reactor–Binary Star Reactor requirements for, Detailed Requirements–Detailed Requirements split-brain syndrome, preventing, Preventing Split-Brain Syndrome binding, Invalid Combinations (see server node) Black Box pattern, High-Speed Subscribers (Black Box Pattern)–High-Speed Subscribers (Black Box Pattern) bridging, Transport Bridging–Transport Bridging broker, Intermediaries and Proxies (see proxy or broker) brokerless messaging, reliability for, Brokerless Reliability (Freelance Pattern)–Model Three: Complex and Nasty BSD license, The Contract–The Contract, Care and Feeding burnout, reducing risk of, Burnout–Burnout C C string format, A Minor Note on Strings–A Minor Note on Strings C4 contract, The ØMQ Community, The ØMQ Process: C4–Evolution of Public Contracts Canary Watcher role, The Canary Watcher Cheap or Nasty pattern, The Cheap or Nasty Pattern CHP (Clustered Hashmap Protocol), The Clustered Hashmap Protocol–Security client node, Plugging Sockets into the Topology–Plugging Sockets into the Topology, Plugging Sockets into the Topology, Plugging Sockets into the Topology, Plugging Sockets into the Topology, Invalid Combinations, Designing Reliability, Designing Reliability, Designing Reliability, Client-Side Reliability (Lazy Pirate Pattern)–Client-Side Reliability (Lazy Pirate Pattern), Brokerless Reliability (Freelance Pattern)–Model Three: Complex and Nasty connecting sockets to endpoint, Plugging Sockets into the Topology–Plugging Sockets into the Topology multiple, connecting to multiple servers with proxy, Designing Reliability (see also Majordomo pattern; Paranoid Pirate pattern; Simple Pirate pattern; Titanic pattern) multiple, connecting to multiple servers without proxies, Designing Reliability, Brokerless Reliability (Freelance Pattern)–Model Three: Complex and Nasty multiple, connecting to single server, Designing Reliability, Client-Side Reliability (Lazy Pirate Pattern)–Client-Side Reliability (Lazy Pirate Pattern) role of, Plugging Sockets into the Topology, Plugging Sockets into the Topology, Invalid Combinations starting before server node, Plugging Sockets into the Topology clocks, portable, Features of a Higher-Level API Clone pattern, Reliable Publish-Subscribe (Clone Pattern)–Building a Multithreaded Stack and API, Reliable Publish-Subscribe (Clone Pattern), Centralized Versus Decentralized, Representing State as Key-Value Pairs–Representing State as Key-Value Pairs, Getting an Out-of-Band Snapshot–Getting an Out-of-Band Snapshot, Republishing Updates from Clients–Republishing Updates from Clients, Working with Subtrees–Working with Subtrees, Ephemeral Values–Ephemeral Values, Using a Reactor–Using a Reactor, Adding the Binary Star Pattern for Reliability–Adding the Binary Star Pattern for Reliability, The Clustered Hashmap Protocol–Security, Building a Multithreaded Stack and API–Building a Multithreaded Stack and API adding Binary Star pattern to, Adding the Binary Star Pattern for Reliability–Adding the Binary Star Pattern for Reliability central server for, Centralized Versus Decentralized Clustered Hashmap Protocol for, The Clustered Hashmap Protocol–Security ephemeral values with, Ephemeral Values–Ephemeral Values multithreaded stack for, Building a Multithreaded Stack and API–Building a Multithreaded Stack and API reactor with, Using a Reactor–Using a Reactor requirements for, Reliable Publish-Subscribe (Clone Pattern) state representation, Representing State as Key-Value Pairs–Representing State as Key-Value Pairs state snapshots, Getting an Out-of-Band Snapshot–Getting an Out-of-Band Snapshot state subtrees, Working with Subtrees–Working with Subtrees state updates from clients, Republishing Updates from Clients–Republishing Updates from Clients cloud computing example, Worked Example: Inter-Broker Routing (see Inter-Broker Routing example) Clustered Hashmap Protocol (CHP), The Clustered Hashmap Protocol COD (Complexity-Oriented Design), Complexity-Oriented Design–Complexity-Oriented Design code examples, Using the Code Examples, Using the Code Examples, Using the Code Examples, Using the Code Examples, Using the Code Examples, Getting the Examples, Getting the Examples, Getting the Examples, Getting the Examples, Ask and Ye Shall Receive–Ask and Ye Shall Receive, Getting the Message Out–Getting the Message Out, Divide and Conquer–Divide and Conquer, Handling Multiple Sockets–Handling Multiple Sockets, Shared Queue (DEALER and ROUTER Sockets)–ØMQ’s Built-in Proxy Function, Transport Bridging–Transport Bridging, Handling Errors and ETERM–Handling Errors and ETERM, Multithreading with ØMQ–Multithreading with ØMQ, Signaling Between Threads (PAIR Sockets)–Signaling Between Threads (PAIR Sockets), Node Coordination–Node Coordination, A Load-Balancing Message Broker–A Load-Balancing Message Broker, Worked Example: Inter-Broker Routing, On Assertions, How This Book Happened–Removing Friction, Licensing (see also patterns) creation of, How This Book Happened–Removing Friction Git repository for, Getting the Examples Hello World, Ask and Ye Shall Receive–Ask and Ye Shall Receive Inter-Broker Routing example, Worked Example: Inter-Broker Routing (see Inter-Broker Routing example) licensing for, Licensing licensing of, Using the Code Examples, Getting the Examples Load-Balancing Message Broker, A Load-Balancing Message Broker–A Load-Balancing Message Broker Multiple Socket Reader/Poller, Handling Multiple Sockets–Handling Multiple Sockets Multithreaded Hello World, Multithreading with ØMQ–Multithreading with ØMQ Multithreaded Relay, Signaling Between Threads (PAIR Sockets)–Signaling Between Threads (PAIR Sockets) Parallel Task Ventilator, Divide and Conquer–Divide and Conquer, Handling Errors and ETERM–Handling Errors and ETERM permission to use, Using the Code Examples Request-Reply Broker, Shared Queue (DEALER and ROUTER Sockets)–ØMQ’s Built-in Proxy Function Synchronized Publisher, Node Coordination–Node Coordination translations of, Using the Code Examples, Getting the Examples Weather Update Proxy, Transport Bridging–Transport Bridging Weather Update Server, Getting the Message Out–Getting the Message Out website for, Using the Code Examples Zyre project, On Assertions (see Zyre project) code generation, Code Generation–Code Generation Collective Code Construction Contract, The ØMQ Process: C4 (see C4 contract) collector, Invalid Combinations (see server node) community, The ØMQ Community–Architecture of the ØMQ Community, The ØMQ Community, The ØMQ Community, Architecture of the ØMQ Community–Architecture of the ØMQ Community, Architecture of the ØMQ Community, How to Make Really Large Architectures–Care and Feeding, The Contract–The Contract, The Process–Care and Feeding, Care and Feeding, The ØMQ Process: C4–Evolution of Public Contracts, Licensing and Ownership, A Real-Life Example–A Real-Life Example, Burnout–Burnout building and maintaining, The Process–Care and Feeding burnout, reducing risk of, Burnout–Burnout C4 contract, The ØMQ Community, The ØMQ Process: C4–Evolution of Public Contracts example of, A Real-Life Example–A Real-Life Example iMatix’s role in, Architecture of the ØMQ Community licensing, The Contract–The Contract, Care and Feeding, Licensing and Ownership open source model used by ZeroMQ, The ØMQ Community software architecture guidelines, How to Make Really Large Architectures–Care and Feeding structure of, Architecture of the ØMQ Community–Architecture of the ØMQ Community Complexity-Oriented Design (COD), Complexity-Oriented Design–Complexity-Oriented Design connectedness of software, Fixing the World–Fixing the World connecting, Invalid Combinations (see client node) connections, Plugging Sockets into the Topology–Plugging Sockets into the Topology, Plugging Sockets into the Topology (see also client node) transports for, Plugging Sockets into the Topology Constant Gardner role, The Constant Gardener contact information for this book, How to Contact Us context, Getting the Context Right, Getting the Context Right–Making a Clean Exit, Getting the Context Right, Making a Clean Exit, Upgrading from ØMQ v2.2 to ØMQ v3.2, Upgrading from ØMQ v2.2 to ØMQ v3.2, I/O Threads, Handling Errors and ETERM, Multithreading with ØMQ, Signaling Between Threads (PAIR Sockets) adding threads to, I/O Threads best practices for, Getting the Context Right–Making a Clean Exit configuring, Upgrading from ØMQ v2.2 to ØMQ v3.2 creating, Getting the Context Right destroying, Getting the Context Right, Making a Clean Exit, Handling Errors and ETERM monitoring, Upgrading from ØMQ v2.2 to ØMQ v3.2 as threadsafe, Multithreading with ØMQ, Signaling Between Threads (PAIR Sockets) contracts, Contracts and Protocols, The ØMQ Community, The ØMQ Process: C4–Evolution of Public Contracts, Step 3: Decide on the Contracts, Step 3: Decide on the Contracts, Step 3: Decide on the Contracts, Unprotocols–Error handling APIs as, Step 3: Decide on the Contracts C4 contract, The ØMQ Community, The ØMQ Process: C4–Evolution of Public Contracts unprotocols as, Step 3: Decide on the Contracts, Unprotocols–Error handling contributors to this book, Tales from Out There–Vadim Shalts’s Story conventions used in this book, Conventions Used in This Book cooperative discovery, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts Cost Gravity, A Framework for Distributed Computing creation of this book, How This Book Came to Be–How This Book Came to Be, How This Book Happened–Removing Friction Ctrl-C (SIGINT), handling, Handling Interrupt Signals–Handling Interrupt Signals, Features of a Higher-Level API, The CZMQ High-Level API, The CZMQ High-Level API, The CZMQ High-Level API CZMQ API, The CZMQ High-Level API–The CZMQ High-Level API D data serialization, Serializing Your Data (see serialization of data) DEALER and DEALER combination, The DEALER to DEALER Combination, The Asynchronous Client/Server Pattern DEALER and REP combination, The DEALER to REP Combination DEALER and ROUTER combination, The DEALER to ROUTER Combination, ROUTER Broker and DEALER Workers–A Load-Balancing Message Broker, The Asynchronous Client/Server Pattern–The Asynchronous Client/Server Pattern (see also ROUTER-DEALER proxy) asynchronous client/server pattern using, The Asynchronous Client/Server Pattern–The Asynchronous Client/Server Pattern load balancing using, ROUTER Broker and DEALER Workers–A Load-Balancing Message Broker DEALER socket, Messaging Patterns, Shared Queue (DEALER and ROUTER Sockets), Recap of Request-Reply Sockets, Request-Reply Combinations–The ROUTER to ROUTER Combination (see also ROUTER-DEALER proxy) design models, The Tale of Two Bridges–Simplicity-Oriented Design, Trash-Oriented Design–Trash-Oriented Design, Complexity-Oriented Design–Complexity-Oriented Design COD (Complexity-Oriented Design), Complexity-Oriented Design–Complexity-Oriented Design TOD (Trash-Oriented Design), Trash-Oriented Design–Trash-Oriented Design Digital Standards Organization (Digistan), How to Make Really Large Architectures disconnected network, asynchronous, Disconnected Reliability (Titanic Pattern)–Disconnected Reliability (Titanic Pattern) disconnected TCP transport, Unicast Transports (see tcp transport) discovery, Discovery–More About UDP, Preemptive Discovery over Raw Sockets–Preemptive Discovery over Raw Sockets, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts, Multiple Nodes on One Device, Designing the API–Designing the API, More About UDP–More About UDP API for, Designing the API–Designing the API cooperative discovery, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts preemptive discovery, Preemptive Discovery over Raw Sockets–Preemptive Discovery over Raw Sockets testing with multiple nodes per device, Multiple Nodes on One Device UDP for, More About UDP–More About UDP distributed computing, A Framework for Distributed Computing–Design for the Real World, Discovery–More About UDP, Preemptive Discovery over Raw Sockets–Preemptive Discovery over Raw Sockets, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts, Multiple Nodes on One Device, Designing the API–Designing the API, Spinning Off a Library Project, Distributed Logging and Monitoring–Binary Logging Protocol discovery, Discovery–More About UDP, Preemptive Discovery over Raw Sockets–Preemptive Discovery over Raw Sockets, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts, Multiple Nodes on One Device, Designing the API–Designing the API API for, Designing the API–Designing the API cooperative discovery, Cooperative Discovery Using UDP Broadcasts–Cooperative Discovery Using UDP Broadcasts preemptive discovery, Preemptive Discovery over Raw Sockets–Preemptive Discovery over Raw Sockets testing with multiple nodes per device, Multiple Nodes on One Device logging and monitoring for, Distributed Logging and Monitoring–Binary Logging Protocol Zyre project for, Spinning Off a Library Project (see Zyre project) dynamic discovery, The Dynamic Discovery Problem–The Dynamic Discovery Problem E EAGAIN return code, Handling Errors and ETERM, Dealing with Blocked Peers Earth and Sky role, The Earth and Sky EFSM error code, The REQ to REP Combination, Client-Side Reliability (Lazy Pirate Pattern) EHOSTUNREACH error code, ROUTER Error Handling EINTR return code, Handling Interrupt Signals envelopes, Pub-Sub Message Envelopes–Pub-Sub Message Envelopes, The Request-Reply Mechanisms–Recap of Request-Reply Sockets ephemeral values, Ephemeral Values–Ephemeral Values error handling, Handling Errors and ETERM–Handling Errors and ETERM, ROUTER Error Handling, Error handling with Cheap and Nasty pattern, Error handling by ROUTER socket, ROUTER Error Handling Espresso pattern, Pub-Sub Tracing (Espresso Pattern)–Pub-Sub Tracing (Espresso Pattern) ETERM return code, Handling Errors and ETERM examples, Sockets and Patterns (see code examples) exclusive pair pattern, Messaging Patterns exiting, best practices for, Making a Clean Exit–Making a Clean Exit F failure, causes of, What Is “Reliability”?


pages: 413 words: 119,587

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


A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, augmented reality, autonomous vehicles, 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 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, 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 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, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, 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

(Photo courtesy of Yann LeCun) This time they had something else going for them—the pace of computing power had accelerated, making it possible to build neural networks of vast scale, processing data sets orders of magnitude larger than before. It had taken almost a decade, but by then the progress, power, and value of the neural network techniques was indisputable. In addition to raw computing power, the other missing ingredient had been large data sets to use to train the networks. That would change rapidly with the emergence of the global Internet, making possible a new style of centralized computing power—cloud computing—as well as the possibility of connecting that capacity to billions of mobile sensing and computing systems in the form of smartphones. Now the neural networks could be easily trained on millions of digital images or speech samples readily available via the network. As the success of their techniques became more apparent, Hinton began to receive invitations from different computer companies all looking for ways to increase the accuracy of a wide variety of consumer-oriented artificial intelligence services—speech recognition, machine vision and object recognition, face detection, translation and conversational systems.

The Siri project didn’t feed into the “eye candy” focus at Apple—the detailed attention of software and hardware design that literally defined Apple as a company—but was instead about providing customers with reliable and invisible software that worked well. But many engineers in the software development organization at Apple thought that if Steve—and later on one of his top lieutenants, Scott Forstall—didn’t say “make it happen,” they didn’t need to work on that project. After all, Apple was not recognized as a company that developed cloud-computing services. Why reinvent the wheel? An assistant or simply voice control? After all, how much difference would it really make? In fact, people were dying while reading email and “driving while intexticated,” so presenting drivers with the ability to use their phones safely while driving made a tremendous difference. When Apple’s project management bureaucracy balked at the idea of including the ability to send a hands-free text message in the first version of the software, Gruber, who had taken the role of a free-floating technical contributor after the acquisition, said he would take personal responsibility for completing the project in time for the initial Apple Siri launch.


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Digital Wars: Apple, Google, Microsoft and the Battle for the Internet by Charles Arthur