Chapter 2: Google’s System of the World
1. Stephenson borrowed the title from Newton himself, who titled the third volume of his Principia, “De mundi systemate.”
2. D. T. Whiteside, The Mathematical Papers of Isaac Newton, (Cambridge: Cambridge University Press, 2008), xxix.
3. Franz Lieber, “Appointment in Tomorrow,” Galaxy Science Fiction, July 1951.
4. For my explorations of this theory see Knowledge and Power (2013), expanded in The Scandal of Money (2016).
5. Nathan K. Lewis, “The World’s Experience with Gold Standard Systems,” Chapter 5 in Gold: The Monetary Polaris (New Berlin, N.Y.: Canyon Maple Publishing, 2013).
6. Ibid.
7. David Hilbert, quotes, Wikipedia entry.
8. Gregory J. Chaitin, Thinking about Gödel and Turing: Essays on Complexity, 1970–2007 (Hackensack, N.J.: World Scientific Publishing Co., 2007), 281 and passim.
9. William Briggs, Uncertainty: The Soul of Modeling, Probability and Statistics (Switzerland: Springer International Publishing, 2016), 32.
10. Hubert Yockey, Information Theory, Evolution, and the Origin of Life (New York: Cambridge University Press, 2005). Information Theory and Molecular Biology (1992).
11. George Dyson, Turing’s Cathedral: The Origins of the Digital Universe (New York: Pantheon Books, 2012), 252. He cites Turing’s dissertation under Alonzo Church at Princeton: Alan Turing, “Systems of Logic Based on Ordinals”, 161.
12. Werner Heisenberg, who had introduced the uncertainty principle to physics in 1927, was in the audience at Gödel’s introduction of incompleteness in 1930 but failed to appreciate it as a generalization of his own insight. Later Gödel famously pushed the physicist John Wheeler out of his office when Wheeler suggested that there might be a connection between the uncertainty principle in physics and the apparently kindred principle in computing.
13. Chaitin, Proving Darwin: Making Biology Mathematical (New York: Pantheon Books, 2012), 212. Like Hubert Yockey, Chaitin proves that Darwin is unprovable but mathematically intelligible. See also, Chaitin, Thinking about Gödel and Turing, 333. “The number omega is the probability that a self-contained computer program, chosen at random . . . will eventually stop, rather than continue calculating forever. . . . Surprisingly enough, the precise numerical value of omega is uncomputable, in fact, irreducibly complex. [This] can be interpreted pessimistically, as indicating there are limits to human knowledge. The optimistic interpretation, which I prefer, is that omega shows that one cannot do mathematics mechanically and that intuition and creativity are essential. Indeed, in a sense omega is the crystalized, concentrated essence of mathematical creativity.”
Chapter 3: Google’s Roots and Religions
1. http://citeseer.ist.psu.edu/stats/articles. I counted the Stanford and Google papers.
2. A lucid explanation of PageRank and search technology is John MacCormick, Nine Algorithms that Changed the Future: The Ingenious Ideas that Drive Today’s Computers (Princeton: Princeton University Press, 2012), 10–37.
3. Larry Page, hey, virtually all his quotes are accessible on Google!
4. David Gelernter, Mirror Worlds (New York: Oxford University Press, 1992).
5. Page, ibid.
6. If you prefer the text version beyond all the Google search resources on the saga of its inventors and founders, it is lavishly there in Steven Levy’s In the Plex: How Google Thinks, Works, and Shapes our Lives (New York: Simon & Schuster, 2011), or in the silken New Yorker prose of media-savvy Ken Auletta, Googled: The End of the World as We Know It (New York: Penguin Books, 2010). The Olympian view from on high is expounded by Eric Schmidt and Jonathan Rosenberg, with a foreword by Larry Page, How Google Works (New York: Hachette, 2014).
7. Fred Turner, Burning Man at Google: A Cultural Infrastructure for New Media Production (Sage Journal, 2009).
8. The muckraking, litigious, and eloquent Scott Cleland and the tech-savvy Ira Brodsky unleash the targeted-drone version of anti-Google history: Search & Destroy: Why You Can’t Trust Google Inc. (St. Louis: Telescope Books, 2011). I disagree with their animus and their belief in an antitrust legal remedy for Google, but the book is full of trenchant observations about Google’s strategy and business.
9. Cleland, ibid., 82.
Chapter 4: End of the Free World
1. Jerry Bowyer, “Will Bitcoin Kill Don Draper? The Real End of an Era,” Forbes.com, May 31, 2015.
2. Douglas Edwards, I’m Feeling Lucky: Confessions of Google Employee Number 59 (Boston: Houghton Mifflin Harcourt, 2011), 11.
3. Jeremy Rifkin, The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism (New York: St. Martin’s Press, 2016). For the speech at Google, see https://www.youtube.com/watch?v=5-iDUcETjvo
4. Edwards, xi, Introduction.
5. Jonathan Taplin, Move Fast and Break Things: How Facebook, Google and Amazon Cornered Culture and Undermined Democracy (New York: Little Brown and Company, 2017), 126 and passim.
6. Daniel Colin James, “This Is How Google Collapsed”, Hacker Noon: Where hackers start their afternoons, April 27, 2017. https://hackernoon.com/how-google-collapsed-b6ffa82198ee
7. Ibid. Most of these numbers come from the Daniel Colin James blog.
Chapter 5: Ten Laws of the Cryptocosm
1. “Safety Last” is the principle of Ethernet inventor Bob Metcalfe.
2. The source of the image of M&A unicorns and IPO gazelles is the financier-philosopher William Walton.
Chapter 6: Google’s Datacenter Coup
1. George Gilder, “The Information Factories,” Wired, October 1, 2006. I originally made this trip as a contributing editor of Wired and much of the prose in the chapter, including the opening paragraphs, originally appeared in Wired. However, all the data and themes were updated and reinterpreted twelve years later for this book.
2. The Dalles is only a piece of Google’s global data center empire, which comprises some two million servers at fifteen sites from Singapore to Quilicura, Chile.
3. Jaron Lanier, Who Owns the Future? (New York: Simon & Schuster, 2013), 53 and passim.
4. Gordon Bell, “Bell’s Law for the Birth and Death of Computer Classes,” Communications of the ACM. 51 (1), January 2008: 86–94.
5. Described by Tracy Kidder in his masterpiece, The Soul of a New Machine (Boston: Little Brown & Company, 1981). No one has captured so vividly the saga of designing new computers and software.
6. Urs Hölzle, speech to the Optical Fiber Conference in Los Angeles, CA, April 11, 2017. This and many other Hölzle speeches are available on YouTube, and his broader analysis, with Luiz Barroso and Jimmy Clidaras, was expounded in The Datacenter as a Computer (San Raphael, CA: Morgan and Claypool Publishers, 2013).
7. “The Information Factories,” Wired, Ibid. see note 1.
8. Andy Bectolsheim, ibid., and as updated at Arista at Linley Group’s “Cloud Hardware Conference,” February 8, 2017.
Chapter 7: Dally’s Parallel Paradigm
1. This ride to the future with Bill Dally, on August 25, 2017, followed a long interview at Nvidia in Mountain View, following interviews in years gone by at Caltech and at MIT, and close perusal of his book with Brian Towles, Principles and Practices of Interconnection Networks (San Francisco: Morgan Kauffmann Publishers, 2004), and articles by Dally and his colleagues, including “The GPU Computing Era,” with John Nickolls, also at Nvidia, in IEEE Micro, March–April 2010, and “Scaling the Power Wall: A Path to Exascale,” by Dally and eleven colleagues, IEEE Micro, September–October 2011. Nvidia turns out to have accomplished most of what it projected in these early publications. Dally has long influenced me but is obviously not responsible for any of my views expressed in this chapter or elsewhere.
2. Nick Tredennick and Brion Shimamoto, “Embedded Systems and the Microprocessor,” Microprocessor Report (Cahners) April 24, 2000. He als
o used to joke about the coveted “zero-sales” segment—chips made for aero-space and other markets with unit demand in the hundreds of chips, or less.
3. HC03 (1991) August 26–27. Hot Chips: A Symposium on High Performance Chips, sponsored by IEEE Technical Committee on Microprocessors and Microcomputers in cooperation with ACM-SIGARTH. https://www.hotchips.org/archives/1990s/hc03/. Held at the Stanford Memorial Auditorium, everyone was there, from conference chairmen John Hennessy and Forrest Baskett (Silicon Graphics) to Dally and Tom Knight of MIT, to a battalion from Texas Instruments, and David Perlmutter and Michael Kagan all the way from Intel Israel to tout the ill-fated i860 “very long instruction word (VLIW)” chip that evolved into the also ill-fated Itanium.
4. A pithy introduction to the technology of machine learning is Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Tsuan-Tien Lin, Learning from Data: A Short Course (AMLbook.com). Abu-Mostafa introduced me to his mastery of machine learning in a fascinating dinner at the Caltech Athenaeum in February 2013.
5. John Markoff, “How Many Computers to Identify a Cat? 16,000,” New York Times, June 25, 2012.
6. Claude Elwood Shannon, “A Mathematical Theory of Communication,” published in the Bell Systems Technical Journal in October 1948 and available in N. J. A. Sloane, Aaron D. Wyner, edits, Shannon Collected Papers (Piscataway, N.J.: IEEE Press, 1993), section 12: “Equivocation and Channel Capacity,” 33.
7. Thiel continued his critique in his revelatory book Zero to One: Notes on Startups, or How to Build the Future (New York: Crown, 2014).
8. Talk of the Town, New Yorker, December 6, 1958, https://www.newyorker.com/magazine/1958/12/06/rival-2
Chapter 8: Markov and Midas
1. Lawrence Rabiner, “Hidden Markov Models,” Proceedings of the IEEE, February 1989. This paper has become the sixth-most-cited in the entire corpus of computer science.
2. Philipp von Hilgers and Amy N. Langville, “The Five Greatest Applications of Markov Chains,” in Amy N. Langville and William J. Stewart, eds., Proceedings of the Markov Anniversary Meeting (Altadena, Calif.: Boson Books, 2006), 156–57.
3. Claude Elwood Shannon, “A Mathematical Theory of Communications” in The Bell System Technical Journal, October 1948, section 4, “Graphical Representation of a Markoff Process,” in Collected Papers (Piscataway, N.J.: IEEE Press, 1993), 15. “Stochastic processes of the type described above (“The Discrete Noiseless Channel”) are known mathematically as discrete Markov processes. . . . [A] discrete [information] source, for our purposes can be considered to be represented by a Markoff process. The general case can be described as follows: There exist a finite number of possible ‘states’ of a system. . . . In addition, there is a set of transition probabilities; . . . the probability that if the system is in state Si it will next go to state Sj . . . [W]e assume a letter is produced for each transition. . . . The states will correspond to the ‘residue of influence’ from preceding letters.”
4. Ray Kurzweil, How to Create a Mind: The Secret of Human Thought Revealed (New York: Penguin Books, 2012), 143. Kurzweil explains that Hierarchical Hidden Markov Models and their kin are based, like nearly all machine learning, on hierarchies of linear sequences with weights and adaptive learning in the links based on immersion in data.
5. Amy Langville and Carl D. Meyer, Google’s Page Rank and Beyond: The Science of Search Engine Rankings (Princeton: Princeton University Press, 2006, 2011).
6. Kurzweil, How to Creat a Mind, 153.
7. George Gilder, Microcosm: The Quantum Revolution in Economics and Technology (New York: Simon & Schuster, 1989), 262–89.
8. Jaron Lanier, Who Owns the Future (New York: Simon & Schuster, 2013), xxv.
9. Ibid.
10. Ibid., xxiii.
11. Hal Lux, “The Secret World of Jim Simons,” Institutional Investor, November 2000, https://www.institutionalinvestor.com/article/b151340bp779jn/the-secret-world-of-jim-simons
12. Robert P. Crease, The Prism and the Pendulum: The Ten Most Beautiful Experiments in Science (New York: Random House, 2004), 59–76, Chapter Four: “Newton’s Decomposition of Light with Prisms.”
13. Lanier, Who Owns the Future, xxvi.
14. Ibid., 153.
Chapter 9: Life 3.0
1. Max Tegmark, Life 3.0: Being Human in the Age of Artificial Intelligence (New York: Alfred A. Knopf, 2017). He describes the saga of organizing and funding the conference in an Epilogue, “The Tale of the FLI [Future of Life Institute] Team,” 316–35.
2. Tegmark, Life 3.0, 4.
3. Ibid., 4.
4. Musk on AI: https://www.cnbc.com/2018/03/13/elon-musk-at-sxsw-a-i-is-more-dangerous-than-nuclear-weapons.html.
5. Hawking on AI. It gave him a voice and he used it to warn against AI. https://qz.com/1231092/ai-gave-stephen-hawking-a-voice-and-he-used-it-to-warn-us-against-ai/
6. Ray Kurzweil in speeches popularized the fable of the emperor of China and the inventor of chess. The emperor was so grateful for the invention that he offered the inventor anything he asked. The inventor said, “Just a grain of rice on the first square of the chessboard . . . and a doubling of the grains on each subsequent square of the 64.” Not a mathematician, the emperor readily agreed to the exponential process. To produce 264 (minus 1) grains, the emperor would have to award the inventor roughly eighteen million trillion grains, or all the rice ever grown on earth times some factor. As Kurzweil would point out, the emperor’s troubles would begin when the doubling moved to the second half of the chessboard. Kurzweil would speculate on two possible endings: one, the inventor takes over the kingdom; two, the inventor is decapitated. The lesson for inventors is keep an eye on the emperor.
7. Tegmark, Life 3.0, 158.
8. Ibid., 147.
9. Ibid., 245.
10. Ray Kurzweil, editor, Kurzweil.ai.net, with the AI standing for Accelerating Intelligence.
11. G. K. Chesterton, Tremendous Trifles (Beaconsfield, England: Darwen Finlayson, 1968), 55.
12. Jaron Lanier, You Are Not a Gadget (New York: Vintage Books, 2010), 17.
13. Charles Sanders Peirce, Chance, Love and Logic: Philosophical Essays, edited with an introduction by Morris R. Cohen and a supplemental essay by John Dewey (New York: Barnes & Noble, 1923). A luminous introduction to Peirce is Josiah Lee Auspitz, “The Wasp Leaves the Bottle,” The American Scholar, 2001, 602–19. Applying Peirce to Information Systems and Software is E. T. Nozawa, “Peircean Semeiotic: A New Engineering Paradigm for Automatic and Adaptive Intelligent Systems Design” (Marietta, Georgia: Lockheed Martin Aeronautics), which shows that “Peircean Semeiotic [the science of signs and symbols] has a very revolutionary role to play in the advanced development of Artificial Intelligence, Cognitive Science,” and other information sciences.
14. Michael Denton, Nature’s Destiny: How the Laws of Biology Reveal Purpose in the Universe (New York: The Free Press, 1998), 324–27 in Chapter 14: “The Dream of Asilomar.”
15. Leigh Cuen, “What Really Is Ethereum? Co-Founder Joe Lubin Explains,” International Business Times, August 24, 2017, http://www.ibtimes.com/what-really-ethereum-co-founder-joe-lubin-explains-2578228.
16. Klint Finley, “Out in the Open: Teenage Hacker Transforms Web into One Giant Bitcoin Network,” Wired, 01/27/14, https://www.wired.com/2014/01/ethereum/.
Chapter 10: 1517
1. The Thiel Fellowship website, About the Fellowship, http://thielfellowship.org/about/.
2. “In 2012, I entered the University of Waterloo; in 2013 I realized that crypto projects were taking up 30h/week of my time, so I dropped out. I went around the world, explored many crypto projects, and finally realized that they were all too concerned about specific applications and not being sufficiently general—hence the birth of Ethereum, which has been taking up my life ever since. . . . ” Vitalik Buterin, https://about.me/vitalik_buterin.
3. 1517 Fund website, About, http://www.1517fund.com/thesis/.
4. Pony Tracks “weaponry;” Bruce Newman, “Tanks for the Memories: Historic Collection of Military Might Auctioned for More Than $10 Million” Mercury News, July 13, 2014, https://www.mercurynews.com/2014/07/13/tanks-for-the-memories-historic-collection-of-military-might-auctioned-for-more-than-10-million/.
Chapter 11: The Heist
1. Hal Finney posted this response to Satoshi on January 16, 2009, on what is now called the Bitcoin Forum.
2. Finney, ibid.
3. John Mauldin and Jonathan Tepper, Code Red: How to Protect Your Savings from the Coming Crisis (Hoboken, N.J.: John Wiley & Sons, 2014).
4. Ayn Rand, Atlas Shrugged (New York: Signet, 1957).
5. Nermin Hajdarbegovic, “Lingusitic Researchers Name Nick Szabo as Author of the Bitcoin Whitepaper,” Coindesk, April 16, 2014. He pointed to a team of forensic linguistic experts at Ashton University in Birmingham, England, led by Professor Jack Grieve. The story also cites the linguistic researcher Skye Grey as coming to the same conclusion in December 2013. Michael Chon of Booz Allen Hamilton, however, published a paper on December 26, 2017, invoking an array of classification algorithms, that pointed to Szabo as author of the Whitepaper, but fingered Ian Grigg, a Craig Wright associate, as the author of Satoshi’s emails. Grigg has named Wright and Kleiman as key members of the Satoshi team. Regardless of Szabo’s specific role, he is the most original and interesting thinker in the bunch, and his bitgold paper is prophetic.
6. George Gilder, Telecosm: The World after Bandwidth Abundance (New York: Simon & Schuster, 2000), 116–17. This Marc Andreessen riff was first published in Forbes ASAP as “The Coming Software Shift” and republished by Rich Karlgaard in 1996 under the Forbes American Heritage label in a collection of my ASAP articles entitled Telecosm.
7. Ira Stoll, Silicon Snake Oil: Second Thoughts on the Information Highway (New York: Doubleday, 1995).
8. Marc Andreessen, “Why Bitcoin Matters,” New York Times, January 21, 2014.
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