Y Combinator

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pages: 332 words: 97,325

The Launch Pad: Inside Y Combinator, Silicon Valley's Most Exclusive School for Startups by Randall Stross

affirmative action, Airbnb, AltaVista, always be closing, Amazon Mechanical Turk, Amazon Web Services, barriers to entry, Ben Horowitz, Burning Man, business cycle, California gold rush, call centre, cloud computing, crowdsourcing, don't be evil, Elon Musk, high net worth, index fund, inventory management, John Markoff, Justin.tv, Lean Startup, Marc Andreessen, Mark Zuckerberg, medical residency, Menlo Park, Minecraft, minimum viable product, Paul Buchheit, Paul Graham, Peter Thiel, QR code, Richard Feynman, Richard Florida, ride hailing / ride sharing, Sam Altman, Sand Hill Road, side project, Silicon Valley, Silicon Valley startup, Skype, social graph, software is eating the world, South of Market, San Francisco, speech recognition, Stanford marshmallow experiment, Startup school, stealth mode startup, Steve Jobs, Steve Wozniak, Steven Levy, TaskRabbit, transaction costs, Y Combinator

Thank You Everyone Who Helped,” HT blog, March 27, 2008, http://blog.harjtaggar.com/auctomatic-is-acquired-thank-you-everyone-who. 23. HT answering Quora question: “What Does Harjeet Taggar’s Role at Y Combinator Entail, and How Did He Become Partner at 25?” Quora, September 25, 2011, www.quora.com/What-does-Harjeet-Taggars-role-at-Y-Combinator-entail-and-how-did-he-become-partner-at-25. 24. “Y Combinator Announces Two New Partners, Paul Buchheit and Harj Taggar,” YC Posterous, November 12, 2010, http://ycombinator.posterous.com/y-combinator-announces-two-new-partners-paul. 25. HT, “I’m a Partner at Y Combinator.” 26. “Welcome Sam, Garry, Emmett, and Justin,” YC Posterous, June 18, 2011, http://ycombinator.posterous.com/welcome-sam-garry-emmett-and-justin. 27. The official announcement of Aaron Iba’s appointment and Garry Tan’s promotion to full-time partner was not made until the winter 2012 batch had started.

It would have been more difficult to convince YC applicants of the desirability of moving to where YC was had it stayed where it started, in Cambridge. But after the first YC batch had finished in August 2005, Graham decided it would be a good idea to plant the flag in Silicon Valley. He expected that other seed funds would pop up and copy the Y Combinator model, and he didn’t want to leave open an opportunity for someone to come along and say, “We’re the Y Combinator of Silicon Valley.” He wanted Y Combinator to be the Y Combinator of Silicon Valley. He and Livingston planned to move out to the Bay Area for the next batch, in winter 2006, and then alternate, running a summer batch in Cambridge and a winter one in the Valley. They would need one room large enough to seat everyone in the batch for the weekly dinner, but only for a few months every year.

Graham and his partners did not have room for their own offices at YC. They commandeered a tabletop in the main hall when they needed to use their laptops. Y Combinator fit the definition of accelerator, but Graham was fussily averse to calling YC anything other than plain “seed fund.” TechStars played up its own openness, contrasting it with Y Combinator, which did not disclose information about whom it funded and how they were doing. “At TechStars, we believe in full transparency,” said the challenger, listing every company in every batch, how much capital each had raised, and whether the company remains active, has been acquired, or has failed. Y Combinator adopted the position that it could not give a full accounting of each batch because doing so would entail the release of information that at least some of the startups had not yet released.


pages: 216 words: 61,061

Without Their Permission: How the 21st Century Will Be Made, Not Managed by Alexis Ohanian

Airbnb, barriers to entry, carbon-based life, cloud computing, crowdsourcing, en.wikipedia.org, Hans Rosling, hiring and firing, Internet Archive, Justin.tv, Kickstarter, Marc Andreessen, Mark Zuckerberg, means of production, Menlo Park, minimum viable product, Occupy movement, Paul Graham, Silicon Valley, Skype, slashdot, social web, software is eating the world, Startup school, Tony Hsieh, unpaid internship, Y Combinator

Traction starts with a product people want; as word spreads, you’ll start seeing the week-over-week and month-over-month growth that gets investors pulling out their checkbooks and briefcases full of money.4 Investment Summer Camp for Startups There’s an unassuming, slightly bizarre-looking building located at 135 Garden Street in Cambridge, Massachusetts. It’s the original home of Y Combinator. When Paul Graham, Jessica Livingston, Dr. Robert Morris, and Trevor Blackwell decided to start a new kind of seed-stage venture capital firm, not many people understood it, let alone expected it to revolutionize tech investment as it has. Today there are scores of Y Combinator clones all over the world, such as TechStars, 500 Startups, and Seedcamp. And I was lucky enough to have been in that first class of founders who showed up for what was then called the Summer Founders Program. That first class at Y Combinator may have been a special sample of fortunate founders, but the group itself had a range of personalities. There was the braggart, the teacher’s pet, even the condescending misanthrope.

He’s my personal lawyer to this day.6 All of us were there that first summer to learn as much as we could, both from the experts who visited every week for special off-the-record talks and Q&A and from each other. Over time, that network of Y Combinator guests and alums has become one of its strongest assets. At the time, however, not even Paul and the other founders of Y Combinator were aware of the value in the network they were creating. As more founders went through the program, the previous participants felt honor-bound to assist them, a tradition that continues to this day. Encounter a problem you’ve never experienced before? There’s probably someone in the network who has—just ask. It’s been referred to as the YC mafia. But it’s not exclusive to Y Combinator. The most healthy startup communities have a network of founders who are genuinely interested in helping one another. I see this today throughout the New York tech community.

The phrase “Make something people want” was emblazoned on the shirts each one of us received at the end of that first Y Combinator dinner. Jessica Livingston, one of the YC founders, illustrated this brilliantly in a fundamental way when she taught me people won’t wear uncomfortable swag (remember the previous chapter!). As founders, we’re never to forget this phrase comfortably adorned on our chests, which serves as a mantra of sorts for Y Combinator. Startups will never succeed unless they make something people want. It’s a lesson I come back to time and time again. There’s Nothing Fun About Funding Unless you get incredibly lucky (remember, there are already many factors going against you), you’ll need to have at least built something people want before you can get your first round of funding. The application process varies, but most accelerators follow Y Combinator’s lead and start with a written application (submitted online, of course) followed by offers for in-person interviews.


We Are the Nerds: The Birth and Tumultuous Life of Reddit, the Internet's Culture Laboratory by Christine Lagorio-Chafkin

4chan, Airbnb, Amazon Web Services, Bernie Sanders, big-box store, bitcoin, blockchain, Brewster Kahle, Burning Man, crowdsourcing, cryptocurrency, David Heinemeier Hansson, Donald Trump, East Village, game design, Golden Gate Park, hiring and firing, Internet Archive, Jacob Appelbaum, Jeff Bezos, jimmy wales, Joi Ito, Justin.tv, Kickstarter, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, minimum viable product, natural language processing, Paul Buchheit, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, QR code, recommendation engine, RFID, rolodex, Ruby on Rails, Sam Altman, Sand Hill Road, Saturday Night Live, self-driving car, semantic web, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, Snapchat, social web, South of Market, San Francisco, Startup school, Stephen Hawking, Steve Jobs, Steve Wozniak, technoutopianism, uber lyft, web application, WikiLeaks, Y Combinator

The investment vehicle that would fund the Summer Founders Program soon earned another name: Y Combinator. The name came from an obscure concept in lambda calculus (which uses fixed-point combinators) that allows mathematical equation-writing to achieve something called Curry’s paradox. Put into plain English, a Y combinator might help form a sentence such as, “If this sentence is true, mayonnaise is made from peat moss.” The same way that sentence defeats itself, a Y combinator can show that lambda calculus is an unsound system, by finding inconsistency in mathematical logic. The concept is referenced in certain computer programming styles, and had become something of a hacker inside joke. Learning what the heck a “Y combinator” is would be a little Easter egg to every applicant who Googled it—so much so that for a while YC’s blog included a tagline only a nerd could adore: “Y Combinator: Not your standard fixed-point combinator.”

Four years later, they had an idea for a startup. They were accepted into a summer program that soon would become known as Y Combinator. Over three months, they set out to build “the front page of the Internet.” Courtesy of Jessica Livingston. Y Combinator began in June 2005. Eight groups of young men received a $6,000-per-person stipend for the summer. The group, overseen by Paul Graham (far right) and Jessica Livingston (far left), brought together several soon-to-be well-known tech figures, including Huffman and Ohanian (third and fourth from left), Chris Slowe (fifth from left), Justin Kan (front seated), Aaron Swartz (immediately behind him), and Sam Altman (arms crossed). Courtesy of Kate Courteau. After Y Combinator ended, Aaron Swartz’s company, Infogami, merged with Reddit. Swartz moved into the apartment Huffman, Ohanian, and Slowe, the Harvard graduate student who’d become Reddit’s first employee, shared on Washington Street in Somerville, Massachusetts, carving himself a temporary sleeping nook inside a kitchen cupboard.

Rejected by girls: Alexis Ohanian, Without Their Permission: How the 21st Century Will Be Made, Not Managed (New York: Business Plus, 2013), 21–22. How to Start a Startup an eighty-page thesis: “Our Y Combinator Summer 05 Application,” posted by Alexis Ohanian on November 29, 2010, AlexisOhanian.com. Swartz was pondering: Aaron Swartz, “The Case Against Lawrence Summers,” aaronsw.com, March 9, 2005. “If you want to do it”: Paul Graham, “How to Start a Startup,” essay delivered before the Harvard Computer Society, posted online March 2005. Not Your Standard Fixed-Point Combinator Graham snapped a photo: Paul Graham, “How Y Combinator Started,” blog post on Y Combinator’s former website, March 15, 2012. “How do we even tell people”: Jessica Livingston, Founders at Work: Stories of Startups’ Early Days (New York: Apress, 2007), 448.


pages: 290 words: 87,549

The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions...and Created Plenty of Controversy by Leigh Gallagher

Airbnb, Amazon Web Services, barriers to entry, Ben Horowitz, Bernie Sanders, cloud computing, crowdsourcing, don't be evil, Donald Trump, East Village, Elon Musk, housing crisis, iterative process, Jeff Bezos, Jony Ive, Justin.tv, Lyft, Marc Andreessen, Mark Zuckerberg, medical residency, Menlo Park, Network effects, Paul Buchheit, Paul Graham, performance metric, Peter Thiel, RFID, Sam Altman, Sand Hill Road, Saturday Night Live, sharing economy, side project, Silicon Valley, Silicon Valley startup, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, the payments system, Tony Hsieh, Travis Kalanick, uber lyft, Y Combinator, yield management

One night in November 2008, Chesky and Gebbia were having dinner with Seibel, who suggested that they consider applying to Y Combinator. Chesky took umbrage at the suggestion. Y Combinator was for prelaunch companies. AirBed & Breakfast had already launched—they had customers! They had been written up on TechCrunch! But Seibel delivered the truth that, deep down, they all knew: “Look at you,” he said. “You guys are dying. Do Y Combinator.” The application deadline had passed, but Seibel sent a message to Graham, who said he’d consider them if they got their application in by midnight. They called Blecharczyk in Boston, waking him up at 1 a.m. to ask if they could put his name on the application with them. He hardly remembers agreeing, but he did. They applied, got an interview, and somehow convinced Blecharczyk to come back to San Francisco for it. Y Combinator’s application process is famously brutal; interviews are just ten minutes flat, consisting of Graham and his partners asking rapid-fire questions; no presentations are allowed.

Seibel is now an established entrepreneurial adviser with two major successes under his belt: he and his cofounders sold Twitch (which is what Justin.tv eventually became) to Amazon for $970 million and Socialcam, a video app, to Autodesk for $60 million. But back then he was twenty-five, had only recently become a first-time CEO, and didn’t have much experience. “I wasn’t someone people pitched,” he says. Chesky and Gebbia were the first founders who had ever asked him for advice. But he had just gone through Y Combinator, the prestigious start-up accelerator program cofounded by the entrepreneur and venture capitalist Paul Graham (Seibel is now CEO of the Y Combinator program). Seibel told them he’d help give them counsel, and as they began to devise something more tangible, he could maybe introduce them to some angels. Chesky had no idea what he was talking about (“I’m, like, ‘Oh my god, this guy believes in angels. What the hell?’” he says now). Seibel explained to Chesky that he was referring to angel investors, people who over dinner might write him a check for $20,000.

It was a full-on start-up school, as well known for the access it provided—through dinners, speakers, and the high degree of hand-holding provided by its leaders—as for its specific way of doing things. Its motto, “Make something people want,” originally attributed to Paul Buchheit, the creator of Gmail and now a Y Combinator partner, is one of many YC principles that often run counter to conventional MBA wisdom. Chesky would later say that although he went to RISD, he graduated from the school of Y Combinator. Graham himself has become a Silicon Valley folk hero, a prolific thinker and writer on entrepreneurialism known as much for his wisdom as for his tough-love approach. These days, YC takes on more than a hundred companies each season, but in January 2009, AirBed & Breakfast was one of just sixteen start-ups participating.


pages: 559 words: 155,372

Chaos Monkeys: Obscene Fortune and Random Failure in Silicon Valley by Antonio Garcia Martinez

Airbnb, airport security, always be closing, Amazon Web Services, Burning Man, Celtic Tiger, centralized clearinghouse, cognitive dissonance, collective bargaining, corporate governance, Credit Default Swap, crowdsourcing, death of newspapers, disruptive innovation, drone strike, El Camino Real, Elon Musk, Emanuel Derman, financial independence, global supply chain, Goldman Sachs: Vampire Squid, hive mind, income inequality, information asymmetry, interest rate swap, intermodal, Jeff Bezos, Kickstarter, Malcom McLean invented shipping containers, Marc Andreessen, Mark Zuckerberg, Maui Hawaii, means of production, Menlo Park, minimum viable product, MITM: man-in-the-middle, move fast and break things, move fast and break things, Network effects, orbital mechanics / astrodynamics, Paul Graham, performance metric, Peter Thiel, Ponzi scheme, pre–internet, Ralph Waldo Emerson, random walk, Ruby on Rails, Sam Altman, Sand Hill Road, Scientific racism, second-price auction, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, social web, Socratic dialogue, source of truth, Steve Jobs, telemarketer, undersea cable, urban renewal, Y Combinator, zero-sum game, éminence grise

Getting a first look at a potential Uber or Airbnb is what distinguished a first-class VC from an also-ran. Given Y Combinator’s immense success in drawing the best entrepreneurs, it had a quasi-stranglehold on the best early-stage deal flow in the Valley. And since early-stage deal flow today translated into later-stage deal flow tomorrow, via the follow-on investing phenomena described, Y Combinator was the gatekeeper to the best present and future deals in the Valley. Like control of the water supply in some arid agricultural region, whoever had the most upstream control of the water sluice controlled everything else—which is what Y Combinator’s Demo Day represented. Thus, powerful and haughty VCs who wanted to attend Y Combinator’s showcase pitch event had to kneel and kowtow to a sandal-wearing bear of a man with a distaste for bullshit and a flair for the written word.

§ Venture capitalists (VCs for short) are the bettors at the startup casino, funding startups from the earliest stages, at which investments are the price of a new car or less, to the latest, in which funding rounds can be in the hundreds of millions of dollars. * The bar-code-reading problem circa 2010 was still relatively unsolved. A company named RedLaser would soon do so, and it was almost instantly acquired by eBay. * Little-known fact: Y Combinator alums are the first readers of all Y Combinator applications, and are essentially the first filter. This is the one question I always make it a point to read when reviewing Y Combinator applications. If the answer is left blank, my cursor is already halfway to the No button. If it reads something like “I’d never hack a system or do anything illegal” I hit that No button faster than a Jeopardy contestant buzzes in. * The other star in the startup café firmament is Coupa Cafe in downtown Palo Alto.

Procrastinating on a Monday, I decided to read an essay by Paul Graham. PG, as he’s known to the cognoscenti, founded an online store builder called Viaweb in the early days of the Web, which got bought in the $40 million range in 1997, and eventually became Yahoo Shopping. In his postacquisition freedom, he created one of the more incredible institutions in Silicon Valley: Y Combinator.* Twice a year, every year, Y Combinator accepts a few dozen startup hopefuls into what can only be described as a startup boot camp.† They are given a tiny amount of money and the goal of shipping a product by the end of three months. Some come in with nothing but a few hacked-up lines of code and an idea; some have entire going concerns that have already raised money.‡ Three months later, they all pitch at Demo Day, a major event on the Bay Area’s venture capital calendar.§ PG is the leading apostle, to not say messiah, of the startup gospel, and other than maybe Marc Andreeson, possesses the only prose style among techies that doesn’t trigger a literary gag reflex.


pages: 468 words: 233,091

Founders at Work: Stories of Startups' Early Days by Jessica Livingston

8-hour work day, affirmative action, AltaVista, Apple II, Brewster Kahle, business cycle, business process, Byte Shop, Danny Hillis, David Heinemeier Hansson, don't be evil, fear of failure, financial independence, Firefox, full text search, game design, Googley, HyperCard, illegal immigration, Internet Archive, Jeff Bezos, Joi Ito, Justin.tv, Larry Wall, Maui Hawaii, Menlo Park, Mitch Kapor, nuclear winter, Paul Buchheit, Paul Graham, Peter Thiel, Richard Feynman, Robert Metcalfe, Ruby on Rails, Sam Altman, Sand Hill Road, side project, Silicon Valley, slashdot, social software, software patent, South of Market, San Francisco, Startup school, stealth mode startup, Steve Ballmer, Steve Jobs, Steve Wozniak, web application, Y Combinator

The Alliant management team in 1985: (from left to right) Rich McAndrew, Craig Mundie, Ronald Gruner, John Clary, and David Micciche C H A P T E R 33 Jessica Livingston Cofounder, Y Combinator Jessica Livingston founded Y Combinator in 2005 with Paul Graham, Robert Morris, and Trevor Blackwell. Y Combinator developed a new approach to venture funding: to fund startups in batches, giving them just enough money to get started, working closely with them to refine their ideas, and then introducing them to later stage investors for further funding. In three years they have funded more than 100 startups. When did you start Y Combinator? Livingston: We started Y Combinator in March 2005. Around that same time, I had gotten a book deal for Founders at Work, so I had planned to quit my job doing marketing at an investment bank and work full-time for a little while on the book. But we started Y Combinator simultaneously, so I didn’t really get to spend much time on the book.

We chose eight that we had wanted to fund, and all of them but one said yes. I give the founders a lot of credit, because this was a brand new concept and Y Combinator had no track record. The deal was: move to Cambridge for the summer and get $12,000 or $18,000, depending on whether you were two or three founders. We based the amount of money on the MIT graduate student stipend, which was a couple grand a month. We said, “Come to Cambridge and we’ll work with you, and we’ll get together for dinner and hear from guest speakers every week.” (Unfortunately for Paul, we hijacked his personal office to use for Y Combinator.) So seven of them said yes, and I went into work on Monday thinking “Y Combinator is real now”—even though we didn’t even have Y Combinator legally set up at this point. I gave my notice that day, I think. But that day something else very memorable happened.

But we started Y Combinator simultaneously, so I didn’t really get to spend much time on the book. What was the process when Y Combinator got started? Livingston: That would assume that we had a process. There was no process. Remember, Y Combinator started off as an experiment. Paul had wanted to do angel investing. He wanted to help people start companies. But he didn’t really want all the requirements that come with being an angel investor, so he thought he should start an organization that could handle all of this for him. I said, “That sounds interesting. I’d love to work with entrepreneurs.” So we sort of hatched this idea for Y Combinator, and I was the one in charge of doing a lot of the business stuff. We decided to do a batch of investments at once, so that we could learn how to be investors. We decided, “OK, we’ll invest in a group of startups, and we’ll do it over the summer since a lot of people are free over the summertime.”


pages: 373 words: 112,822

The Upstarts: How Uber, Airbnb, and the Killer Companies of the New Silicon Valley Are Changing the World by Brad Stone

Affordable Care Act / Obamacare, Airbnb, Amazon Web Services, Andy Kessler, autonomous vehicles, Ben Horowitz, Boris Johnson, Burning Man, call centre, Chuck Templeton: OpenTable:, collaborative consumption, East Village, fixed income, Google X / Alphabet X, housing crisis, inflight wifi, Jeff Bezos, Justin.tv, Kickstarter, Lyft, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mitch Kapor, Necker cube, obamacare, Paul Graham, peer-to-peer, Peter Thiel, race to the bottom, rent control, ride hailing / ride sharing, Ruby on Rails, Sand Hill Road, self-driving car, semantic web, sharing economy, side project, Silicon Valley, Silicon Valley startup, Skype, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, Tony Hsieh, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ubercab, Y Combinator, Y2K, Zipcar

By spending time at Justin.tv, the Airbnb founders got to see what a real tech startup looked like, one with real offices, real employees, and actual venture capital in the bank. (Justin.tv later spun off a video-game service, Twitch.tv, which was acquired by Amazon in 2014 for $970 million.) Continuing this education, they attended a one-day event called Startup School, organized by the startup incubator Y Combinator and hosted by Stanford University. The speakers that year included Amazon CEO Jeff Bezos and the investor Marc Andreessen, an inventor of the web browser. But the speech the founders remembered best was by Greg McAdoo, a venture capitalist at the top-tier VC firm Sequoia Capital, a man whom they would soon get to know well. McAdoo spoke about why being a great entrepreneur required the precision of a great surfer.

It did not propel the company to immediate success or generate any significant wealth; in fact, they were still barely making ends meet and began subsisting on the surplus Cap’n McCains. But it did demonstrate an extreme level of commitment and an ability to think creatively that, ultimately, would lead to their long-awaited break. A few weeks later, Chesky decided that the founders of the struggling company should apply to the prestigious Y Combinator startup school, which invested seventeen thousand dollars in each startup, took a 7 percent ownership stake, and surrounded founders with mentors and technology luminaries during an intense three-month program. It was a last-ditch effort and Chesky actually missed the application deadline by a day. Michael Seibel, an alumnus of the program (and later its CEO), had to ask the organizers to let the company submit late.

Blecharczyk flew out to San Francisco and crashed on the living-room couch on Rausch Street, and the three co-founders gathered themselves for one last try. “If we didn’t get in, we would not exist,” Gebbia says. “The business was just not working.” Before they left for the interview, Gebbia went to grab boxes of the cereal. Blecharczyk snapped at him. “No, no, no,” he said. “Keep the cereal at home.” Gebbia pretended to acquiesce, then surreptitiously slipped two boxes into his bag anyway. The interview at Y Combinator’s offices in Mountain View was practically hostile. “People are actually doing this?” asked Paul Graham, the program’s legendary co-founder, when the three men described the home-sharing concept. “Why? What’s wrong with them?” Graham, then forty-four, later admitted that he didn’t get it. “I wouldn’t want to stay on anyone else’s sofa and I didn’t want anyone to stay on mine,” he says. But after they turned to go, to Blecharczyk’s consternation, Gebbia brought out the two boxes of cereal and handed them to Graham, who was rightfully confused.


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, commoditize, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, Donald Trump, Douglas Hofstadter, dumpster diving, Flash crash, G4S, Gödel, Escher, Bach, High speed trading, Howard Rheingold, index fund, Isaac Newton, John Markoff, John Maynard Keynes: technological unemployment, knowledge economy, late fees, Marc Andreessen, Mark Zuckerberg, market bubble, medical residency, money market fund, Myron Scholes, Narrative Science, PageRank, pattern recognition, Paul Graham, Pierre-Simon Laplace, prediction markets, quantitative hedge fund, Renaissance Technologies, ride hailing / ride sharing, risk tolerance, Robert Mercer, 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

In the fall of 2010, I conjured something with my friend Riley Scott that seemed like it could work. The idea eventually became Aisle50, a Web site that offers deals on grocery items for consumers to purchase before they head to the store. While building Aisle50, we applied and were accepted to be part of Silicon Valley’s Y Combinator, which helps startups get off the ground with funding, mentorship, and connections to investors. A good percentage of my cohort at Y Combinator picked up programming by the time they were fourteen years old. When they reached college, often an elite university, they could already string together thousands of lines of code, create the guts of a stable application, or bolt up an original Web site design in a matter of hours. During the three months I spent there in the summer of 2011, I learned how Mark Zuckerbergs are created: not from spontaneous explosions of intellect and technology, but from years and years of staring at a computer screen, getting to know code as intuitively as a seasoned copy editor knows idioms, punctuation, and style.

There now exist all sorts of paths for people to learn programming at young ages. Countless Web communities and chat rooms are dedicated solely to the writing of code and the construction of algorithms. One company from my Y Combinator group, Codecademy, hit upon an idea so popular—a well-designed site for learning how to program online—that it drew more than 200,000 users in its first two weeks after launching. Just six months after launch, Codecademy landed a partnership with the White House to promote computer programming. This is the new reality we live in: a twenty-one-year-old with the tools to conceive complex algorithms can form a partnership with the president of the United States. Y Combinator is just a microcosm of a movement, often pushed forward by youth, that is putting algorithms inside everything we do. During the last couple of decades, this class of revolutionaries has led the way in fashioning algorithms that solve problems, make money, and, in sweeping fashion, take jobs away from people.

By the time I finished, however, I had left Forbes to form a startup, Aisle50, which offers grocery discounts to consumers. It was quite a change for me but also one that I embraced. There have been many helping hands along the way, some of the most formidable ones coming from our investors and advisers at Y Combinator, Paul Graham and Jessica Livingston. They have built something special in Silicon Valley, and, for the curious, there happens to be a book being released at exactly the same time as this one, by the same publisher, that is the best chronicle ever put together on Y Combinator: Randy Stross’s The Launch Pad. Read it. As for Aisle50, I have high hopes thanks to our crack sales and engineering teams, who have proven to be up to every challenge we faced so far, and there have been many. Most important, I’m grateful to Riley Scott, my cofounder.


pages: 294 words: 82,438

Simple Rules: How to Thrive in a Complex World by Donald Sull, Kathleen M. Eisenhardt

Affordable Care Act / Obamacare, Airbnb, asset allocation, Atul Gawande, barriers to entry, Basel III, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, drone strike, en.wikipedia.org, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, Moneyball by Michael Lewis explains big data, Nate Silver, Network effects, obamacare, Paul Graham, performance metric, price anchoring, RAND corporation, risk/return, Saturday Night Live, sharing economy, Silicon Valley, Startup school, statistical model, Steve Jobs, TaskRabbit, The Signal and the Noise by Nate Silver, transportation-network company, two-sided market, Wall-E, web application, Y Combinator, Zipcar

. [>] When the two friends: Jessica Salter, “Airbnb: The Story Behind the $1.3bn Room-Letting Website,” Telegraph, September 7, 2012, http://www.telegraph.co.uk/technology/news/9525267/Airbnb-The-story-behind-the-1.3bn-room-letting-website.html. [>] Because of the success: Ibid. [>] Y Combinator is a “seed accelerator”: Benjamin L. Hallen, Christopher B. Bingham, and Susan L. Cohen, “Do Accelerators Accelerate? A Study of Venture Accelerators as a Path to Success” (working paper, University of Washington, Seattle, 2013). [>] At this point: Paul Graham, October 2013, “What Happens at Y Combinator,” http://ycombinator.com/atyc.html, accessed April 28, 2014; and Freedman, 2013, “YC Without Being in YC,” http://blog.42floors.com, accessed April 28, 2014. Firsthand account of how former Y Combinator entrepreneurs mimicked the Y Combinator experience by pretending that they had just been accepted again. [>] Another way of learning: Derek Thompson, “Airbnb CEO Brian Chesky on Building a Company and Starting a Sharing Revolution,” Atlantic, August 13, 2013, http://www.theatlantic.com/business/archive/2013/08/airbnb-ceo-brian-chesky-on-building-a-company-and-starting-a- sharing-revolution/278635/. [>] As Brian recalled: Ibid. [>] Like clockwork: Tame, “From Toilet Seats to $1 Billion.” [>] The founders coupled these: Jessie Hempel, “More Than a Place to Crash,” Fortune, May 3, 2012, http://fortune.com/2012/05/03/airbnb-more-than-a-place-to-crash/. [>] The founders also had: Vella and Bradley, “Airbnb CEO—‘Grow Fast but not Too Fast.’” [>] Airbnb ended up with: Tomio Geron, “Airbnb Hires Joie de Vivre’s Chip Conley as Head of Hospitality,” Forbes, September 17, 2013, http://www.Forbes.com/sites/tomiogeron/2013/09/17. [>] In fact, Airbnb: Salter, “Airbnb: The Story Behind the $1.3bn Room-Letting Website.” [>] Airbnb has become: Thompson, “Airbnb CEO Brian Chesky on Building a Company and Starting a Sharing Revolution.” 8.

Joe and Brian kept Airbnb afloat by selling gimmicky breakfast cereal, and surprisingly sold several hundred boxes of “Obama O’s” and “Cap’n McCain” on eBay. The big picture was, however, that Airbnb was floundering, with a few initial rules that cried out for improvement. A much-needed turning point came when Airbnb joined Y Combinator. Y Combinator is a “seed accelerator” providing financing, advice, and connections to cohorts of early-stage ventures, but its headliner mission is helping entrepreneurs improve very fast. At this point, Airbnb’s entrepreneurs began multitasking different ways to learn. One way was from weekly Tuesday-night dinners at Y Combinator. Each week, a famous founder or other luminary delivered an off-the-record speech full of stories and advise about building companies. It was an opportunity to learn vicariously from role models from the real world. During the mingling time at the dinner, entrepreneurs from various companies talked with each other to learn what their peers were doing across lots of markets, and to give and get advice.

During the mingling time at the dinner, entrepreneurs from various companies talked with each other to learn what their peers were doing across lots of markets, and to give and get advice. This was another opportunity to learn—this time through presenting Airbnb’s story and getting feedback and insights from peers. These dinners created a relentless weekly rhythm of stepping back to reflect, getting feedback and ideas, and heading back to work. Another way of learning was through tailored expert advice. The Airbnb founders gained two pivotal insights from Y Combinator cofounder Paul Graham that critically reframed their conception of what to do. One piece of advice was counterintuitive—forget about growing Airbnb, and instead focus on creating the perfect Airbnb experience. Graham’s argument was, “It’s better to have a hundred people love you than to have a million people like you.” The second piece of advice was to stop organizing their business around conferences and get out into cities.


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How to Build a Billion Dollar App: Discover the Secrets of the Most Successful Entrepreneurs of Our Time by George Berkowski

Airbnb, Amazon Web Services, barriers to entry, Black Swan, business intelligence, call centre, crowdsourcing, disruptive innovation, en.wikipedia.org, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, iterative process, Jeff Bezos, Jony Ive, Kickstarter, knowledge worker, Lean Startup, loose coupling, Marc Andreessen, Mark Zuckerberg, minimum viable product, MITM: man-in-the-middle, move fast and break things, move fast and break things, Network effects, Oculus Rift, Paul Graham, QR code, Ruby on Rails, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software as a service, software is eating the world, Steve Jobs, Steven Levy, Travis Kalanick, ubercab, Y Combinator

See www.webopedia.com/TERM/L/link_farming.html. 6 Matt Marshall, ‘The Top 10 Mobile Advertising Companies’, article on VentureBeat.com, 12 June 2013, venturebeat.com/2013/06/12/the-top-10-mobile-advertising-companies/. 7 ‘What Does it Cost to do Press Releases and What Services (Marketwire, PRWeb, Business Wire) Are Best?’, Quora.com, www.quora.com/What-does-it-cost-to-do-press-releases-and-what-services-Marketwire-PRWeb-BusinessWire-etc-are-best. Chapter 11: Is Your App Ready for Investment? 1 According to a post from a partner at Y Combinator on ‘How Many People/Teams Get Rejected by Y Combinator During Each Application Period?’, Quora.com, www.quora.com/How-many-people-teams-get-rejected-by-Y-Combinator-during-each-application-period. 2 This information comes from an interview with Alice Bentinck, cofounder of Entrepreneur First conducted on 24 February 2014. Chapter 12: How Much is Your App Worth and How Much Money Should You Raise? 1 Bill Payne, ‘The Pre-Money Valuation of Angel Deals in 2012’, blog post on AngelCapitalAssociation.org, 13 May 2013, www.angelcapitalassociation.org/blog/1266679842/. 2 Investor Tool on SiSense.com, www.crunchbase.sisense.com/#!

It’s a great alternative to just going and chasing seed investors via AngelList (or good old-fashioned hitting the pavement). I have a few friends who have graduated from two accelerators – Y Combinator and Techstars – and the feedback has been mixed. Americans love having seals of approval from prestigious institutions, so the programme seems to yield great results for them, but the Europeans seem a bit more tepid about the format. Personally, I think you get back what you put in, and having access to their network of alumni and their inside knowledge is a precious resource. Let’s have a look the three top programmes. Y Combinator is probably the best seed accelerator. It was started in March 2005 and has funded more than 500 companies – including Dropbox, Airbnb and Stripe. It provides seed money, advice and connections during two three-month programmes each year.

Learning About Leadership When Dropbox started to take off, Drew Houston, the CEO, started reading. He knew that he had a lot to learn and relied on any resources he could lay his hands on. He knew he had to adapt quickly if he was going to make his company a success. Y Combinator – the accelerator programme – helped the young CEO along the way. ‘It’s a mix of a variety of different things,’ he says, ‘like mentors – people who are experienced and have been through the process many times – and peers. Some of my best friends are Y Combinator founders, and we all went through the same kind of thing at the same time.’ Dropbox’s early board of directors also helped him recognise patterns and gave him an idea of what he should be thinking about. In the end, his attitude proved to be the most important resource to draw on.9 ‘The advice I would give is to get used to things,’ says Houston.


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The End of Nice: How to Be Human in a World Run by Robots (Kindle Single) by Richard Newton

3D printing, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, disruptive innovation, fear of failure, Filter Bubble, future of work, Google Glasses, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, lateral thinking, Lean Startup, low skilled workers, Mark Zuckerberg, move fast and break things, move fast and break things, Paul Erdős, Paul Graham, recommendation engine, rising living standards, Robert Shiller, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, social intelligence, Steve Ballmer, Steve Jobs, Y Combinator

In contrast, this more detailed recent research suggests that Mozart was in fact wrestling with his composition all day long, sometimes on paper and sometimes in his prodigious memory. Far from being the passive recipient of great work, the truth is that creativity is work – a great deal of it. Grit The magic lies, brace yourself, in determination. When he spoke about the number one quality he looks for in founders, Paul Graham of Y Combinator said: “Determination. This has turned out to be the most important quality in start-up founders. We thought when we started Y Combinator that the most important quality would be intelligence. That’s the myth in the Valley. And certainly you don’t want founders to be stupid. But as long as you’re over a certain threshold of intelligence, what matters most is determination. You’re going to hit a lot of obstacles. You can’t be the sort of person who gets demoralized easily.”

Becoming Anti-Nice “Though the most successful founders are usually good people, they tend to have a piratical gleam in their eye. They’re not Goody Two-Shoes type good. Morally, they care about getting the big questions right, but not about observing proprieties. That’s why I’d use the word naughty rather than evil. They delight in breaking rules, but not rules that matter. This quality may be redundant though; it may be implied by imagination.” – Paul Graham, founder of Y Combinator In his autobiography, Mark Twain tells of his childhood friend, Tom Blankenship, who was the inspiration for Huckleberry Finn, a character who was poorly educated and stood outside society but as a result appraised the world and society around him with a clear and critical eye: “In Huckleberry Finn I have drawn Tom Blankenship exactly as he was. He was ignorant, unwashed, insufficiently fed; but he had as good a heart as ever any boy had.

In pursuit of failure Inside a utilitarian converted warehouse in East London’s trendy Farringdon an accelerator program is in process. Cramped around shared desks and a battery of 24/7 coffee machines eleven start-up companies from seven different countries are plotting to disrupt established big businesses. The program is run by a company called TechStars which is one of the three big names in “start-up accelerators” alongside Y-Combinator and 500 Start-Ups. Accelerators are entrepreneurial bootcamps which provide embryonic companies with a workspace, business expertise and access to money, press, partners, know-how and a giant corps d’esprit. After a typical three-month program, the start-up companies are released into the commercial world to disrupt, innovate and clean up! Or fail. In fact the name of the game is fail fast.


pages: 499 words: 144,278

Coders: The Making of a New Tribe and the Remaking of the World by Clive Thompson

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 4chan, 8-hour work day, Ada Lovelace, AI winter, Airbnb, Amazon Web Services, Asperger Syndrome, augmented reality, Ayatollah Khomeini, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, blue-collar work, Brewster Kahle, Brian Krebs, Broken windows theory, call centre, cellular automata, Chelsea Manning, clean water, cloud computing, cognitive dissonance, computer vision, Conway's Game of Life, crowdsourcing, cryptocurrency, Danny Hillis, David Heinemeier Hansson, don't be evil, don't repeat yourself, Donald Trump, dumpster diving, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Ethereum, ethereum blockchain, Firefox, Frederick Winslow Taylor, game design, glass ceiling, Golden Gate Park, Google Hangouts, Google X / Alphabet X, Grace Hopper, Guido van Rossum, Hacker Ethic, HyperCard, illegal immigration, ImageNet competition, Internet Archive, Internet of things, Jane Jacobs, John Markoff, Jony Ive, Julian Assange, Kickstarter, Larry Wall, lone genius, Lyft, Marc Andreessen, Mark Shuttleworth, Mark Zuckerberg, Menlo Park, microservices, Minecraft, move fast and break things, move fast and break things, Nate Silver, Network effects, neurotypical, Nicholas Carr, Oculus Rift, PageRank, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, pink-collar, planetary scale, profit motive, ransomware, recommendation engine, Richard Stallman, ride hailing / ride sharing, Rubik’s Cube, Ruby on Rails, Sam Altman, Satoshi Nakamoto, Saturday Night Live, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, single-payer health, Skype, smart contracts, Snapchat, social software, software is eating the world, sorting algorithm, South of Market, San Francisco, speech recognition, Steve Wozniak, Steven Levy, TaskRabbit, the High Line, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, universal basic income, urban planning, Wall-E, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator, Zimmermann PGP, éminence grise

The investor isn’t looking for stability: They want rapid growth that leads to a bigger return on their investment. The Y Combinator accelerator—which takes in several dozen tech firms each year, to try and help them into the big leagues—ends each cohort’s program with a Demo Day, where the young companies show off their products for a room of handpicked venture capitalists. The start-ups are inevitably desperate to include in their presentation a hockey-stick chart—the one that shows their user base suddenly blasting off into the sky. One evening, I visited the hackerhouse of People.ai, a company that just days earlier had done their Y Combinator demo. They pecked at keyboards and exhaustedly described how they’d spent the three months in Y Combinator frantically registering new clients for their service, in an attempt to produce that hockey stick.

for sex by investors: Reed Albergotti, “Silicon Valley Women Tell of VC’s Unwanted Advances,” The Information, June 22, 2017, https://www.theinformation.com/articles/silicon-valley-women-tell-of-vcs-unwanted-advances; Sara O’Brien, “Sexual Harassment in Tech: Women Tell Their Stories,” CNN Tech, https://money.cnn.com/technology/sexual-harassment-tech/; Katie Benner, “Women in Tech Speak Frankly on Culture of Harassment,” New York Times, June 30, 2017, https://www.nytimes.com/2017/06/30/technology/women-entrepreneurs-speak-out-sexual-harassment.html; all accessed August 19, 2018.. Pao later wrote: Ellen Pao, Reset: My Fight for Inclusion and Lasting Change (New York: Random House, 2017), 78. gender for Y Combinator: Cadran Cowansage, “Ask a Female Engineer: Thoughts on the Google Memo,” Y Combinator (blog), August 15, 2017, accessed August 19, 2018, https://blog.ycombinator.com/ask-a-female-engineer-thoughts-on-the-google-memo/. as a lawsuit alleged: Jordan Pearson, “How the Magic Leap Lawsuit Illuminates Tech’s Gendered Design Bias,” Motherboard, February 15, 2017, accessed August 19, 2018, https://motherboard.vice.com/en_us/article/aeygje/how-the-magic-leap-lawsuit-illuminates-techs-gendered-design-bias.

A vaguely goopy white, Soylent looks pretty much like “a glassful of pancake batter,” as a coder friend of mine joked, adding that “it tastes like it, too.” He was right, as I discovered as I slugged back the drink. But I finished the entire meal in five minutes, which is the point: Soylent is the ultimately optimized meal. Soylent was invented in 2013 by a 25-year-old Rob Rhinehart, a programmer whose start-up—founded with two young collaborators—had gotten $170,000 from Y Combinator to create inexpensive, newfangled cell phone towers. Alas, their tech was a bust. But Rhinehart had, in his spare time, been pondering a new problem of everyday life: food. Food, Rhinehart decided, was an enormous waste of time. He figured he spent about two hours a day on meals. “Typically I would cook eggs for breakfast, eat out for lunch, and cook a quesadilla, pasta, or a burger for dinner,” he calculated on his blog.


pages: 406 words: 105,602

The Startup Way: Making Entrepreneurship a Fundamental Discipline of Every Enterprise by Eric Ries

activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, autonomous vehicles, barriers to entry, basic income, Ben Horowitz, Black-Scholes formula, call centre, centralized clearinghouse, Clayton Christensen, cognitive dissonance, connected car, corporate governance, DevOps, Elon Musk, en.wikipedia.org, fault tolerance, Frederick Winslow Taylor, global supply chain, index card, Jeff Bezos, Kickstarter, Lean Startup, loss aversion, Marc Andreessen, Mark Zuckerberg, means of production, minimum viable product, moral hazard, move fast and break things, move fast and break things, obamacare, peer-to-peer, place-making, rent-seeking, Richard Florida, Sam Altman, Sand Hill Road, secular stagnation, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Steve Jobs, the scientific method, time value of money, Toyota Production System, Uber for X, universal basic income, web of trust, Y Combinator

At the start of 2017, the government selected roughly two thousand unemployed workers from fields ranging from technology to construction and enrolled them in a pilot UBI program to see what will happen.21 Y Combinator is also running an experiment with basic income, having selected one hundred families in Oakland, California, who will receive $1,000 to $2,000 a month as part of a five-year program designed to look at how ready money affects people’s “happiness, well-being, financial health, as well as how people spend their time.” The data and research methods will be shared at the project’s end so others can learn from and build on the experiment, which is testing the idea, as Y Combinator president Sam Altman says, that a basic income could “give people the freedom to pursue further education or training, find or create a better job, and plan for the future.”22 In France, an experiment that allowed people to keep their unemployment benefits while starting a new business saw an increase of 25 percent per month in the creation of new companies.23 And the Dutch and Canadians aren’t far behind—both countries also launched experiments in 2017.24 REGULATORY RELIEF FOR STARTUPS “Sliding Scale” Regulations Regulation can destroy startups without even meaning to.

We’ll see this idea again in the next chapter, but startup-style meritocracy is a little different than what most people are used to. Even if you wanted to design a program that was only for entrepreneurs, it would be impossible to do so. What makes someone an entrepreneur is not that she or he got assigned that role by someone at corporate HQ. Good ideas come from unexpected places. In fact, one of the lessons of the rise of startup accelerators like Y Combinator (YC) and Techstars is that they achieved their disproportionate impact on the world, in part, by bringing new people into the entrepreneurial ecosystem. This is one of the most striking things about reading the early YC applications in particular. Many of the founders of multibillion-dollar startups weren’t sure they were cut out for entrepreneurship at all. By lowering the barriers to getting started, providing a low-risk way to try it out, and effective role modeling, YC has been able to bring unexpected talent into the ecosystem.4 In order for an organization to take advantage of the latent entrepreneurial talent within it, it has to invest in making the broad pool of its employee base aware of the possibilities of entrepreneurship as a career path.

Let’s design our experiments to prove that.4 In addition to the learning benefits I mentioned above, this approach offers another major bonus: Sometimes the team really is right! COACHING STRUCTURE In the startup world, coaching has been a long-standing part of our practice. Investors have always maintained networks of mentors and advisors to help teams develop and grow. More recent accelerator programs, such as Y Combinator and Techstars, and more modern VCs, such as Andreessen Horowitz, have formalized this approach into a more structured program of services and support. Advice and mentorship are available to startups in the portfolio, but they are never—ever—substitutes for leadership. Nobody is forced to talk to any specific mentor or do what that mentor says. Advisors take on the role of coaches—not spies, not leaders, not executives, not substitute board members.


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

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

A growing number of people are proposing a bold new idea to deal with this. In 2017 I interviewed Sam Altman, the president of Y Combinator, the most important fund in Silicon Valley for tech start-ups. Thousands of businesses apply every year to access Y Combinator’s funding and guidance, in exchange for a small slice of their company. Sam is a Princeton dropout and frequently wears a hoodie, yet when I met him, he was only 31 years old and already a multi-millionaire. He is often described as ‘the man who invents the future’. The companies Y Combinator have funded include Airbnb and Starsky Robotics, and are now altogether valued at $80 billion. Aware of the potential turbulence that AI might unleash, Y Combinator recently started to fund a pilot in universal basic income. UBI, as it is commonly referred to, is an increasingly popular idea to deal with the possible rise of joblessness and tech-fuelled inequality.

For some on the left, including a handful of radicals in the UK circling Labour leader Jeremy Corbyn, it represents a way to redistribute wealth more fairly. And for the utopians, it would allow people to do more meaningful things with their lives than monotonous labour.* Sam doesn’t think anyone is ready for AI. ‘We are going to need to have new distribution, new social safety nets,’ he told me in his Y Combinator office. ‘What happens if you just give people money to live on? . . . Say, “Here’s enough money to have a house and eat and have fun”.’ It’s an interesting idea. There are an awful lot of jobs that people don’t really want to do. If the things that people gain from work – economic means, structure, purpose – can be achieved in other ways, that’s worth exploring. Proponents of UBI argue that this would be a ‘basic’ income – and not necessarily a replacement for work.


pages: 706 words: 202,591

Facebook: The Inside Story by Steven Levy

active measures, Airbnb, Airbus A320, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, augmented reality, Ben Horowitz, blockchain, Burning Man, business intelligence, cloud computing, computer vision, crowdsourcing, cryptocurrency, don't be evil, Donald Trump, East Village, Edward Snowden, El Camino Real, Elon Musk, Firefox, Frank Gehry, glass ceiling, indoor plumbing, Jeff Bezos, John Markoff, Jony Ive, Kevin Kelly, Kickstarter, Lyft, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, move fast and break things, move fast and break things, natural language processing, Network effects, Oculus Rift, PageRank, Paul Buchheit, paypal mafia, Peter Thiel, pets.com, post-work, Ray Kurzweil, recommendation engine, Robert Mercer, Robert Metcalfe, rolodex, Sam Altman, Sand Hill Road, self-driving car, sexual politics, Shoshana Zuboff, side project, Silicon Valley, Silicon Valley startup, slashdot, Snapchat, social graph, social software, South of Market, San Francisco, Startup school, Steve Ballmer, Steve Jobs, Steven Levy, Steven Pinker, Tim Cook: Apple, web application, WikiLeaks, women in the workforce, Y Combinator, Y2K

postmortem podcast: “Friendster 1: The Rise,” Startup, April 21, 2017. Buddy Zoo: “AIM Meets Social Network Theory,” Slashdot, April 14, 2003. Chris Hughes: In addition to personal interview, Hughes tells his own story in Fair Shot: Rethinking Inequality and How We Learn (St. Martin’s Press, 2018). “People would just spend hours”: Interview with Sam Altman, Y Combinator, “Mark Zuckerberg: How to Build the Future,” August 16, Zuckerberg Transcripts, 171. steam coming from the suite’s bathroom: Interview with Y Combinator, “Mark Zuckerberg at Startup School 2013,” October 25, 2013, Zuckerberg Transcripts, 160. his first notice: S. F. Brickman, “Not So Artificial Intelligence,” Harvard Crimson, October 23, 2003. “a bitch”: The online journal cited here, and first published by Luke O’Brien in the online Harvard alumni journal 02138 in “Poking Facebook,” would become notorious in the movie The Social Network.

A New Claim Emerges,” New York Times, September 1, 2007. “unfazed”: Matt Welsh blogged, “How I Almost Killed Facebook,” February 20, 2009. Harry Lewis: Alexis C. Madrigal, “Before It Conquered the World, Facebook Conquered Harvard,” The Atlantic, February 4, 2019. “There was nothing like that”: Interview with Y Combinator, “Mark Zuckerberg at Startup School 2013,” October 25, 2013, Zuckerberg Transcripts, 160. come from Microsoft: Interview with Y Combinator, “Mark Zuckerberg at Startup School 2012,” October 20, 2012, Zuckerberg Transcripts, 161. Saverin kicked in: Information about Eduardo Saverin is drawn from Kirkpatrick, The Facebook Effect; Mezrich, The Accidental Billionaires (Saverin cooperated with the book); and Nicholas Carlson, “How Mark Zuckerberg Booted His Co-Founder Out of the Company,” Business Insider, May 15, 2012.

Google’s elders were professors who wrote the textbooks that its leaders learned from; Facebook hired Mark Zuckerberg’s Harvard TA. True, even in 2005 there was a smattering of thirtysomethings on staff—a few of them married, with kids. But while Zuckerberg understood the value of veterans like Jeff Rothschild, at his core he believed that younger people were . . . smarter. He said exactly that in a Y Combinator start-up school in 2007, telling 650 would-be founders to hire people who were young and technical. “Why are most chess masters under thirty?” he asked. His later apology for that remark (which, if it truly reflected Facebook’s hiring policy, would put the company in violation of federal labor laws) didn’t cover up the fact that his original statement seemed totally in sync with his worldview.


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WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

4chan, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, blockchain, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, corporate governance, corporate raider, creative destruction, crowdsourcing, Danny Hillis, data acquisition, deskilling, DevOps, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, full employment, future of work, George Akerlof, gig economy, glass ceiling, Google Glasses, Gordon Gekko, gravity well, greed is good, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, move fast and break things, Network effects, new economy, Nicholas Carr, obamacare, Oculus Rift, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, strong AI, TaskRabbit, telepresence, the built environment, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

Is there a way that we could provide value to firms that want to make their mark in the real economy without putting them on the treadmill to an exit? Bryce came up with a creative solution, which he called indie.vc. Indie.vc is modeled on Y Combinator, the classic Silicon Valley accelerator, which takes a small but meaningful stake in very-early-stage companies in exchange for a very small amount of cash, plus a lot of help in business planning, networking with other entrepreneurs, and eventually, showcasing the company to VCs. Y Combinator has been phenomenally successful, helping to birth companies such as Airbnb and Dropbox. But the focus of Y Combinator’s program specifically, and VC-funded companies generally, is on raising the next round of funding. In the case of Y Combinator, months of work and preparation are put into nailing the perfect pitch for a performance in fundraising called demo day. For VC-backed startups, the focus is on what milestones a team must hit in order to be attractive for their next round of funding—ideally at a meaningful multiple of the last funding round price.

In Norway, by contrast, Autor said, “All kinds of work are valued. Everybody works, they just work a little less.” The generous redistribution of oil profits and a strong social safety net funded by the wealth that is understood to belong to all makes Norway one of the happiest and wealthiest countries in the world. For a technology perspective, I turned to Paul Buchheit, creator of Gmail and now a partner at Y Combinator, and Sam Altman, the head of Y Combinator. In a 2016 conversation, Paul said to me: “There may need to be two kinds of money: machine money, and human money. Machine money is what you use to buy things that are produced by machines. These things are always getting cheaper. Human money is what you use to buy things that only humans can produce.” The idea that there should be different kinds of “money” is a provocative metaphor rather than a concrete proposal.

The experiment was so successful that they decided to build out a short-term room, apartment, and home rental service for the upcoming SXSW technology conference in Austin, Texas, because they knew that every hotel room in the city would be sold out. They followed that up by doing the same thing for the 2008 Democratic National Convention, held in Denver, Colorado. In 2009, they were accepted into Y Combinator, the prestigious Silicon Valley startup incubator, and then received funding from one of Silicon Valley’s top venture firms, Sequoia Capital. But despite a promising start, they were still struggling with acquiring users fast enough. The breakthrough came when they realized that hosts were taking lousy photographs of their properties, leading to lower trust and thus lower interest by possible renters.


pages: 56 words: 16,788

The New Kingmakers by Stephen O'Grady

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

Even when venture capitalists took an interest, the deals they offered often were not favorable for entrepreneurs—they frequently provided more money than was required in order to obtain the largest possible share of the company. Then in 2008, Paul Graham’s Y Combinator launched. Recognizing that the technology landscape had dramatically lowered the cost of starting a business, Y Combinator offered substantially less money—typically less than $20,000—in return for a commensurately smaller share of the company. Its average equity stake was around 6%. The falling costs of business creation led to a decoupling of the average deal size with the average deal volume. Because the changing technology landscape had dramatically lowered the cost of starting a technology business, its small investments were sufficient to get these young companies off the ground. With the amount of money each company needed in decline, more businesses were given less money, and Y Combinator and other programs like TechStars have played a critical role in this.


Systematic Trading: A Unique New Method for Designing Trading and Investing Systems by Robert Carver

asset allocation, automated trading system, backtesting, barriers to entry, Black Swan, buy and hold, cognitive bias, commodity trading advisor, Credit Default Swap, diversification, diversified portfolio, easy for humans, difficult for computers, Edward Thorp, Elliott wave, fixed income, implied volatility, index fund, interest rate swap, Long Term Capital Management, margin call, merger arbitrage, Nick Leeson, paper trading, performance metric, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, survivorship bias, systematic trading, technology bubble, transaction costs, Y Combinator, yield curve

You first create a trading subsystem for each instrument. Each subsystem tries to predict the price of an individual instrument, and calculate the appropriate position required. These subsystems are then combined into a portfolio, which forms the final trading system. TABLE 15: EXAMPLE OF COMPONENTS IN A TRADING SYSTEM Instruments Trading rule A, variation 2 A2 forecast for instrument Y Trading rule B, variation 1 B1 forecast for instrument Y Combined forecast Y weights A1 forecast, instrument Y Subsystem position in Y Instrument Trading rule A, variation 1 sizing B1 forecast for instrument X Position Trading rule B, variation 1 Portfolio weighted position in X Subsystem position in X Combined forecast X targeting A2 forecast for instrument X Volatility Trading rule A, variation 2 weights A1 forecast for instrument X Forecast Trading rule A, variation 1 Portfolio weighted position in Y Customising for speed and size This trading system has two trading rules A and B; three rule variations A1, A2 and B1; and two instruments X and Y.

When designing trading systems it’s important to know how expensive they are to trade, and whether you have an unusually large or small amount of capital. Given that information, how should you then tailor your system? I’ll address both of these issues in detail in the final chapter of part three. Chapter Six. Instruments Instruments Trading rule A, variation 2 A2 forecast for instrument Y Trading rule B, variation 1 B1 forecast for instrument Y Combined forecast Y weights A1 forecast, instrument Y Subsystem position in Y Instrument Trading rule A, variation 1 sizing B1 forecast for instrument X Position Trading rule B, variation 1 Portfolio weighted position in X Subsystem position in X Combined forecast X targeting A2 forecast for instrument X Volatility Trading rule A, variation 2 weights A1 forecast for instrument X Forecast Trading rule A, variation 1 Portfolio weighted position in Y Customising for speed and size B EFORE YOU THINK ABOUT HOW YOU TRADE YOU NEED TO consider what you’re going to trade – the actual instruments to buy or sell.

If you have only one trading rule variation you can also skip the next chapter. But if you’re using multiple rules or variations then you’ll need to read chapter eight to discover how to combine forecasts from different rules. 123 Chapter Eight. Combined Forecasts Instruments Trading rule A, variation 2 A2 forecast for instrument Y Trading rule B, variation 1 B1 forecast for instrument Y Combined forecast Y weights A1 forecast, instrument Y Subsystem position in Y Instrument Trading rule A, variation 1 sizing B1 forecast for instrument X Portfolio weighted position in X Subsystem position in X Position Trading rule B, variation 1 Combined forecast X targeting A2 forecast for instrument X Volatility Trading rule A, variation 2 weights A1 forecast for instrument X Forecast Trading rule A, variation 1 Portfolio weighted position in Y Customising for speed and size Staunch Systems Trader This chapter is about combining forecasts from different trading rules, including variations of the same rule, so it’s required reading for most staunch systems traders.


pages: 179 words: 42,006

Startup Weekend: How to Take a Company From Concept to Creation in 54 Hours by Marc Nager, Clint Nelsen, Franck Nouyrigat

Amazon Web Services, barriers to entry, business climate, invention of the steam engine, James Watt: steam engine, Mark Zuckerberg, minimum viable product, pattern recognition, Silicon Valley, transaction costs, web application, Y Combinator

New groups of VCs called super angels, which are generally smaller than the traditional multihundred-million-dollar VC fund, can make the small investments necessary to help launch a consumer Internet startup. These angels make lots of early bets and double-down when early results appear. And the results do appear years earlier than they would in a traditional startup. In addition to super angels, incubators like Y Combinator, TechStars, and the 100-plus others like them worldwide have begun to formalize seed-investing. They pay expenses in a formal three-month program, while a startup builds something impressive enough to raise money on a larger scale. However, the penultimate events in this area are Startup Weekends: 54-hour conferences that allow developers, designers, marketers, product managers, and startup enthusiasts to come together to share ideas, form teams, build products, and launch startups.

Those who attend will meet the people who can eventually determine a venture's success. Lovell also warns entrepreneurs against concentrating too much on their ideas, or thinking of Startup Weekend merely as a place to go to find people to do some free weekend work on their idea. “When people are married to an idea, it can go horribly wrong,” she says. One of our facilitators, who has worked with other startup mentorship programs like Y-Combinator, says that these types of programs pick companies to support based on the people who comprise the teams, and expect that the ideas will change along the way. “As a facilitator, I look for attendees on the sidelines Friday night who are struggling to figure out what team to join or [who] feel discouraged because their idea wasn't picked. I tell them to just talk to the teams and join one with people who seem fun.”

There are several programs out there that do mentoring incubation; that is, they will help to support entrepreneurs both financially and educationally for a few weeks or months to see if their ideas take off. These programs are not easy to get into; however, once you're in, you have the freedom and the mentor expertise at your disposal to really pursue your project full-time and wholeheartedly. Y-Combinator, Tech Stars, and Startup Labs are all great entry points into the world of Startup Funding. This is the stage at which somebody—an outsider— really starts to believe in your dream. That's when you can move closer to jumping off the entrepreneurial cliff. This brings us to the next step in the entrepreneurial ladder—the scaling leap. Venture capitalists are constantly considering the groups and individuals that come out of the programs we just mentioned.


pages: 286 words: 87,401

Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies by Reid Hoffman, Chris Yeh

activist fund / activist shareholder / activist investor, Airbnb, Amazon Web Services, autonomous vehicles, bitcoin, blockchain, Bob Noyce, business intelligence, Chuck Templeton: OpenTable:, cloud computing, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, database schema, discounted cash flows, Elon Musk, Firefox, forensic accounting, George Gilder, global pandemic, Google Hangouts, Google X / Alphabet X, hydraulic fracturing, Hyperloop, inventory management, Isaac Newton, Jeff Bezos, Joi Ito, Khan Academy, late fees, Lean Startup, Lyft, M-Pesa, Marc Andreessen, margin call, Mark Zuckerberg, minimum viable product, move fast and break things, move fast and break things, Network effects, Oculus Rift, oil shale / tar sands, Paul Buchheit, Paul Graham, Peter Thiel, pre–internet, recommendation engine, ride hailing / ride sharing, Sam Altman, Sand Hill Road, Saturday Night Live, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart grid, social graph, software as a service, software is eating the world, speech recognition, stem cell, Steve Jobs, subscription business, Tesla Model S, thinkpad, transaction costs, transport as a service, Travis Kalanick, Uber for X, uber lyft, web application, winner-take-all economy, Y Combinator, yellow journalism

Brian and his cofounders, Joe Gebbia and Nathan Blecharcyzk, had already fought their way through plenty of obstacles to build Airbnb, a website that makes it easy for people to rent out their rooms or homes for the night. In the beginning, every investor the founders approached had turned them down or, worse, ignored them. The company was on the upswing now, but the painful early days were still fresh in their minds, and they weren’t looking for another battle. * * * When the Airbnb founders first met, Paul Graham, the highly regarded founder of the start-up accelerator Y Combinator (YC), told them flat out that their idea was terrible. “People are actually doing this?!” he incredulously asked. When Brian told him yes, people were, in fact, renting out their living spaces for a night, Graham’s response was “What’s wrong with them?” Still, Graham had accepted the Airbnb guys into the three-month-long YC program. Not because he was inspired by their Airbnb business, but because he was impressed by the hustle of the founders.

But Wimdu had the home-turf advantage, not to mention ten times the number of employees and more than ten times the amount of invested capital. Competing against them would be one hell of an uphill battle. Tired of the fund-raising grind, especially its emotional toll, Brian wondered whether he had it in him to take on this new and likely bruising fight. But he and his team had spent eighteen seemingly fruitless months working on Airbnb before entering Y Combinator, racking up tens of thousands of dollars in credit card debt. After all the blood, sweat, and tears, were they really willing to give up a quarter of their company? Ultimately, Brian decided not to buy Wimdu, swayed in part by the arguments of his key advisers. Facebook founder Mark Zuckerberg counseled him to fight. “Don’t buy them,” he said. “The best product will win.” YC’s Paul Graham gave similar feedback.

If a company can’t achieve “venture scale” (generally, a market of at least $1 billion in annual sales), then most VCs won’t invest, even if it is a good business. It simply isn’t large enough to help them achieve their goal of returning more than three times their investors’ money. When Brian Chesky was pitching venture capitalists to invest in Airbnb, one of the people he consulted was the entrepreneur and investor Sam Altman, who later became the president of the Y Combinator start-up accelerator. Altman saw Chesky’s pitch deck and told him it was perfect, except that he needed to change the market-size slide from a modest $30 million to $30 billion. “Investors want B’s, baby,” Altman told Chesky. Of course, Altman wasn’t telling Chesky to lie; rather, he argued that if the Airbnb team truly believed in their own assumptions, $30 million was a gross underestimate, and they should use a number that was true to their convictions.


pages: 307 words: 82,680

A Pelican Introduction: Basic Income by Guy Standing

bank run, basic income, Bernie Sanders, Bertrand Russell: In Praise of Idleness, Black Swan, Boris Johnson, British Empire, centre right, collective bargaining, cryptocurrency, David Graeber, declining real wages, deindustrialization, Donald Trump, Elon Musk, Fellow of the Royal Society, financial intermediation, full employment, future of work, gig economy, Gunnar Myrdal, housing crisis, hydraulic fracturing, income inequality, intangible asset, job automation, job satisfaction, Joi Ito, labour market flexibility, land value tax, libertarian paternalism, low skilled workers, lump of labour, Mark Zuckerberg, Martin Wolf, mass immigration, mass incarceration, moral hazard, Nelson Mandela, offshore financial centre, open economy, Panopticon Jeremy Bentham, Paul Samuelson, plutocrats, Plutocrats, precariat, quantitative easing, randomized controlled trial, rent control, rent-seeking, Sam Altman, self-driving car, shareholder value, sharing economy, Silicon Valley, sovereign wealth fund, Stephen Hawking, The Future of Employment, universal basic income, Wolfgang Streeck, women in the workforce, working poor, Y Combinator, Zipcar

Segal has recommended a monthly income guarantee of C$1,320 per person, about 75 per cent of the provincial poverty line, with an extra $500 for disability, to be paid for a minimum of three years. Y Combinator, California In 2016, the start-up ‘accelerator’ Y Combinator announced a plan to conduct a small-scale basic income pilot in Oakland, California, for which $20 million has been put aside, probably to be supplemented by other donors. A ‘pre-pilot’ was launched in September 2016 to test logistics and study design, and a three- or four-year pilot was set to start in mid-2017.14 Sam Altman, the young venture capitalist who is president of Y Combinator, has said he wanted to fund a study on basic income because of the potential of artificial intelligence to eliminate traditional jobs and widen inequalities. He is not primarily interested in studying the impact on employment, assuming that there will not be many jobs out there.

Supporters in this fourth wave include: Nobel Prize winners James Buchanan, Herbert Simon, Angus Deaton, Christopher Pissarides and Joseph Stiglitz; academics Tony Atkinson, Robert Skidelsky and Robert Reich, former Secretary of Labour under Bill Clinton; prominent economic journalists Sam Brittan and Martin Wolf; and leading figures in the BIEN movement, such as German sociologist Claus Offe and the Belgian philosopher Philippe van Parijs. Latterly, the idea has been taken up by Silicon Valley luminaries and venture capitalists, some putting up money for the cause, as we shall see. They include Robin Chase, co-founder of Zipcar, Sam Altman, head of the start-up incubator Y Combinator, Albert Wenger, a prominent venture capitalist, Chris Hughes, co-founder of Facebook, Elon Musk, founder of SolarCity, Tesla and SpaceX, Marc Benioff, CEO of Salesforce, Pierre Omidyar, founder of eBay, and Eric Schmidt, Executive Chairman of Alphabet, Google’s parent. Some people have rejected basic income on the rather crude reasoning that support from this quarter means it must be wrong!

And we can be reasonably sure that these changes will continue to worsen inequalities and be seriously disruptive, in often unpredictable ways that will hit many people through absolutely no fault of their own. In these circumstances, introducing a basic income system now would be sensibly precautionary and an equitable way to respond to the already visible disruption and inequality. Sam Altman, president of the American start-up incubator Y Combinator, has justified his allocation of funds to a basic income pilot (discussed in Chapter 11) on the grounds that we need to know how people would respond if the jobless future were to be realized and a basic income introduced. He told Bloomberg, ‘I’m fairly confident that at some point in the future, as technology continues to eliminate traditional jobs and massive new wealth gets created, we’re going to see some version of this [basic income] at a national scale.’21 In another interview, he put that point at ‘no fewer than 10 years’ and ‘no more than 100’.22 However, the immediate problem is one of income distribution rather than a sudden disappearance of work for humans to do.


pages: 282 words: 81,873

Live Work Work Work Die: A Journey Into the Savage Heart of Silicon Valley by Corey Pein

23andMe, 4chan, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Anne Wojcicki, artificial general intelligence, bank run, barriers to entry, Benevolent Dictator For Life (BDFL), Bernie Sanders, bitcoin, Build a better mousetrap, California gold rush, cashless society, colonial rule, computer age, cryptocurrency, data is the new oil, disruptive innovation, Donald Trump, Douglas Hofstadter, Elon Musk, Extropian, gig economy, Google bus, Google Glasses, Google X / Alphabet X, hacker house, hive mind, illegal immigration, immigration reform, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Law of Accelerating Returns, Lean Startup, life extension, Lyft, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Menlo Park, minimum viable product, move fast and break things, move fast and break things, mutually assured destruction, obamacare, passive income, patent troll, Paul Graham, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, platform as a service, plutocrats, Plutocrats, Ponzi scheme, post-work, Ray Kurzweil, regulatory arbitrage, rent control, RFID, Robert Mercer, rolodex, Ronald Reagan, Ross Ulbricht, Ruby on Rails, Sam Altman, Sand Hill Road, Scientific racism, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, Skype, Snapchat, social software, software as a service, source of truth, South of Market, San Francisco, Startup school, stealth mode startup, Steve Jobs, Steve Wozniak, TaskRabbit, technological singularity, technoutopianism, telepresence, too big to fail, Travis Kalanick, tulip mania, Uber for X, uber lyft, ubercab, upwardly mobile, Vernor Vinge, X Prize, Y Combinator

But they soon became a habit, and in a misguided effort to become more “productive,” I devoured page after page of the self-help and motivational material these websites featured, most of it directed at startup wannabes like me. Lying awake in bed, arm stiff from holding my smartphone aloft, I sought solace in the sanguine stream of updates on Hacker News, a techie discussion forum run by a venture capital fund and startup “incubator” called Y Combinator. This outfit seemed vaguely prestigious, the commenters knowledgeable. The titles of the inspirational homilies on Hacker News reassured me that I was not alone: “Fail Fast, Fail Often, and Fail by Design,” “Failing Fast Means … Failing a Lot,” and, most succinctly, “Success Through Failure.” I took it all to heart. I reinterpreted my failure as a character-building experience. But something else was going on with this self-guided tutelage.

“The dangerous thing is, faking does work to some degree on investors,” Graham wrote. “If you’re super good at sounding like you know what you’re talking about, you can fool investors for at least one and perhaps even two rounds of funding.” Did I need more than one or two rounds of funding? Not really. This was encouraging. * * * I felt even better about my prospects after learning that I didn’t really need an idea. In 2012, Y Combinator, the investment fund behind Hacker News, announced in an online post that it would begin accepting funding applications from teams who didn’t even have ideas for their startups. “So if the only thing holding you back from starting a startup is not having an idea for one,” the investors wrote, “now nothing is holding you back.” I knew the spendthrift reputation of venture capital, yet I was still surprised to learn that some of the most prestigious investors in tech were funneling millions of dollars in capital to kids who showed up for their interviews without so much as an idea.

What did they care? It wasn’t their money. Like private stockbrokers for startups, VCs managed large pools of funds. Which is to say, the investors had investors. Often these were big institutions like foundations and universities—Stanford, naturally, was a major player—as well as pension funds. Because such people expected results, the VC industry couldn’t appear completely irresponsible. Therefore, Y Combinator presented a flimsy rationale for its lax investment criteria in the same online post: A lot of the startups we accept change their ideas completely, and some of those do really well … The other reason we’re doing it is that our experience suggests that smart people who think they can’t come up with a good startup idea are generally mistaken. Almost every smart person has a good idea in them.


pages: 393 words: 91,257

The Coming of Neo-Feudalism: A Warning to the Global Middle Class by Joel Kotkin

Admiral Zheng, Andy Kessler, autonomous vehicles, basic income, Bernie Sanders, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Cass Sunstein, clean water, creative destruction, deindustrialization, demographic transition, don't be evil, Donald Trump, edge city, Elon Musk, European colonialism, financial independence, Francis Fukuyama: the end of history, gig economy, Gini coefficient, Google bus, guest worker program, Hans Rosling, housing crisis, income inequality, informal economy, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, Joseph Schumpeter, land reform, liberal capitalism, life extension, low skilled workers, Lyft, Mark Zuckerberg, market fundamentalism, Martin Wolf, mass immigration, megacity, Nate Silver, new economy, New Urbanism, Occupy movement, Parag Khanna, Peter Thiel, plutocrats, Plutocrats, post-industrial society, post-work, postindustrial economy, postnationalism / post nation state, precariat, profit motive, RAND corporation, Ray Kurzweil, rent control, Richard Florida, road to serfdom, Robert Gordon, Sam Altman, Satyajit Das, sharing economy, Silicon Valley, smart cities, Steve Jobs, Stewart Brand, superstar cities, The Death and Life of Great American Cities, The Future of Employment, The Rise and Fall of American Growth, Thomas L Friedman, too big to fail, trade route, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, unpaid internship, upwardly mobile, We are the 99%, Wolfgang Streeck, women in the workforce, working-age population, Y Combinator

“The rise to power of net-based monopolies coincides with a new sort of religion based on becoming immortal,” writes Jaron Lanier.30 Potentially the most radical and far-reaching of the emerging creeds, transhumanism is a distinctly secular approach to achieving the long-cherished religious goal of immortality.31 The new tech religion treats mortality not as something to be transcended through moral actions, but as a “bug” to be corrected by technology.32 Although it sounds a bit like a wacky cult, transhumanism has long exercised a strong fascination for the elites of Silicon Valley. Devotees range from Sergei Brin, Larry Page, and Ray Kurzweil (of Google) to Peter Thiel and Sam Altman (Y Combinator). Kurzweil celebrates new technologies that allow for close monitoring of brain activity.33 Y Combinator is developing a technology for uploading one’s brain and preserving it digitally.34 The aim is to “develop and promote the realization of a Godhead based on Artificial Intelligence.”35 In some ways, transhumanism seems natural for those who hold technology above all other values. It dispenses with the physical and emotional realities of belonging to a church.

Most, Ferenstein adds, believe that an “increasingly greater share of economic wealth will be generated by a smaller slice of very talented or original people. Everyone else will come to subsist on some combination of part-time entrepreneurial ‘gig work’ and government aid.”11 Ferenstein says that many tech titans, in contrast to business leaders of the past, favor a radically expanded welfare state.12 Mark Zuckerberg, Elon Musk, Travis Kalanick (former head of Uber), and Sam Altman (founder of Y Combinator) all favor a guaranteed annual income, in part to allay fears of insurrection by a vulnerable and struggling workforce. Yet unlike the “Penthouse Bolsheviks” of the 1930s, they have no intention of allowing their own fortunes to be squeezed. Instead, the middle class would likely foot much of the bill for guaranteed wages, health care, free college, and housing assistance, along with subsidies for gig workers, who do not receive benefits from their employers.13 This model could best be described as oligarchical socialism.

CHAPTER 18 The Totalitarian Urban Future The new urban paradigm elevates efficiency and central control above privacy local autonomy class diversity and broad-based property ownership. The same oligarchs who dominate our commercial culture, seek to profit from manipulating our moods, and influence the behavior of our children want to structure our living environment as well.1 Major tech firms—Y Combinator, Lyft, Cisco, Google, Facebook—are aiming to build what they call the “smart city.” Promoted as a way to improve efficiency in urban services, these plans will also provide more opportunity for oligarchs to monitor our lives, as well as sell more advertising. The “smart city” would replace organic urban growth with a regime running on algorithms designed to rationalize our activities and control our way of life.2 This urban vision appeals to tech oligarchs’ belief that their mission is to “change the world,” not simply make money by meeting customers’ needs and desires.


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The Little Schemer by Daniel P. Friedman, Matthias Felleisen, Duane Bibby

Gödel, Escher, Bach, pattern recognition, Y Combinator

Which cond-line is chosen for (apply-primitive name vals) where name is cons and vals is (6 (a b e)) The third: (( eq? name (quote cons)) (cons (first vals) (second vals))). Are we finished now? Yes, we are exhausted. But what about (define ... ) It isn't needed because recursion can be obtained from the Y combinator. Is (define ... ) really not needed? Yes, but see The Seasoned Schemer. Does that mean we can run the interpreter on the interpreter if we do the transformation with the Y combinator? Yes, but don't bother. What makes value unusual? It sees representations of expressions. Should will-stop? see representations of expressions? That may help a lot. Does it help? No, don't bother-we can play the same game again. We would be able to define a function like last-try? that will show that we cannot define the new and improved will-stop ?

I) 0) (else (addl (length (cdr I)))))))) What did we actually get back? We extracted the original function mk-length. Let's separate the function that makes length from the function that looks like length That's easy. .--------------------, (lambda (Ie) ((lambda (mk-length) (mk-length mk-length)) (lambda (mk-length) (Ie (lambda (x) ( (mk-length mk-length) x)))))) Does this function have a name? Yes, it is called the applicative-order Y combinator. (define Y (lambda (Ie) ((lambda (f) (f f)) (lambda (f) (Ie (lambda (x) ((f f) x))))))) Does (define ... ) work again? Sure, now that we know what recursion is. Do you now know why Y works? Read this chapter just one more time and you will. 172 Chapter 9 What is (Y Y) Who knows, but it works very hard. Does your hat still fit? Perhaps not after such a mind stretcher. Stop the World-/ Want to Get Off.


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, Joi Ito, 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

It's good to see that kind of ambition. Santos: And that ambition was not as visible in the beginning? Sohoni: Yeah, I think so. Santos: You think that's changed? Sohoni: We hear that from the guys we've backed. Now that they've become role models in their own local geographies, it's amazing to see them inspire future entrepreneurs and I hear those stories over and over again. Santos: Going back a bit, when you started, Y Combinator and TechStars already existed, and in the blog post when as you mentioned, Saul was thinking of the idea, he actually looked into them. In the beginning, in those talks that you were defining the model for Seedcamp, did you think to follow, more or less, the same model? Why did you choose different values, a different model, the Mini Seedcamps? What led to this difference? Sohoni: Inspiration always comes from both seeing things that trigger ideas in your head.

The second is, as I said, in Europe I kept seeing such a class difference, almost, between money and entrepreneurs, between VCs and entrepreneurs, between the serial entrepreneurs and first-time entrepreneurs, and we wanted to break down that social caste system. So having a much more laid back and almost a university atmosphere for the events was really crucial, and, again, putting entrepreneurs at the center of gravity really was a big shift in culture here. So I think that was crucial to do as well. One of the biggest things we've done is we invest per company three times as much as any other, Y Combinator or TechStars, do. And we take roughly the same amount of equity that they do. That was the other thing. Companies here need a longer runway to raise follow-on funding. I think that's probably changed in the last four years, but at the time we started, they needed a longer runway and you couldn't just invest $18,000. [laughs] It would definitely not have the same result. So that was the big difference, as well.

For our companies, it's certainly given them access to US investors and US businesses. Santos: Now going a bit more into the details behind Seedcamp. Seedcamp is also a company, so it has to pay its own investments. If we look at it, you're taking the same equity, you're offering more money, and you're even touring with the teams that go through the program in the US. Is that competitive in the long run against programs like Y Combinator, TechStars, or other things in Europe, or is it still an unproven model? Sohoni: Granted, yes, it's more funding per business, but we're not in here to build very small businesses. We have a global ambition and it's building globally relevant and globally-sized businesses. And in that sense you're coming in quite early, right? And you're coming in for small amounts of equity, but you're definitely coming in quite early.


pages: 385 words: 101,761

Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire by Bruce Nussbaum

3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, Chuck Templeton: OpenTable:, clean water, collapse of Lehman Brothers, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, disruptive innovation, Elon Musk, en.wikipedia.org, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, follow your passion, game design, housing crisis, Hyman Minsky, industrial robot, invisible hand, James Dyson, Jane Jacobs, Jeff Bezos, jimmy wales, John Gruber, John Markoff, Joseph Schumpeter, Kickstarter, lone genius, longitudinal study, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, new economy, Paul Graham, Peter Thiel, QR code, race to the bottom, reshoring, Richard Florida, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, Tesla Model S, The Chicago School, The Design of Experiments, the High Line, The Myth of the Rational Market, thinkpad, Tim Cook: Apple, too big to fail, tulip mania, We are the 99%, Y Combinator, young professional, Zipcar

id=309165&page=1#.UEu57q60J8E. 121 “We both went to Montessori School”: ABC News, “A Fascinating Group.” 121 Montessori alums include: Peter Sims, “The Montessori Mafia,” Wall Street Journal, April 5, 2011, accessed September 13, 2012, http://blogs.wsj.com/ideas-market/2011/04/05/the-montessori-mafia/. 121 Other entrepreneurs with educational backgrounds: “Google Logo, Founders Spell Success: Montessori,” http://HispanicBusiness.com, August 31, 2012, accessed September 13, 2012, http://www.hispanicbusiness.com/2012/8/31/ google_logo_founders_spell_success_montessori.htm. 121 Paul Graham, the founder of Y Combinator: Randall Stross, The Launch Pad: Inside Y Combinator, Silicon Valley’s Most Exclusive School for Startups (New York: Portfolio, 2012); http://paulgra ham.com/bio.html. 121 Biz Stone, cofounder of Twitter: http://CMO.com, “Twitter Creator Biz Stone Chats with Adobe CMO Lewnes at Digital Summit 2012, http://m.cmo.com/leadership/ twitter-creator-biz-stone-chats-adobe-cmo-lewnes-digital-summit-2012, accessed September 13, 2012. 121 “Being playful, less structured”: Melissa Korn and Amir Efrati, “Master of ’Biz’ Returns to School,” Wall Street Journal, September 1, 2011, accessed September 13, 2012, http://online.wsj.com/article/SB1000142405311190 4009304576533010574207444.html?

It’s perhaps no accident then that Montessori alums include Wikipedia founder Jimmy Wales, Amazon founder Jeff Bezos, Sims video game creator Will Wright, and rap mogul Sean “P. Diddy” Combs. Other entrepreneurs with educational backgrounds in art, design, and music where play is intrinsic to learning have founded a whole slew of new companies, including Kickstarter, Tumblr, YouTube, Flickr, Instagram, Vimeo, Android, and, of course, Apple. And the list goes on and on: Paul Graham, the founder of Y Combinator, one of the top incubators for new start-ups in Silicon Valley, studied painting at Rhode Island School of Design and the Accademia di Belle Arti in Florence, in addition to getting his PhD in computer science from Harvard. Biz Stone, cofounder of Twitter and Xanga, says he learned a valuable lesson studying graphic design. “Being playful, less structured, less hierarchical . . .,” he said as an example of what he might offer to MBA students at the Berkeley Haas School of Business before he became an advisor there.

They set up shop in a bustling area congested with people launching their own businesses. They cultivated a network of people who can help them scale their creativity. They didn’t limit themselves to one platform, looking instead for natural partners in other industries who would “get” them. No matter your field, your pivot network is key to getting your idea into the world. One incubator that nurtures young entrepreneurs and helps them develop their ideas, Y Combinator, was founded on the premise that an entrepreneur’s original idea may not even matter when it comes to building a new company. The important thing is the circle of people who surround the founders, providing the scaling skills and capital necessary for pivoting. So how do you build your own pivot network? Pivoting Organically Starting with those close to you, whether people inside your large organization or your family and friends, is perhaps the most common first step in moving from creativity to creation.


pages: 425 words: 112,220

The Messy Middle: Finding Your Way Through the Hardest and Most Crucial Part of Any Bold Venture by Scott Belsky

23andMe, 3D printing, Airbnb, Albert Einstein, Anne Wojcicki, augmented reality, autonomous vehicles, Ben Horowitz, bitcoin, blockchain, Chuck Templeton: OpenTable:, commoditize, correlation does not imply causation, cryptocurrency, delayed gratification, DevOps, Donald Trump, Elon Musk, endowment effect, hiring and firing, Inbox Zero, iterative process, Jeff Bezos, knowledge worker, Lean Startup, Lyft, Mark Zuckerberg, Marshall McLuhan, minimum viable product, move fast and break things, move fast and break things, NetJets, Network effects, new economy, old-boy network, pattern recognition, Paul Graham, ride hailing / ride sharing, Silicon Valley, slashdot, Snapchat, Steve Jobs, subscription business, TaskRabbit, the medium is the message, Travis Kalanick, Uber for X, uber lyft, Y Combinator, young professional

SOMETIMES A RESET IS THE ONLY WAY FORWARD. “I spent three weeks”: Jennifer Wang, “How 5 Successful Entrepreneurs Bounced Back After Failure,” Entrepreneur, January 23, 2013, www.entrepreneur.com/article/225204. “I was blindsided”: Ibid. “It was painful”: Ibid. The Muse was accepted: Kathryn Minshew, “The Muse’s Successful Application to Y Combinator (W12),” The Muse, accessed March 22, 2018, www.themuse.com/advice/the-muses-successful-application-to-y-combinator-w12. “My heroes, in real life”: Wang, “How 5 Successful Entrepreneurs Bounced Back.” Anthropologie’s “Woman of Character”: “Women of Character: Kathryn Minshew,” Anthropologie, September 30, 2015, www.youtube.com/watch?v=M32tPGYzCXs. EMBRACING THE LONG GAME PLAYING THE LONG GAME REQUIRES MOVES THAT DON’T MAP TO TRADITIONAL MEASURES OF PRODUCTIVITY.

The PYP staff (most of which Minshew hired) joined her, along with one PYP cofounder. The site drew more visitors in its first month than PYP did at its peak. “It was painful, but being forced to start over was a unique sort of gift, because having been through a lot together, the team comes out of it with the confidence that nothing is going to stop us,” Minshew told Entrepreneur. In November 2011, The Muse was accepted into the Y Combinator accelerator program. Today, The Muse is among the most trusted career platforms for millennials, listing jobs and corporate profiles from hundreds of companies like Goldman Sachs, Wells Fargo, Gap, HBO, Condé Nast, and Bloomberg. “My heroes, in real life, tend to be people who either broke through barriers or overcame tremendous obstacles—not only individually, but people who opened up pathways,” Minshew said in Anthropologie’s “Women of Character” feature.

Their success, largely a product of their self-imposed constraints, ultimately led to their acquisition by Google in 2014 for $500 million. Nothing disrupts resourcefulness more than a sudden infusion of resources. The common debate in the early-stage investor community is how much money is too much money at each stage of a business. This is because there are some serious hidden costs that come along with raising capital. Jessica Livingston, cofounder of Y Combinator, one of the world’s most well-known incubators and start-up investors, talked about the perils of raising too much money too quickly during a talk at one of their annual summits: I’ve seen many startups shift from doing more with less to doing less with more once they’ve raised funding. It’s easy to think money can buy your way out of problems. Don’t like sales and calling users? Hire a salesperson.


pages: 353 words: 91,520

Most Likely to Succeed: Preparing Our Kids for the Innovation Era by Tony Wagner, Ted Dintersmith

affirmative action, Airbnb, Albert Einstein, Bernie Sanders, Clayton Christensen, creative destruction, David Brooks, en.wikipedia.org, Frederick Winslow Taylor, future of work, immigration reform, income inequality, index card, Jeff Bezos, jimmy wales, Joi Ito, Khan Academy, Kickstarter, knowledge economy, knowledge worker, low skilled workers, Lyft, Mark Zuckerberg, means of production, new economy, pattern recognition, Paul Graham, Peter Thiel, Ponzi scheme, pre–internet, school choice, Silicon Valley, Skype, Steven Pinker, TaskRabbit, the scientific method, uber lyft, unpaid internship, Y Combinator

But today innovative programs, such as Paul Graham’s Y Combinator, are giving young entrepreneurs powerful learning experiences and a “brand” as powerful as an elite MBA. Y Combinator is every bit as selective as a top business school, but with admissions criteria focused more on a person’s ideas than his or her undergraduate GPA. A young entrepreneur going to business school will study topics, start a business (now mandatory at many programs, including Harvard Business School), develop a network of contacts, and . . . pay substantially more than $100,000 in tuition. At Y Combinator, the student will learn similar topics, start a serious business, develop a powerful network, and get funding for a start-up while paying no tuition. Not surprisingly, Y Combinator and other similar programs are becoming the new “MBA” in the Internet economy, with an emerging sense that spending more than $100,000 for a business credential in 2015 is a bit of a sucker’s play.

See college education University of Chicago, 192 University of Phoenix, 195 University of Washington, 194 Urban Academy, New York City, 247 USA Today, 250 Vander Ark, Tom, 247–48 Vietnam War, in history course, 126, 127 Virtual High School (VHS), 203–04 “Virtually No One Reads What You Write” (blog post), 158–59 vocabulary, 115–17 vocational training, 244–45 voting patterns, 20, 67–68, 70–71, 74, 174 Wagner, Tony, 1–3, 5–6, 9, 34, 47, 50, 55, 64, 72, 103, 104, 105, 111, 143, 149–50, 159, 161, 178, 179, 214, 216, 238–39, 247, 260, 262, 265–66 Waiting for Superman (documentary film), 56, 250 Waldorf schools, 85 Wales, Jimmy, 85 Wallace, William, 128 Wall Street Journal, 85, 170 Walters, Barbara, 85 Walton family, 250 Warriner’s Handbook, 111 Washington Post, 218 Washington University, 198 Washor, Elliot, 247 Wellesley, Massachusetts, schools, 215–16 We’re Losing Our Minds (Keeling and Hersh), 149, 157, 160, 162 white-collar jobs, 25–26, 27, 33, 43 Whiteley, Greg, 3, 9, 114 Wiggins, Grant, 227 Winning the Brain Race (Kearns and Doyle), 225 Wolfe, Kristen, 167 Wolfe, Rachel, 46–47 Wolfram, Conrad, 94–95 WolframAlpha, 94, 95, 98 workplace. See employment World Is Flat, The (Friedman), 61 Wright, Frank Lloyd, 24 writing courses, 105–11 importance of, 103–04, 105 mechanics of writing taught in, 110, 111 practice needed in, 105, 110–11 standardized tests and, 106–10 20th-century model of, 102–03 “writers’ workshop” approach to teaching, 105 See also English language courses Xamarin, 62 Yale University, 173, 186, 187 Y Combinator, 243 Yen, Hope, 166 Yerkes, Robert, 206 YouTube, 192, 237, 245 Zhao, Yong, 54, 55–56 Zuckerberg, Mark, 187, 250 Zverev, Nikolai, 24 SCRIBNER An Imprint of Simon & Schuster, Inc. 1230 Avenue of the Americas New York, NY 10020 www.SimonandSchuster.com Copyright © 2015 by Tony Wagner and Ted Dintersmith All rights reserved, including the right to reproduce this book or portions thereof in any form whatsoever.


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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

, The Independent, 2 May 2014. http://www.independent.co.uk/news/science/stephen-hawking-transcendence-looks-at-the-implications-of-artificial-intelligence-but-are-we-taking-9313474.html 61 Greg Brockman, Ilya Sutskever & the OpenAI team, “Introducing OpenAI”, 11 December 2015 https://openai.com/blog/introducing-openai/ 62 Steven Levy, “How Elon Musk and Y Combinator Plan to Stop Computers From Taking Over”, 11 December 2015 https://medium.com/backchannel/how-elon-musk-and-y-combinator-plan-to-stop-computers-from-taking-over-17e0e27dd02a#.qjj55npcj 63 Sara Konrath, Edward O’Brien, and Courtney Hsing. “Changes in dispositional empathy in American college students over time: A meta-analysis.” Personality and Social Psychology Review (2010). 64 Quoted in: Simon Kuper, “Log out, switch off, join in”, FT Magazine, 2 October 2015. http://www.ft.com/intl/cms/s/0/fc76fce2-67b3-11e5-97d0-1456a776a4f5.html 65 Sherry Turkle, Reclaiming Conversation: The Power of Talk in a Digital Age, Penguin, 2015. 66 Nicholas Carr, The Shallows: How the Internet is changing the way we think, read and remember, Atlantic Books, 2010. 67 Pico Iyer, The Art of Stillness: Adventures in Going Nowhere, Simon and Schuster, 2014. 68 Quoted in: Elizabeth Segran, “The Ethical Quandaries You Should Think About the Next Time You Look at Your Phone”, Fast Company, 5 October 2015.

As theoretical physicist and author Stephen Hawking and fellow scientists Stuart Russell, Max Tegmark and Frank Wilczek wrote in the newspaper The Independent when considering the implications of artificial intelligence: “Whereas the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all…All of us should ask ourselves what we can do now to improve the chances of reaping the benefits and avoiding the risks”.60 One interesting development in this area is OpenAI, a non-profit AI research company announced in December 2015 with the goal to “advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return”.61 The initiative – chaired by Sam Altman, President of Y Combinator, and Elon Musk, CEO of Tesla Motors - has secured $1 billion in committed funding. This initiative underscores a key point made earlier – namely, that one of the biggest impacts of the fourth industrial revolution is the empowering potential catalyzed by a fusion of new technologies. Here, as Sam Altman stated, “the best way AI can develop is if it’s about individual empowerment and making humans better, and made freely available to everyone.”62 The human impact of some particular technologies such as the internet or smart phones is relatively well understood and widely debated among experts and academics.


Falter: Has the Human Game Begun to Play Itself Out? by Bill McKibben

23andMe, Affordable Care Act / Obamacare, Airbnb, American Legislative Exchange Council, Anne Wojcicki, artificial general intelligence, Bernie Sanders, Bill Joy: nanobots, Burning Man, call centre, carbon footprint, Charles Lindbergh, clean water, Colonization of Mars, computer vision, David Attenborough, Donald Trump, double helix, Edward Snowden, Elon Musk, ending welfare as we know it, energy transition, Flynn Effect, Google Earth, Hyperloop, impulse control, income inequality, Intergovernmental Panel on Climate Change (IPCC), Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, life extension, light touch regulation, Mark Zuckerberg, mass immigration, megacity, Menlo Park, moral hazard, Naomi Klein, Nelson Mandela, obamacare, off grid, oil shale / tar sands, pattern recognition, Peter Thiel, plutocrats, Plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, Robert Mercer, Ronald Reagan, Sam Altman, self-driving car, Silicon Valley, Silicon Valley startup, smart meter, Snapchat, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, supervolcano, technoutopianism, The Wealth of Nations by Adam Smith, traffic fines, Travis Kalanick, urban sprawl, Watson beat the top human players on Jeopardy!, Y Combinator, Y2K, yield curve

Amortized across the Earth’s entire population, Merkle estimates a “surprisingly competitive” price of $24 to $32 per person.12 Currently, at least a thousand people are waiting for their chance, and they include a large selection of Silicon Valley pioneers. This being the tech industry, though, a newer iteration of the idea is already available. Nectome is one of the handful of start-ups chosen to be part of Y Combinator, the most important of California’s tech incubators. (They’re the people who first championed Dropbox, Airbnb, and Reddit.) In fact, Y Combinator head Sam Altman has already plunked down his $10,000 for Nectome’s service, which involves embalming your brain when you’re near death so that it can later be digitized and encoded. “The idea is that someday in the future scientists will scan your bricked brain and turn it into a computer simulation,” writes Antonio Regalado in MIT Technology Review.13 In fact, this notion that we will one day be meshed with computers and thus live forever has gained currency perhaps because, while bizarre, it seems somehow less absurd than the idea of Ted Williams lumbering around again in the real world.

It’s the ultimate in what the business gurus happily call disruption, and it’s been a siren song for entrepreneurs with ambitions higher than the next Snapchat plug-in. Helgesen, for instance. Tall, with long lank hair, he could be the bassist in an indie band, but the Y Combinator T-shirt he’s wearing gives the game away. He didn’t actually do a stint at Silicon Valley’s most famous incubator (his wife did), but that’s his lineage, the same one that produced Airbnb and also the company that wants to embalm your brain so you can be digitally scanned and reimplanted in an android. The Y Combinator T-shirt reads, “Make Something People Want,” which pretty much defines cheap solar power. Africans are desperate for electricity. * * * “This is how the solar revolution happens,” Kim Schreiber, Off-Grid’s communications director, whispers to me.

Supreme Court Unity Biotechnology Urban, Tim USA Today Utah utilities Vanity Fair vapor pressure deficit Vassar, Michael Venezuela Venice Verity, William Vermont Vietnam Vinci, Leonardo da Virgin Galactic Virtue of Selfishness, The (Rand) Vodafone volcanoes voting rights Walker, Scott Wall Street Journal Walton family Washington Post water Watson, James Wealth of Nations (Smith) welfare West, Michael wet-bulb temperature wheat Whippman, Ruth White, Curtis Whitehead, Emily white supremacy wilderness, protected wildlife Wilkinson, Richard Williams, Jerry Williams, Ted wind power Wired Wisconsin Wohlforth, Charles Wojcicki, Anne Wojcicki, Stanley Wojcicki, Susan women’s rights Woods, Darren World Bank World Happiness Report World Meteorological Organization World Petroleum Congress (Beijing, 1997) World War II Worster, Donald Wozniak, Steve Y Combinator Yellowstone Yosemite Valley Youtube Yudkowsky, Eliezer Zhang, Feng Zinke, Ryan Zuckerberg, Mark ALSO BY BILL McKIBBEN Radio Free Vermont Oil and Honey The Global Warming Reader Eaarth American Earth The Bill McKibben Reader Fight Global Warming Now Deep Economy The Comforting Whirlwind Wandering Home Enough Long Distance Hundred Dollar Holiday Maybe One Hope, Human and Wild The Age of Missing Information The End of Nature ABOUT THE AUTHOR BILL MCKIBBEN is a founder of the environmental organization 350.org and was among the early advocates for action on global warming.


pages: 567 words: 122,311

Lean Analytics: Use Data to Build a Better Startup Faster by Alistair Croll, Benjamin Yoskovitz

Airbnb, Amazon Mechanical Turk, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, barriers to entry, Bay Area Rapid Transit, Ben Horowitz, bounce rate, business intelligence, call centre, cloud computing, cognitive bias, commoditize, constrained optimization, en.wikipedia.org, Firefox, Frederick Winslow Taylor, frictionless, frictionless market, game design, Google X / Alphabet X, Infrastructure as a Service, Internet of things, inventory management, Kickstarter, lateral thinking, Lean Startup, lifelogging, longitudinal study, Marshall McLuhan, minimum viable product, Network effects, pattern recognition, Paul Graham, performance metric, place-making, platform as a service, recommendation engine, ride hailing / ride sharing, rolodex, sentiment analysis, skunkworks, Skype, social graph, social software, software as a service, Steve Jobs, subscription business, telemarketer, transaction costs, two-sided market, Uber for X, web application, Y Combinator

* * * [69] http://larsleckie.blogspot.ca/2008/03/magic-number-for-saas-companies.html [70] The Parse.ly team has written a detailed explanation of these changes at http://blog.parse.ly/post/16388310218/hello-publishers-meet-dash. [71] Mike is quick to point out that this is changing, with an increased emphasis on revenue generation. See http://go.bloomberg.com/tech-deals/2012-08-22-y-combinators-young-startups-tout-revenue-over-users/. [72] http://www.slideshare.net/sixteenventures/the-reality-of-freemium-in-saas Chapter 19. Stage Five: Scale You have a product that’s sticky. You’ve got virality that’s multiplying the effectiveness of your marketing efforts. And you have revenues coming in to fuel those user and customer acquisition efforts. The final stage for startups is Scale, which represents not only a wider audience, but also entry into new markets, a modicum of predictability and sustainability, and deals with new partners.

In fact, it’s this growth that distinguishes a startup from other new ventures like a cobbler or a restaurant. Startups, Paul says, go through three distinct growth phases: slow, where the organization is searching for a product and market to tackle; fast, where it has figured out how to make and sell it at scale; and slow again, as it becomes a big company and encounters internal constraints or market saturation, and tries to overcome Porter’s “hole in the middle.” At Paul’s startup accelerator, Y Combinator, teams track growth rate weekly because of the short timeframe. “A good growth rate during YC is 5–7% a week,” he says. “If you can hit 10% a week you’re doing exceptionally well. If you can only manage 1%, it’s a sign you haven’t yet figured out what you’re doing.” If the company is at the Revenue stage, then growth is measured in revenue; if it’s not charging money yet, growth is measured in active users.

When this happens, growth eventually falls off a cliff.”[79] He goes on to say, “Sustainable growth programs are built on a core understanding of the value of your solution in the minds of your most passionate customers.” As we saw in Chapter 5, Sean’s Startup Growth Pyramid illustrates that scaling your business comes only after you’ve found product/market fit and your unfair advantage. In other words: stickiness comes before virality, and virality comes before scale. Most Y Combinator startups (and most startups, for that matter) focus on growth before they hit product/market fit. In some cases this is a necessity, particularly if the value of the startup depends on a network effect—after all, Skype’s no good if nobody else is using it. But while rapid growth can accelerate the discovery of product/market fit, it can just as easily destroy the startup if the timing isn’t right.


pages: 292 words: 85,151

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

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

Find co-founders, contractors and experts. Use crowdfunding and crowdsourcing to validate market demand and as a marketing technique. Algorithms: Identify data streams that can be automated and help with product development. Implement cloud-based and open source machine and deep learning to increase insights. Leveraged Assets: Do NOT acquire assets. Use cloud computing, TechShop for product development. Use incubators like Y Combinator and Techstars for office, funding, mentoring and peer input. Starbucks as office. Engagement: Design product with engagement in mind. Gather all user interactions. Gamify where possible. Create a digital reputational system of users and suppliers to build trust and community. Use incentive prizes to engage crowd and create buzz. Interfaces: Design custom processes for managing SCALE; do not automate until you’re ready to scale.

Celebrated—even recognized—or not, open source software runs the Internet (and thus the world) today. After that extraordinary initial success, the open source movement settled into a stable, stratified environment over much the last decade, with the community producing little in the way of new innovation. Everything changed in 2008, however, when Chris Wanstrath, P.J. Hyett and Tom Preston-Werner (all out of Paul Graham’s Y Combinator entrepreneurial incubator program) founded a company called GitHub. An open source coding and collaboration tool and platform, GitHub has utterly transformed the open source environment. It is a social network for programmers in which people and their collaborations are central, rather than just the code itself. When a developer submits code to a GitHub project, that code is reviewed and commented upon by other developers, who also rate that developer.

Finally, a 3D printer carried a $40,000 price tag seven years ago; today it costs just $100. In short, Moore’s Law is the modern lab’s best friend. Recommendation: Start an internal accelerating technologies lab, leveraging core competencies and aiming for moonshot innovations at a budget price. Partner with Accelerators, Incubators and Hackerspaces The last decade has seen an explosion of new business incubators and accelerators, ranging from Y Combinator (which created disruptive consumer Internet startups Dropbox and Uber) to the membership-based TechShop. Looking at large companies from an ExO perspective, let’s consider four examples: TechShop We first examined TechShop’s fascinating model in Chapter Three. Here we’ll explore the chain’s impact in further detail, focusing on how TechShop is helping large organizations, including Ford and Lowe’s, two companies for which it has built individual facilities.


pages: 307 words: 88,180

AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee

AI winter, Airbnb, Albert Einstein, algorithmic trading, artificial general intelligence, autonomous vehicles, barriers to entry, basic income, business cycle, cloud computing, commoditize, computer vision, corporate social responsibility, creative destruction, crony capitalism, Deng Xiaoping, deskilling, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, full employment, future of work, gig economy, Google Chrome, happiness index / gross national happiness, if you build it, they will come, ImageNet competition, income inequality, informal economy, Internet of things, invention of the telegraph, Jeff Bezos, job automation, John Markoff, Kickstarter, knowledge worker, Lean Startup, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, Menlo Park, minimum viable product, natural language processing, new economy, pattern recognition, pirate software, profit maximization, QR code, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, risk tolerance, Robert Mercer, Rodney Brooks, Rubik’s Cube, Sam Altman, Second Machine Age, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, special economic zone, speech recognition, Stephen Hawking, Steve Jobs, strong AI, The Future of Employment, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, urban planning, Y Combinator

At the time, advocates saw a GMI as a simple way to end poverty, and in 1970 President Nixon actually came close to passing a bill that would have granted each family enough money to raise itself above the poverty line. But following Nixon’s unsuccessful push, discussion of a UBI or GMI largely dropped out of public discourse. That is, until Silicon Valley got excited about it. Recently, the idea has captured the imagination of the Silicon Valley elite, with giants of the industry like the prestigious Silicon Valley startup accelerator Y Combinator president Sam Altman and Facebook cofounder Chris Hughes sponsoring research and funding basic income pilot programs. Whereas GMI was initially crafted as a cure for poverty in normal economic times, Silicon Valley’s surging interest in the programs sees them as solutions for widespread technological unemployment due to AI. The bleak predictions of broad unemployment and unrest have put many of the Silicon Valley elite on edge.

To these proponents, massive redistribution schemes are potentially all that stand between an AI-driven economy and widespread joblessness and destitution. Job retraining and clever scheduling are hopeless in the face of widespread automation, they argue. Only a guaranteed income will let us avert disaster during the jobs crisis that looms ahead. How exactly a UBI would be implemented remains to be seen. A research organization associated with Y Combinator is currently running one pilot program in Oakland, California, that gives a thousand families a stipend of a thousand dollars each month for three to five years. The research group will track the well-being and activities of those families through regular questionnaires, comparing them with a control group that receives just fifty dollars per month. Many in Silicon Valley see the program through the lens of their own experience as entrepreneurs.

A BLUEPRINT FOR HUMAN COEXISTENCE WITH AI move to a four-day work week: Seth Fiegerman, “Google Founders Talk About Ending the 40-Hour Work Week,” Mashable, July 7, 2014, https://mashable.com/2014/07/07/google-founders-interview-khosla/#tXe9XU.mr5qU. creative approaches to work-sharing: Steven Greenhouse, “Work-Sharing May Help Companies Avoid Layoffs,” New York Times, June 15, 2009, http://www.nytimes.com/2009/06/16/business/economy/16workshare.html. Y Combinator president Sam Altman: Kathleen Pender, “Oakland Group Plans to Launch Nation’s Biggest Basic-Income Research Project,” San Francisco Chronicle, September 21, 2017, https://www.sfchronicle.com/business/networth/article/Oakland-group-plans-to-launch-nation-s-biggest-12219073.php. Facebook cofounder Chris Hughes: The Economic Security Project, https://economicsecurityproject.org/. gives a thousand families a stipend: Pender, “Oakland Group.”


pages: 313 words: 91,098

The Knowledge Illusion by Steven Sloman

Affordable Care Act / Obamacare, Air France Flight 447, attribution theory, bitcoin, Black Swan, Cass Sunstein, combinatorial explosion, computer age, crowdsourcing, Dmitri Mendeleev, Elon Musk, Ethereum, Flynn Effect, Hernando de Soto, hindsight bias, hive mind, indoor plumbing, Isaac Newton, John von Neumann, libertarian paternalism, Mahatma Gandhi, Mark Zuckerberg, meta analysis, meta-analysis, obamacare, prediction markets, randomized controlled trial, Ray Kurzweil, Richard Feynman, Richard Thaler, Rodney Brooks, Rosa Parks, single-payer health, speech recognition, stem cell, Stephen Hawking, Steve Jobs, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Vernor Vinge, web application, Whole Earth Review, Y Combinator

As one of them, Avin Rabheru, puts it: “Venture capitalists back teams, not ideas.” Consider the view of Y Combinator, one of the leading incubators of early-stage technology start-ups. Their strategy is based on the belief that successful start-ups rarely, if ever, capitalize on their initial idea. Ideas transform. So it’s not ideas that matter the most. Far more important than the quality of an idea is the quality of the team. A good team can make a start-up successful because it can discover a good idea by learning how a market works and then do the work to implement the idea. A good team will divide and distribute the labor in a way that takes advantage of individual skills. Y Combinator avoids investing in start-ups that have a single founder not only because a single founder means there’s no team to divide up the labor.

See also artificial intelligence (AI); Internet ability to self-update and solve its own problems, 135–36 adaptation of the body to new tools, 134 automation paradox, 141–45 block chain, 150 Bodmer Report, 156–59 crowdsourcing, 146–49 effects on information and commerce, 131–32 genetic engineering, 154–55, 165–67 GPS (Global Positioning System) software, 139–40, 143 as a living organism, 134–35 Luddites’ protests against, 153–54 machines’ lack of collaborative ability, 139–42 predictions about the future, 150–52 relationship between brain size and technological change, 133–34 superintelligence, 132–33, 146 venture capital funding, 211–12 Y Combinator funding, 211–12 testing intelligence. See also intelligence Binet, Alfred, 203 c factor, 209–11 collective intelligence hypothesis, 209–10 computer checkers example, 210–11 correlation of performance results, 204, 209–10 factor analysis, 204–05 g score, 204–07 Simon, Theodore, 203 Spearman, Charles, 204 of a team, 209–14 Woolley, Anita, 209–10 Thaler, Richard, 247, 250–51 thermostat mechanics example of causal reasoning, 72–73 thinking.

See also cognitive science causality, 11–12 counterfactual, 64–65 intuition vs. deliberation, 75–84 Kahneman, Daniel, 76 location of the mind, 101–05 purpose of, 10–11 reflection, human ability of, 145–46 vs. action, 11, 65 “tickling the dragon’s tail” experiment, 19–20 toilet design people’s ignorance of, 6–8 siphon action, 7 Tomasello, Michael, 116 tools as an extension of the body, 134 Turing, Alan, 25 understanding confused with familiarity or recognition, 217–18 gathering information to increase, 252–53 “unknown unknowns,” 32–33 vaccination opposition, 155–56, 159, 168 values abortion, 183, 184 assisted suicide, 183, 184 gay marriage, 186 health care, 184–85 Iranian attitudes about nuclear capabilities example, 185–86 Israeli-Palestinian conflict example, 186–87 Julie and Mark example, 181–82 moral dumbfounding, 181–82 as a result of intuitions and feelings without reasoning, 181–83 taboo activities, condemnation of, 182 vs. consequences arguments, 182–87 Venus flytrap, capabilities of a, 41 vesting service letter example of explanation foes and fiends, 243–44 Vinge, Vernor, 132 vision bee example of optic flow, 100 Danny DeVito example of facial recognition, 45–46 doorway example of optic flow, 99–100 facial recognition, 45–46 fly ball example of gaze-direction strategy, 96–98 gaze-direction strategy, 96–98 highway lines example of optic flow, 99 lateral inhibition, 43–45 wheat field example of optic flow, 98–99 Vox Populi (“The Wisdom of Crowds”) (Galton), 148 Vygotsky, Lev, 115–16 walking in a forest example of excessive computations, 89–90 Wanted (film), 69–70 Ward, Adrian, 136–37, 138, 247 watering can handle example of body and brain cooperation, 101–02 water rationing example of causal explanation, 178 weather prediction example of complexity, 30–31 WebMD diagnosis study, 138–39 Wegner, Daniel, 120 wheat field example of optic flow, 98–99 wine expert example of division of cognitive labor, 120 women’s suffrage movement, 196 Woodward, Susan, 233–34 World Trade Center, 32–33 Yap economy, 245 Y Combinator, 211–12 Zheng, Yanmei, 168 zipper example of the illusion of explanatory depth (IoED), 21–23 About the Authors STEVEN SLOMAN is a professor of cognitive, linguistic, and psychological sciences at Brown University. He is the editor in chief of the journal Cognition. He lives with his wife in Providence, Rhode Island. His two children have flown the coop. PHILIP FERNBACH is a cognitive scientist and professor of marketing at the University of Colorado’s Leeds School of Business.


pages: 232 words: 63,846

Traction: How Any Startup Can Achieve Explosive Customer Growth by Gabriel Weinberg, Justin Mares

Airbnb, Firefox, if you build it, they will come, jimmy wales, Justin.tv, Lean Startup, Marc Andreessen, Mark Zuckerberg, Network effects, Paul Graham, Peter Thiel, side project, Skype, Snapchat, social graph, software as a service, the payments system, Uber for X, web application, working poor, Y Combinator

So if you’re in enterprise software, [initial traction] may be two or three early customers who are paying a bit; if you’re in consumer software the bar might be as high as hundreds of thousands of users. You can always get more traction. The whole point of a startup is to grow rapidly. Getting traction means moving your growth curve up and to the right as best you can. Paul Graham, founder of startup accelerator Y Combinator, puts it like this: A startup is a company designed to grow fast. Being newly founded does not in itself make a company a startup. Nor is it necessary for a startup to work on technology, or take venture funding, or have some sort of “exit.” The only essential thing is growth. Everything else we associate with startups follows from growth. Traction is growth. The pursuit of traction is what defines a startup.

Without you this book would not be possible: Jimmy Wales, Cofounder of Wikipedia Alexis Ohanian, Cofounder of reddit Eric Ries, Author of The Lean Startup Rand Fishkin, Founder of Moz Noah Kagan, Founder of AppSumo Patrick McKenzie, CEO of Bingo Card Creator Sam Yagan, Cofounder of OkCupid Andrew Chen, Investor in 500 Startups Dharmesh Shah, Founder of HubSpot Justin Kan, Founder of Justin.tv Mark Cramer, CEO of Surf Canyon Colin Nederkoorn, CEO of Customer.io Jason Cohen, Founder of WP Engine Chris Fralic, Partner at First Round Capital Paul English, CEO of Kayak Rob Walling, Founder of MicroConf Brian Riley, Cofounder of SureStop Steve Welch, Cofounder of DreamIt Jason Kincaid, Blogger at TechCrunch Nikhil Sethi, Founder of Adaptly Rick Perreault, CEO of Unbounce Alex Pachikov, Evernote Founding Team David Skok, Partner at Matrix Ashish Kundra, CEO of myZamana David Hauser, Founder of Grasshopper Matt Monahan, CEO of Inflection Jeff Atwood, Cofounder of Discourse Dan Martell, CEO of Clarity Chris McCann, Founder of Startup Digest Ryan Holiday, Exec at American Apparel Todd Vollmer, Enterprise Sales Veteran Sandi MacPherson, Founder of Quibb Andrew Warner, Founder of Mixergy Sean Murphy, Founder of SKMurphy Satish Dharmaraj, Partner at Redpoint Ventures Garry Tan, Partner at Y Combinator Steve Barsh, CEO of PackLate Michael Bodekaer, Cofounder of Smartlaunch Each of you played a critical role in shaping this book and making it a useful resource. We apologize if we left anyone off this list. We’d also like to thank our early readers for their helpful comments and feedback, as well as Eric Nelson, Michael Zakhar, and Brian Spadora for their editing help. Additional thanks to Eve Weinberg for pulling together our initial cover and Chris Morast and Doug Brown for producing a beautiful Web site and book.

See also specific channels overview, 2–7 traction development, 9–12, 17 traction goals, 12–15, 18, 35–36, 139 defining your Critical Path, 37–38 traction subgoals, 36 traction testing, 21–22, 27–34 inner ring tests, 22–23, 28–31 middle ring tests, 21, 27–28, 209–13 online tools, 32–33 targets, 33–34 traction thinking, 2, 8–18 50 percent rule, 8–12 fund-raising, 15–16 moving the needle, 12–15 targets, 17–18 when to “pivot,” 16–17 trade show booths, 179–81, 182 trade shows, 7, 22, 175–82, 212–13 strategy, 176–77 tactics, 177–81 targets, 181–82 Trainyard, 168, 169 transit advertising, 88 Tribal Fusion, 75 TripAdvisor, 98 Trust Me, I’m Lying (Holiday), 3, 49, 50 Tumblr, 80 TV advertising, 88–90 Twilio, 183 Twitter, 170–71, 184–85 email marketing, 112–13 reaching out to reporters online, 53–54 social ads, 4, 31, 78, 79 targeting blogs, 46 Uber, 57, 94, 120, 121 Unbounce, 5, 29, 102–7, 110 unconventional PR, 3–4, 57–64, 210 case study of David Hauser, 62–63 customer appreciation, 58, 59–61 publicity stunts, 57–59 targets, 63–64 Upfront Ventures, 154, 178–79 Upromise, 160–61 URL Builder, 69 UserTesting.com, 125 UserVoice, 120 Vero, 112 vertical search sites, 161 Vine, 170 viral coefficient, 121–23, 126, 211 viral cycle time, 121, 123, 128 viral loops, 119–21, 123–24, 126, 127–28 viral marketing, xi, 5, 23, 118–25, 211 strategy, 119–23 tactics, 123–26 targets, 127–28 viral pockets, 126, 128 Virgin Galactic, 57–58 Visual Website Optimizer, 29, 70 Vollmer, Todd, 151 Volpe, Mike, 100 Walling, Rob, 7, 186–87, 188–89 Wall Street, 52 Walmart, 82, 160 Warby Parker, 79 Washington Post, 48, 142, 144–45 Weebly, 120 Wendy’s, 89 WePay, 58–59 WhatsApp, 120 widgets, 99, 129, 133 Wikipedia, 7, 98, 199, 201 Williams, Evan, 184–85 Wilson, Fred, 106 Winfrey, Oprah, 50 word of mouth, 120, 127 WordPress, 114, 131 WP Engine, 4, 113–14, 131, 175 writer’s block, 105 Yagan, Sam, 5, 103, 104–5 Yahoo!, 137–38 Y Combinator, 2 yellow pages, ads in, 86 Yelp, 98, 184, 188, 198, 201, 202 YouTube, 4, 44, 46, 59, 81, 120–21, 170 Zappos, 61, 159, 160 Zuckerberg, Mark, 191 Zynga, 31 Looking for more? Visit Penguin.com for more about this author and a complete list of their books. Discover your next great read!


pages: 359 words: 96,019

How to Turn Down a Billion Dollars: The Snapchat Story by Billy Gallagher

Airbnb, Albert Einstein, Amazon Web Services, Apple's 1984 Super Bowl advert, augmented reality, Bernie Sanders, Black Swan, citizen journalism, Clayton Christensen, computer vision, disruptive innovation, Donald Trump, El Camino Real, Elon Musk, Frank Gehry, Google Glasses, Hyperloop, information asymmetry, Jeff Bezos, Justin.tv, Lean Startup, Long Term Capital Management, Mark Zuckerberg, Menlo Park, minimum viable product, Nelson Mandela, Oculus Rift, paypal mafia, Peter Thiel, QR code, Sand Hill Road, Saturday Night Live, side project, Silicon Valley, Silicon Valley startup, Snapchat, social graph, sorting algorithm, speech recognition, stealth mode startup, Steve Jobs, too big to fail, Y Combinator, young professional

Broadcasting 24/7 was just too much time and involved too many boring moments. With Snapchat, Kan distills an entire day down to two to three minutes of the most interesting ten-second photos and videos. Kan leaves his messages open for his eleven thousand followers and typically gets ten messages an hour.2 In May 2016, Kan worked as a partner at the prestigious startup incubator Y Combinator; he let his followers apply to take over his Snapchat account for an hour and pitch their startup for funding from Y Combinator. Eventually, Kan and Y Combinator funded three startups from over four hundred applicants. * * * Venture capital money isn’t just headed to companies pitching on Snapchat. Investors are funding Snapchat-content companies, too. On an unusually windy afternoon in March 2016, I grabbed a coffee from Groundwork Coffee Co. in Venice, a couple blocks down the boardwalk from Snapchat’s main headquarters.

Miami (Michael Salzhauer) Thiel, Peter third-party content (Snapchat Discover) Thompson, Nicholas Thorning-Schmidt, Helle TigerText (app) Tinder Trainor, Meghan Trump, Donald Turley, Ben Turner, Elizabeth Turner, Sarah Twitter demographics of users innovation and Snapchat account at Snapchat compared with txtWeb Uber Valleywag (Gawker blog) Van Natta, Owen Vanity Fair Venice, California Venmo Vergence Labs Vine (app) virtual private network (VPN) Viterbi, Andrew VMWare Vollero, Drew Warner Music Group WeChat (app) Weiner, Anthony Wendell, Peter WhatsApp Whisper (app) White, Emily Wiley, Marcus Wilson, Ryan (ThankYouX) Wolf, Michelle Y Combinator Yahoo Yelp YesJulz (Julieanna Goddard) Yik Yak (app) YouTube Zedd Zero to One (Masters and Thiel) Zuckerberg, Mark ABOUT THE AUTHOR BILLY GALLAGHER is an MBA candidate at Stanford’s Graduate School of Business. Previously, he was a member of the investment team at Khosla Ventures and a writer at TechCrunch, which he joined as a Stanford sophomore, writing a profile of a popular startup on campus: Snapchat.


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, Metcalfe’s law, Netflix Prize, new economy, PageRank, paypal mafia, Peter Thiel, recommendation engine, RFID, Robert Metcalfe, 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

Once you’re on the road to mass success and riches—often as a very young coder—there simply isn’t much time to fully think all of this through. And the pressure of the venture capitalists breathing down your neck to “monetize” doesn’t always offer much space for rumination on social responsibility. The $50 Billion Sand Castle Once a year, the Y Combinator start-up incubator hosts a daylong conference called Startup School, where successful tech entrepreneurs pass wisdom on to the aspiring audience of bright-eyed Y Combinator investees. The agenda typically includes many of the top CEOs in Silicon Valley, and in 2010, Mark Zuckerberg was at the top of the list. Zuckerberg was in an affable mood, dressed in a black T-shirt and jeans and enjoying what was clearly a friendly crowd. Even so, when Jessica Livingston, his interviewer, asked him about The Social Network, the movie that had made him a household name, a range of emotions crossed his face.

Walker social capital social graph Social Graph Symposium Social Network, The Solove, Daniel solution horizon Startup School Steitz, Mark stereotyping Stewart, Neal Stryker, Charlie Sullivan, Danny Sunstein, Cass systematization Taleb, Nassim Nicholas Tapestry TargusInfo Taylor, Bret technodeterminism technology television advertising on mean world syndrome and Tetlock, Philip Thiel, Peter This American Life Thompson, Clive Time Tocqueville, Alexis de Torvalds, Linus town hall meetings traffic transparency Trotsky, Leon Turner, Fred Twitter Facebook compared with Últimas Noticias Unabomber uncanny valley Upshot Vaidhyanathan, Siva video games Wales, Jimmy Wall Street Journal Walmart Washington Post Web site morphing Westen, Drew Where Good Ideas Come From (Johnson) Whole Earth Catalog WikiLeaks Wikipedia Winer, Dave Winner, Langdon Winograd, Terry Wired Wiseman, Richard Woolworth, Andy Wright, David Wu, Tim Yahoo News Upshot Y Combinator Yeager, Sam Yelp You Tube LeanBack Zittrain, Jonathan Zuckerberg, Mark Table of Contents Title Page Copyright Page Dedication Introduction Chapter 1 - The Race for Relevance Chapter 2 - The User Is the Content Chapter 3 - The Adderall Society Chapter 4 - The You Loop Chapter 5 - The Public Is Irrelevant Chapter 6 - Hello, World! Chapter 7 - What You Want, Whether You Want It or Not Chapter 8 - Escape from the City of Ghettos Acknowledgements FURTHER READING NOTES INDEX


pages: 477 words: 75,408

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

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

[xcvii] IBM says that its cognitive computing business, which depends heavily on machine learning, now accounts for over a third of its $81 billion annual revenues, and is the main focus for the company’s growth. IBM Watson’s best-known work today is in the medical sector, but it is also carrying out large-scale projects in food safety with Mars, and in personality profiling for recruitment firms and dating apps.[xcviii] In December 2015, Elon Musk and Sam Altman, president of the technology incubator Y Combinator announced the formation of a new company called Open AI. They had recruited a clutch of the top machine learning professionals despite the efforts of Google and Facebook to hang onto them with eye-watering financial offers. There is some uncertainty about whether other companies controlled by Musk and Altman (like Tesla and Solar City) will have privileged access to technologies developed at Open AI, but the thrust of the company is to make advanced AI techniques more widely available in the hope that will de-risk them.

All these initiatives are looking for ways to tackle problems with existing social welfare systems. We have to go to Silicon Valley to find an experiment specifically designed to explore the impact of UBI in the context of a jobless future when machine intelligence has automated most of what we currently do for a living. Just such an experiment was announced in January 2016 by Sam Altman, president of the seed capital firm Y Combinator, which gave a start in life to Reddit, AirBnB and DropBox. Altman's task is not trivial: he will have to figure out a way to quantify the satisfaction his guinea pigs derive from their UBI, and whether they are doing anything useful with their time.[cccv] Socialism? With all these experiments bubbling up, the concept of UBI has become a favourite media topic, but it is controversial. Many opponents – especially in the US – see it as a form of socialism, and the US has traditionally harboured a visceral dislike of socialism.

[ccxcii] http://money.cnn.com/2015/06/23/investing/facebook-walmart-market-value/ [ccxciii] http://quoteinvestigator.com/2011/11/16/robots-buy-cars/ [ccxciv] http://thegreatdepressioncauses.com/unemployment/ [ccxcv] http://www.statista.com/statistics/268830/unemployment-rate-in-eu-countries/ [ccxcvi] http://www.statista.com/statistics/266228/youth-unemployment-rate-in-eu-countries/ [ccxcvii] http://www.scottsantens.com/ [ccxcviii] http://www.economonitor.com/dolanecon/2014/01/27/a-universal-basic-income-conservative-progressive-and-libertarian-perspectives-part-3-of-a-series/ [ccxcix] https://www.reddit.com/r/BasicIncome/wiki/index#wiki_that.27s_all_very_well.2C_but_where.27s_the_evidence.3F [ccc] https://www.reddit.com/r/BasicIncome/wiki/studies [ccci] http://basicincome.org.uk/2013/08/health-forget-mincome-poverty/ [cccii] http://fivethirtyeight.com/features/universal-basic-income/?utm_content=buffer71a7e&utm_medium=social&utm_source=plus.google.com&utm_campaign=buffer [ccciii] http://www.fastcoexist.com/3052595/how-finlands-exciting-basic-income-experiment-will-work-and-what-we-can-learn-from-it [ccciv] http://www.latimes.com/world/europe/la-fg-germany-basic-income-20151227-story.html [cccv] http://www.vox.com/2016/1/28/10860830/y-combinator-basic-income [cccvi] https://en.wikipedia.org/wiki/Sodomy_laws_in_the_United_States#References [cccvii] http://blogs.wsj.com/washwire/2015/03/09/support-for-gay-marriage-hits-all-time-high-wsjnbc-news-poll/ [cccviii] http://www.huffingtonpost.com/2009/05/06/majority-of-americans-wan_n_198196.html [cccix] http://blogs.seattletimes.com/today/2013/08/washingtons-pot-law-wont-get-federal-challenge/ [cccx] http://www.bbc.co.uk/news/magazine-35525566 [cccxi] https://medium.com/basic-income/wouldnt-unconditional-basic-income-just-cause-massive-inflation-fe71d69f15e7#.3yezsngej [cccxii] http://streamhistory.com/die-rich-die-disgraced-andrew-carnegies-philosophy-of-wealth/ [cccxiii] http://www.forbes.com/sites/greatspeculations/2012/12/05/how-i-know-higher-taxes-would-be-good-for-the-economy/#5b0c080b3ec1 [cccxiv] http://taxfoundation.org/article/what-evidence-taxes-and-growth [cccxv] https://en.wikipedia.org/wiki/Laffer_curve [cccxvi] http://www.bbc.co.uk/news/uk-politics-26875420 [cccxvii] A minor character in Shakespeare’s Henry VI called Dick the Butcher has the memorable line, “First thing we do, let’s kill all the lawyers.”


pages: 345 words: 75,660

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, Avi Goldfarb

"Robert Solow", Ada Lovelace, AI winter, Air France Flight 447, Airbus A320, artificial general intelligence, autonomous vehicles, basic income, Bayesian statistics, Black Swan, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, collateralized debt obligation, computer age, creative destruction, Daniel Kahneman / Amos Tversky, data acquisition, data is the new oil, deskilling, disruptive innovation, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, Google Glasses, high net worth, ImageNet competition, income inequality, information retrieval, inventory management, invisible hand, job automation, John Markoff, Joseph Schumpeter, Kevin Kelly, Lyft, Minecraft, Mitch Kapor, Moneyball by Michael Lewis explains big data, Nate Silver, new economy, On the Economy of Machinery and Manufactures, pattern recognition, performance metric, profit maximization, QWERTY keyboard, race to the bottom, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, Second Machine Age, self-driving car, shareholder value, Silicon Valley, statistical model, Stephen Hawking, Steve Jobs, Steven Levy, strong AI, The Future of Employment, The Signal and the Noise by Nate Silver, Tim Cook: Apple, Turing test, Uber and Lyft, uber lyft, US Airways Flight 1549, Vernor Vinge, Watson beat the top human players on Jeopardy!, William Langewiesche, Y Combinator, zero-sum game

Elon Musk and Daniel Kahneman are both confident about AI’s potential and simultaneously worried about the implications of unleashing it on the world. Impatient about the pace at which government responds to technological advances, industry leaders have offered policy suggestions and, in some cases, have acted. Bill Gates advocated for a tax on robots that replace human labor. Sidestepping what would normally be government’s purview, the high-profile startup accelerator Y Combinator is running experiments on providing a basic income for everyone in society.2 Elon Musk organized a group of entrepreneurs and industry leaders to finance Open AI with $1 billion to ensure that no single private-sector company could monopolize the field. Such proposals and actions highlight the complexity of these social issues. As we climb to the pyramid’s top, the choices become strikingly more complex.

James Vincent, “Elon Musk Says We Need to Regulate AI Before It Becomes a Danger to Humanity,” The Verge, July 17, 2017, https://www.theverge.com/2017/7/17/15980954/elon-musk-ai-regulation-existential-threat. 2. Chris Weller, “One of the Biggest VCs in Silicon Valley Is Launching an Experiment That Will Give 3000 People Free Money Until 2022,” Business Insider, September 21, 2017, http://www.businessinsider.com/y-combinator-basic-income-test-2017-9. 3. Stephen Hawking, “This Is the Most Dangerous Time for Our Planet,” The Guardian, December 1, 2016, https://www.theguardian.com/commentisfree/2016/dec/01/stephen-hawking-dangerous-time-planet-inequality. 4. “The Onrushing Wave,” The Economist, January 18, 2014, https://www.economist.com/news/briefing/21594264-previous-technological-innovation-has-always-delivered-more-long-run-employment-not-less. 5.

., 49–50 human weaknesses in, 54–58 stereotypes, 19 Stern, Scott, 169–170, 218–219 Stigler, George, 105 strategy, 2, 18–19 AI-first, 179–180 AI’s impact on, 153–166 boundary shifting in, 157–158 business transformation and, 167–178 capital and, 170–171 cheap AI and, 15–17 data and, 174–176 economics of, 165 hybrid corn adoption and, 158–160 judgment and, 161–162 labor and, 171–174 learning, 179–194 organizational structure and, 161–162 value capture and, 162–165 strokes, predicting, 44–46, 47–49 Sullenberger, Chesley “Sully,” 184 supervised learning, 183 Sweeney, Latanya, 195, 196 Tadelis, Steve, 199 Taleb, Nassim Nicholas, 60–61 The Taming of Chance (Hacking), 40 Tanner, Adam, 195 task analysis, 74–75, 125–131 AI canvas and, 134–139 job redesign and, 142–145 Tay chatbot, 204–205 technical support, 90–91 Tencent Holdings, 164, 217, 218 Tesla, 8 Autopilot legal terms, 116 navigation apps and, 89 training data at, 186–187 upgrades at, 188 Tesla Motor Club, 111–112 Thinking, Fast and Slow (Kahneman), 209–210 Tinder, 189 tolerance for error, 184–186 tools, AI, 18 AI canvas and, 134–138 for deconstructing work flows, 123–131 impact of on work flows, 126–129 job redesign and, 141–151 usefulness of, 158–160 topological data analysis, 13 trade-offs, 3, 4 in AI-first strategy, 181–182 with data, 174–176 between data amounts and costs, 44 between risks and benefits, 205 satisficing and, 107–109 simulations and, 187–188 strategy and, 156 training data for, 43, 45–47 data risks, 202–204 in decision making, 74–76, 134–138 by humans, 96–97 in-house and on-the-job, 185 in medical imaging, 147 in modeling skills, 101 translation, language, 25–27, 107–108 trolley problem, 116 truck drivers, 149–150 Tucker, Catherine, 196 Tunstall-Pedoe, William, 2 Turing, Alan, 13 Turing test, 39 Tversky, Amos, 55 Twitter, Tay chatbot on, 204–205 Uber, 88–89, 164–165, 190 uncertainty, 3, 103–110 airline industry and weather, 168–169, 170 airport lounges and, 105–106 business boundaries and, 168–170 contracts in dealing with, 170–171 in e-commerce delivery times, 157–158 reducing, strategy and, 156–157 strategy and, 165 unknown knowns, 59, 61–65, 99 unknown unknowns, 59, 60–61 US Bureau of Labor Statistics, 171 US Census Bureau, 14 US Department of Defense, 14, 116 US Department of Transportation, 112, 185 Validere, 3 value, capturing, 162–165 variables, 45 omitted, 62 Varian, Hal, 43 variance, 34–36 fulfillment industry and, 144–145 taming complexity and, 103–110 Vicarious, 223 video games, 183 Vinge, Vernor, 221 VisiCalc, 141–142, 163, 164 Wald, Abraham, 101 Wanamaker, John, 174–175 warehouses, robots in, 105 Watson, 146 Waymo, 95 Waze, 89–90, 106, 191 WeChat, 164 Wells Fargo, 173 Windows 95, 9–10 The Wizard of Oz, 24 work flows AI tools’ impact on, 126–129 decision making and, 133–140 deconstructing, 123–131 iPhone keyboard design and, 129–130 job redesign and, 142–145 task analysis, 125–131 World War II bombing raids, 100–102 X.ai, 97 Xu Heyi, 164 Yahoo, 216 Y Combinator, 210 Yeomans, Mike, 117 YouTube, 176 ZipRecruiter, 93–94, 100 About the Authors AJAY AGRAWAL is professor of strategic management and Peter Munk Professor of Entrepreneurship at the University of Toronto’s Rotman School of Management and the founder of the Creative Destruction Lab. He is also a research associate at the National Bureau of Economic Research in Cambridge, Massachusetts, and cofounder of The Next 36 and Next AI entrepreneurship programs.


pages: 242 words: 73,728

Give People Money by Annie Lowrey

"Robert Solow", affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, airport security, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, bitcoin, clean water, collective bargaining, computer age, crowdsourcing, cryptocurrency, deindustrialization, desegregation, Donald Trump, Edward Glaeser, Elon Musk, ending welfare as we know it, everywhere but in the productivity statistics, full employment, gender pay gap, gig economy, Google Earth, Home mortgage interest deduction, income inequality, indoor plumbing, information asymmetry, Jaron Lanier, jitney, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, Kodak vs Instagram, labor-force participation, late capitalism, Lyft, M-Pesa, Mahatma Gandhi, Mark Zuckerberg, mass incarceration, McMansion, Menlo Park, mobile money, mortgage tax deduction, new economy, obamacare, Peter Thiel, post scarcity, post-work, Potemkin village, precariat, randomized controlled trial, ride hailing / ride sharing, Robert Bork, Ronald Reagan, Sam Altman, self-driving car, Silicon Valley, single-payer health, Steve Jobs, TaskRabbit, The Future of Employment, theory of mind, total factor productivity, Turing test, two tier labour market, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, War on Poverty, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y Combinator

Musk, Gates, and other tech titans have expressed interest in the policy christened the “social vaccine of the twenty-first century,” “a twenty-first-century economic right,” and “VC for the people.” Increasingly, that interest is turning into action. There are now “basic income create-a-thons,” for programmers to get together, talk UBI, and hack poverty. Cryptocurrency enthusiasts are looking into a Bitcoin-backed basic-income program. A number of young millionaire tech founders are funding a basic-income pilot among the world’s poorest in Kenya. The start-up accelerator Y Combinator is sending no-strings-attached cash to families in a few states as part of a research project. And Chris Hughes, a founder of Facebook, has plowed $10 million into an initiative to explore UBI and other related policies, something he is calling the Economic Security Project. “The community is evolving as we speak from a small group of people who say, This is it, to a large group of people who say, Hey, there may be something here,” he told me.

But it can feel disillusioning when that omniscience yields uncomfortable truths, he said. “When people join start-ups or work in tech, there’s an aspirational nature to it. But very few CEOs are happy with the idea that their work is going to cause a lot of stress and harm.” Yet the boosterism also does seem to be ignited by a real concern that we are in the midst of a profound economic and technological revolution. Sam Altman, the president of Y Combinator, recently spoke at a poverty summit cohosted by Stanford, the White House, and the Chan Zuckerberg Initiative, the Facebook billionaire’s charitable institution. “There have been these moments where we have had these major technology revolutions—the Agricultural Revolution, the Industrial Revolution, for example—that have really changed the world in a big way,” he said. “I think we’re in the middle or at least on the cusp of another one.”

“This is a new world with new challenges. From technology to Trump, it is a time of greater uncertainty and change,” Kathleen Wynne, Ontario’s premier, said, announcing the pilot. “Our goal is clear. We want to find out whether a basic income makes a positive difference in people’s lives. Whether this new approach gives them the ability to begin to achieve their potential.” Here in the United States, Y Combinator is expanding its basic-income pilot out of Oakland. The group plans to select three thousand people, dividing them into one group that will receive $1,000 a month for up to five years and a second that will receive $50 a month. “Sometimes you hear that if we don’t see huge life transformations that it would be worthless, that kind of thing,” Elizabeth Rhodes, who is leading the study, told me.


Battling Eight Giants: Basic Income Now by Guy Standing

basic income, Bernie Sanders, centre right, collective bargaining, decarbonisation, diversified portfolio, Donald Trump, Elon Musk, full employment, future of work, Gini coefficient, income inequality, Intergovernmental Panel on Climate Change (IPCC), job automation, labour market flexibility, Lao Tzu, longitudinal study, low skilled workers, Martin Wolf, Mont Pelerin Society, moral hazard, North Sea oil, offshore financial centre, open economy, pension reform, precariat, quantitative easing, rent control, Ronald Reagan, selection bias, universal basic income, Y Combinator

The payments are limited to welfare claimants, with people randomly selected and assigned to be a recipient or to be in the control group.17 Interest in these pilots lies primarily in the fact that they are testing for the effects of relaxing conditionalities in connection with so-called active labour market policies and will allow recipients to keep some of the benefit as they earn. Results will not emerge until late 2019. One early conclusion, however, is that scope for local variants of basic income pilots should be allowed and incorporated into any proposed British pilot programme, to broaden the evidence base. (10) California One much-reported pilot has been hatched in California, funded by Y-Combinator Research and run by tech entrepreneurs. The original plan was to give a sample of people in the city of Oakland $1,000 a month. But after three years of preparatory work, its project director Appendix A 97 announced that it would not be conducted in Oakland after all but in two regions in two states. The current plan is to give unconditional cash transfers of $1,000 per month to 1,000 people and $50 to a control group of 2,000 to compensate them for their cooperation in filling in questionnaires.

See Britain UK benefit system 104 UN Climate Summit 34 unconditional cash transfers 90, 97 under-qualified employees 46–7 unemployment 56, 61, 103, 105, 106 unfree market system 13 UNILAB 80 unionism 84 United States 9, 10, 16, 20, 76, 78, 81, 87, 97, 106, 109 Universal Basic Income (UBI) 113 universal basic services (UBS) 30, 108–14 Universal Credit (UC) 4, 10, 17, 24, 28, 39–52, 58, 71, 73, 81, 84 ‘universal individual credits’ 58 ‘universal minimum inheritance’ 75 unpaid work 36, 53, 67 Unum 50 Voice organization 79, 84 wage 14 differentials 15 rates 33 subsidy 105–6 Wall Street Journal 37 Warren, Elizabeth 101 ‘weakness-of-will’ 75 wealth gap 9 welfare assistance schemes 29 welfare benefits 27, 29, 41 welfare state 62, 64, 100, 109 welfare system 41, 88 welfare tourism 6 Willetts, David 76 Wolf, Martin 123 n.15 women 15–16, 36, 43, 62 Work Capability Assessment test 50 Working Tax Credits 81 World Bank 60 World Development Report 60 World Economic Forum 31, 119 n.63 Y-Combinator Research 96 Young, Charlie 124 n.12 zero-hours contracts 16, 45 140 141 142 143 144 145 146


pages: 270 words: 79,180

The Middleman Economy: How Brokers, Agents, Dealers, and Everyday Matchmakers Create Value and Profit by Marina Krakovsky

Affordable Care Act / Obamacare, Airbnb, Al Roth, Ben Horowitz, Black Swan, buy low sell high, Chuck Templeton: OpenTable:, Credit Default Swap, cross-subsidies, crowdsourcing, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, information asymmetry, Jean Tirole, Joan Didion, Kenneth Arrow, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, Metcalfe’s law, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, ride hailing / ride sharing, Robert Metcalfe, Sand Hill Road, sharing economy, Silicon Valley, social graph, supply-chain management, TaskRabbit, The Market for Lemons, too big to fail, trade route, transaction costs, two-sided market, Uber for X, uber lyft, ultimatum game, Y Combinator

Now that he is running his own VC firm, Nozad offers budding entrepreneurs what few others currently do: free office space and access to his extensive network with no strings attached. This generous, nontransactional approach has worked for him before he became a VC. “I started making these introductions without any expectation that these favors would be returned,” Nozad says. He points out, for example, that he likes to help entrepreneurs even if he’s not a shareholder of their company. His relationship with Dropbox, which started at an event at the start-up accelerator Y Combinator and began to blossom over Persian tea at the rug gallery, was never transactional, either. “It’s not like an agency—‘I’ll introduce you to these Hollywood producers, and if you raise money, I’ll get five percent of the profit you make at the end of the day’—it never was like that.”6 At one point, as I began posing a question about “deal flow,” a piece of VC jargon that had slipped from his lips, he interrupted to make sure I didn’t get the wrong idea.

He is not implying that large funds typically put all their eggs in one basket—all VCs hold a portfolio of companies—only that large investments tend to make you more cautious, which means that your portfolio will be less likely to yield exceptional returns. “Larger firms with more partners that invest more money per deal are always going to be more risk-averse,” Maples says. Paul Graham, founder of Y Combinator and likewise a believer in investing at the seed stage, put it more bluntly in his essay “A Theory of VC Suckage.” Each deal is for several million dollars, Graham argues, because management fees give firms an incentive to build up large funds. That, Graham writes, “explains why VCs take so agonizingly long to make up their minds, and why their due diligence feels like a body cavity search. With so much at stake, they have to be paranoid.”27 Some large firms do quite well—Sequoia, Accel, Andreessen Horowitz, and Greylock are a few such exceptions—but size can definitely be a handicap in the pursuit of high returns.

Grainger, 141 Walmart, 8, 140, 196 warmth, 9, 12–13, 112 Watchdogs, 77–8, 85–6, 88, 94 Watts, Duncan, 156–7 Wealthfront, 127 Weiner, Jeff, 23 Whately, Richard, 71 Williams, Evan, 129 Williamson, Oliver, 104 Willman, Hubert, 190–2 Willow-Wear, 61 Wiltermuth, Scott, 192 Wolf, Martin, 190 Wolfe, Mike, 47–52, 57–9, 64–5, 70, 72 Wood, Ann Whitley, 58–65, 72, 89, 164, 169 Xanadu art gallery, 113–14, 116, 119, 135 Y Combinator, 20, 125 YouTube, 4, 134 Zero to One (Thiel), 129 Zillow, 4 ZocDoc, 5, 38, 142–3 Zuckerberg, Mark, 23, 121


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How to Be the Startup Hero: A Guide and Textbook for Entrepreneurs and Aspiring Entrepreneurs by Tim Draper

3D printing, Airbnb, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Berlin Wall, bitcoin, blockchain, Buckminster Fuller, business climate, carried interest, connected car, crowdsourcing, cryptocurrency, Deng Xiaoping, discounted cash flows, disintermediation, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, family office, fiat currency, frictionless, frictionless market, high net worth, hiring and firing, Jeff Bezos, Kickstarter, low earth orbit, Lyft, Mahatma Gandhi, Mark Zuckerberg, Menlo Park, Metcalfe's law, Metcalfe’s law, Mikhail Gorbachev, Minecraft, Moneyball by Michael Lewis explains big data, Nelson Mandela, Network effects, peer-to-peer, Peter Thiel, pez dispenser, Ralph Waldo Emerson, risk tolerance, Robert Metcalfe, Ronald Reagan, Rosa Parks, Sand Hill Road, school choice, school vouchers, self-driving car, sharing economy, short selling, Silicon Valley, Skype, smart contracts, Snapchat, sovereign wealth fund, stealth mode startup, stem cell, Steve Jobs, Tesla Model S, Uber for X, uber lyft, universal basic income, women in the workforce, Y Combinator, zero-sum game

The good is that now the process for you to start a business is getting standardized and simpler. It is simple to get incorporated on LegalZoom or Clerky, get legal advice on LawTrades, and apply to Draper University or an accelerator like Boost.vc, Y Combinator or TechStars. It is simple to list your company on AngelList or Crowdfunder and attract people to invest angel money with you. It is easy to list products on ProductHunt, Kickstarter or Indiegogo to see if there are customers interested in what you are doing. Legal terms are getting standardized and easy to research, terms like “SAFE” (Standard Agreement of Future Equity--innovated by Y Combinator) notes, “KISS” (innovated by 500 Startups) and our favorite with Draper Associates, “Series Seed” (with our addition of “TATS [Tradeable Automated Term Sheet],” which you can find at www.lawtrades.com).

Often startups are judged by how low its CAC is against how high its LTV, the lifetime value of a customer, is. How will the cash flow? Who will pay you and when? When will you have to pay and to whom? Customers who pay in advance can make your company enormously successful, while customers who pay late can cripple you. One example of cash flow business modeling comes from my interaction with Pebble. I met Eric Migicovsky at an early Y Combinator event. A tall lanky European, Eric distinguished himself as being the only presenter who dared to create a hardware company. Venture capitalists at the time were wary of hardware companies because those companies had to buy inventory in order to sell products and that required a lot of cash. But I backed him because I saw something heroic, earnest, determined and visionary in him. He was going to build a smart watch company, which he eventually called Pebble.


pages: 579 words: 183,063

Tribe of Mentors: Short Life Advice From the Best in the World by Timothy Ferriss

23andMe, A Pattern Language, agricultural Revolution, Airbnb, Albert Einstein, Bayesian statistics, bitcoin, Black Swan, blockchain, Brownian motion, Buckminster Fuller, Clayton Christensen, cloud computing, cognitive dissonance, Colonization of Mars, corporate social responsibility, cryptocurrency, David Heinemeier Hansson, dematerialisation, don't be evil, double helix, effective altruism, Elon Musk, Ethereum, ethereum blockchain, family office, fear of failure, Gary Taubes, Geoffrey West, Santa Fe Institute, Google Hangouts, Gödel, Escher, Bach, haute couture, helicopter parent, high net worth, In Cold Blood by Truman Capote, income inequality, index fund, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, Law of Accelerating Returns, Lyft, Mahatma Gandhi, Marc Andreessen, Marshall McLuhan, Mikhail Gorbachev, minimum viable product, move fast and break things, move fast and break things, Naomi Klein, non-fiction novel, Peter Thiel, profit motive, Ralph Waldo Emerson, Ray Kurzweil, Saturday Night Live, side project, Silicon Valley, Skype, smart cities, smart contracts, Snapchat, Steve Jobs, Steven Pinker, Stewart Brand, TaskRabbit, Tesla Model S, too big to fail, Turing machine, uber lyft, web application, Whole Earth Catalog, Y Combinator

“Over the last few years, I’ve found myself looking at all my important relationships through the Enneagram lens. . . . I wish I had discovered it much earlier.” Drew Houston TW: @drewhouston FB: /houston dropbox.com DREW HOUSTON is CEO and co-founder of Dropbox. After graduating from MIT in 2006, he turned his frustration with carrying USB drives and emailing files to himself into a demo for what became Dropbox. In early 2007, he and co-founder Arash Ferdowsi applied to tech accelerator Y Combinator. Dropbox went on to become one of the fastest-growing startups in YC history. Dropbox now has more than 500 million registered users and employs more than 1,500 people in 13 global offices. What is the book (or books) you’ve given most as a gift, and why? Or what are one to three books that have greatly influenced your life? I’ve always admired Warren Buffett and Charlie Munger’s clarity of thought and how they manage to explain complex topics in simple terms.

When I was 24, I came across a website that says most people live for about 30,000 days—and I was shocked to find that I was already 8,000 days down. So you have to make every day count. I’d give the same advice today, but I would clarify that it’s not just about passion or following your dreams. Make sure the problem you become obsessed with is one that needs solving and is one where your contribution can make a difference. As Y Combinator says, “Make something people want.” In the last five years, what have you become better at saying no to? What new realizations and/or approaches helped? This was a hard thing for me to learn; I like helping people. But realizing a couple things made a big difference: You have a lot less time than you think, and you’re not spending your time the way you think you are. I’ve found this analogy useful.

“When I’m old, how much would I be willing to pay to travel back in time and relive the moment that I’m experiencing right now?” Muneeb Ali TW: @muneeb muneebali.com MUNEEB ALI is the co-founder of Blockstack, a new decentralized Internet where users control their data, and apps run without remote servers. Muneeb received his PhD in computer science from Princeton University, specializing in distributed systems. He went through Y Combinator—considered the Harvard/SEAL Team Six of startup incubators—and has worked in the systems research group at Princeton and PlanetLab, the world’s first and largest cloud computing test bed. Muneeb was awarded a J. William Fulbright fellowship and gives guest lectures on cloud computing at Princeton. He has built a broad range of production systems and published research papers with more than 900 citations.


pages: 340 words: 100,151

Secrets of Sand Hill Road: Venture Capital and How to Get It by Scott Kupor

activist fund / activist shareholder / activist investor, Airbnb, Amazon Web Services, asset allocation, barriers to entry, Ben Horowitz, carried interest, cloud computing, corporate governance, cryptocurrency, discounted cash flows, diversification, diversified portfolio, estate planning, family office, fixed income, high net worth, index fund, information asymmetry, Lean Startup, low cost airline, Lyft, Marc Andreessen, Myron Scholes, Network effects, Paul Graham, pets.com, price stability, ride hailing / ride sharing, rolodex, Sand Hill Road, shareholder value, Silicon Valley, software as a service, sovereign wealth fund, Startup school, Travis Kalanick, uber lyft, VA Linux, Y Combinator, zero-sum game

Not only did the absolute cost of servers, networking, storage, data center space, and applications begin to fall, but the procurement method evolved from up-front purchasing to much cheaper “renting” with the advent of what is known as cloud computing. As a startup, these changes are very significant, as they mean that the amount of money you need to raise from VCs to get started is much less than in the past. Y Combinator Cracks Open the “Black Box” The second material transformation in the startup ecosystem was the advent of an incubator known as Y Combinator (or YC for short). Started in 2005 by Paul Graham and Jessica Livingston, YC basically created startup school. Cohorts of entrepreneurs joined a “YC batch,” working in an open office space together and going through a series of tutorials and mentorship sessions over a three-month period to see what might come out the other end.

See dot.com boom/bust term sheets, 140–169, 170–188 on aggregate proceeds, 142, 278 antidilution provisions in, 165–167, 280–281 on board of directors, 171–173, 281 on capitalization, 154, 278 on confidentiality, 285 on conversion/auto-conversion to common shares, 160–165, 280 on co-sale agreements, 181 on D&O insurance, 183, 284 on dividends, 154–155 drag-along provisions in, 182–183, 252, 284 on employee and consultant agreements, 187 and go-shop provisions, 239 on information rights, 282 on legal counsel and fees, 286 on liquidation preference, 155–159, 279 and no-shop provisions, 187–188, 239, 285 on preferred shares, 141–142 on price per share, 147–149, 278 on pro rata investments, 178–180, 283 on protective provisions, 173–177, 281–282 and recapitalizations, 281, 282 on redemption rights, 159 on registration rights, 178, 282 on right-of-first-refusal, 180–181 sample, 141, 277–286 on stock purchase agreement, 284 on stock restriction, 180–182, 283 on vesting, 183–187, 284 on voting rights, 167–169, 281 Tesla, 110 timing in startup world, importance of, 14 Tiny Speck, 137 Trados case, 220–231 and common shareholders, 221–222, 223 and conflict of board, 222–226 decision on, 227–228 distribution of proceeds from acquisition, 221 and entire fairness rule, 222, 226–229 guidelines stemming from, 225–226 and management incentive plan, 221, 226–227 takeaways from, 228–231 transfer restrictions, 98–99 Uber, 102, 172–173 United States and venture capital, 3, 271, 275 university endowments, 54–55, 56–57, 71 unrelated business income (UBIT), 93–94 use of proceeds, 278 vacation policies, 244–245 VA Linux, 264–265 valuation, 118–123 and antidilution provisions in term sheet, 165–167 and convertible notes, 144 pre- and post-money, 147–149 of very-early-stage startups, 153–154 valuation marks, understanding, 76–83 venture-backed companies economic impact of, 3–4, 41 exiting options of (see acquisitions; initial public offerings) five largest US market capitalization companies, 25, 41 and information asymmetry, 5, 140, 275 VC’s relationship with, 2–3, 4–5 venture capital (VC) and ability to raise new funds, 67–68 as asset class, 29–30 batting average of, 37–40 cardinal sins of, 44, 50–51, 179–180 competition for, 271–272 distribution of returns for, 30–32, 31, 35, 38, 40 and dot.com boom/bust, 64–65 early years in Silicon Valley, 19–20 as endorsement of a company, 43–44 equity financing as basis of, 26–27, 28 and evolution of VC industry, 270–273 extensions of last round of, 233 and institutional investors, 40–41 life cycle of, 7–8, 114–115, 268 and life cycle of fund, 152 measuring success of, 36–40 median ten-year returns in, 30 and multiple funds, 67 potential replacements for, 273–274 relationship of LPs to, 69–71 reserves set aside by, 66–67 restricted nature of, 35–36 risks inherent in, 39 rounds of, 34–35, 66–67, 115–117, 138–139, 151–152 signaling in, 32–33, 35, 37 size of industry, 40–41 and state of fund, 83–84 three professional roles in, 29 and Yale University endowment, 62–63, 64–65 as zero-sum game, 33–35 venture capitalists average duration of relationship with, 5, 115 creating incentives for, 114–115 as dual fiduciaries, 201–202 exit of, following IPO, 266–267 and failure to invest in winners, 33 funding from (see difficult financings; raising money from venture capitalists; term sheets) goals of, 114–115, 126, 139 and information asymmetry, 5, 140, 275 and opportunity costs, 43–44, 83, 212–213, 223 over-involvement with company, 203 and pitches (see pitching to venture capitalists) role of, 2–3, 29, 274–275 vesting accelerated, 99–101, 186–187, 250–251 and acquisitions, 250–251 and founders, 95–97, 99–101, 183, 186, 205–206 and general partners (GPs), 89 and term sheets, 183–187, 284 VMware, 132 voting on authorization of new classes of stock, 176 on corporate actions, 176 protective provisions on, 173–177 voting rights, 167–169, 281 WARN statutes, 243–244 waterfall valuation method, 77, 78–79 Waymo, 187 whaling industry, 53 winding down the company, 243–246 working capital, 150 Yale University endowment, 54, 59–65 Y Combinator (YC), 20–21 zero-sum game, venture capital as, 33–35 ABCDEFGHIJKLMNOPQRSTUVWXYZ ABOUT THE AUTHOR Scott Kupor is the managing partner of Andreessen Horowitz. He has overseen the firm's rapid growth to one hundred fifty employees and more than $7 billion in assets under management. He is also a cofounder and codirector of the Stanford Venture Capital Director's College and teaches venture capital and corporate governance courses at Stanford Law School and the Haas School of Business and Boalt School of Law at UC Berkeley.


pages: 359 words: 97,415

Vanishing Frontiers: The Forces Driving Mexico and the United States Together by Andrew Selee

Berlin Wall, call centre, Capital in the Twenty-First Century by Thomas Piketty, Donald Trump, energy security, Gini coefficient, guest worker program, illegal immigration, immigration reform, income inequality, income per capita, informal economy, job automation, low skilled workers, manufacturing employment, oil shale / tar sands, open economy, payday loans, Richard Florida, rolodex, Ronald Reagan, Silicon Valley, Silicon Valley startup, Steve Wozniak, Y Combinator

They are looking at practical solutions to real problems in Mexico, but they may be scalable to fit other similar markets around the world. Unima, a company started by four PhDs in chemistry, fits this mold. The founders developed an online diagnostic test that rural clinics with no doctor present can use to diagnose a range of diseases. An app reads the patient’s blood sample, analyzes it, and shares it with a doctor at a remote location, who can provide a diagnosis. “We were the first Mexican start-up accepted in Y-Combinator,” Silicon Valley’s most prestigious technology accelerator, says José Luis Nuño, one of the company’s founders. That experience helped put them in touch with venture capitalists willing to back them. Now, with several millions of dollars in investment from the Gates Foundation and US and Mexican venture capital funds, Unima is about ready to initiate production of the diagnostic test in its own plant in Guadalajara.

Still another Guadalajara-based company, Sunu, makes a wristband for the visually impaired that helps its wearer navigate throughout the day by sensing objects nearby. It’s essentially a digital complement to walking canes, using ultrasound to send signals to the user about obstacles in the environment that go beyond what a cane can detect. It’s young founder, Marco Trujillo, got the idea while doing community service at a school for the blind in Guadalajara. His big break came when Sunu was admitted into MassChallenge, Boston’s equivalent of Y-Combinator, which has strong links to health-care technology. This experience opened up investment from US as well as Mexican-based venture funds. Most of Sunu’s sales are in the United States, though the technology was developed in Mexico. This is just a sampling of the many start-ups taking hold in Mexico. Whereas Guadalajara was once a manufacturing hub for technology components, it’s now becoming a seedbed of innovation for new technologies that can improve everyday life in Mexico—and sometimes in other countries as well.

See Hazelton, Pennsylvania Valdés, Guillermo, 169–170, 171, 173–174, 175 Vasconcelos, José, 209–210 Venegas, Julieta, 216 venture capital, 6, 97, 99, 101, 102, 103, 107–108, 109–110, 111–112, 272 Videgaray, Luis, 200 Villanueva, Fernando, 78–79 Villaraigosa, Antonio, 266 Villas de Salvárcar massacre, 165, 166, 167, 169 virtual border crossing, 281 visas, 4, 30, 47, 100, 191, 248, 265 Vitro, 57, 76 Volvo, 54 voting, 17, 19, 21, 53, 164, 264, 266, 267, 278 wage pressure, 187 See also low-wage jobs Wallace, Roger, 114–115, 116, 117 Walmart, 77, 85, 96 Wanzek, Terry, 49, 50, 53, 54 Wilson, Christopher, 58, 61 Wilson, Woodrow, 211 wind power, 117, 121–122, 123, 124 Wizeline, 99–100, 106 Woldenberg, José, 278 Women’s National Basketball League (WNBA), 250 Wood, Duncan, 120, 122, 124, 130, 132 work ethic, 78, 79 World Cup, 47, 251, 270 World Series, 2, 272–273 World Trade Organization, 63, 98 Wozniak, Steve, 41 writing community, 213–214 Y-Combinator, 102, 103 Young Jaguars for Good, 165–166 Zacatecan Federation of Southern California, 188–190, 192 Zeta (newspaper), 135, 139, 140 Zetas, 138, 171–174, 175, 176


pages: 346 words: 97,330

Ghost Work: How to Stop Silicon Valley From Building a New Global Underclass by Mary L. Gray, Siddharth Suri

Affordable Care Act / Obamacare, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, basic income, big-box store, bitcoin, blue-collar work, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative consumption, collective bargaining, computer vision, corporate social responsibility, crowdsourcing, data is the new oil, deindustrialization, deskilling, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, en.wikipedia.org, equal pay for equal work, Erik Brynjolfsson, financial independence, Frank Levy and Richard Murnane: The New Division of Labor, future of work, gig economy, glass ceiling, global supply chain, hiring and firing, ImageNet competition, industrial robot, informal economy, information asymmetry, Jeff Bezos, job automation, knowledge economy, low skilled workers, low-wage service sector, market friction, Mars Rover, natural language processing, new economy, passive income, pattern recognition, post-materialism, post-work, race to the bottom, Rana Plaza, recommendation engine, ride hailing / ride sharing, Ronald Coase, Second Machine Age, sentiment analysis, sharing economy, Shoshana Zuboff, side project, Silicon Valley, Silicon Valley startup, Skype, software as a service, speech recognition, spinning jenny, Stephen Hawking, The Future of Employment, The Nature of the Firm, transaction costs, two-sided market, union organizing, universal basic income, Vilfredo Pareto, women in the workforce, Works Progress Administration, Y Combinator

He asked company founders to design products and services that made a market for themselves, filling a societal need rather than using profits from a popular product to fund philanthropy. Parikh had some powerful fans, like the venture capitalists behind the Bay Area incubator Y Combinator. Students who enrolled in Parikh’s class had a chance to compete for real financial backing through Y Combinator. Philipp Gutheim, Anand Kulkarni, Prayag Narula, and Dave Rolnitzky took their classroom project, MobileWorks, and won Y Combinator’s summer 2011 competition, giving them enough money to bankroll a group of engineers, a marketing campaign, and a network of on-demand workers serving as virtual assistants from around the world. See Gray et al., “The Crowd”; Anand Kulkarni et al., “MobileWorks: Designing for Quality in a Managed Crowdsourcing Architecture,” IEEE Internet Computing 16, no. 5 (September 2012): 28–35, https://doi.org/10.1109/MIC.2012.72.


pages: 198 words: 53,264

Big Mistakes: The Best Investors and Their Worst Investments by Michael Batnick

activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, asset allocation, bitcoin, Bretton Woods, buy and hold, buy low sell high, cognitive bias, cognitive dissonance, Credit Default Swap, cryptocurrency, Daniel Kahneman / Amos Tversky, endowment effect, financial innovation, fixed income, hindsight bias, index fund, invention of the wheel, Isaac Newton, John Meriwether, Kickstarter, Long Term Capital Management, loss aversion, mega-rich, merger arbitrage, Myron Scholes, Paul Samuelson, quantitative easing, Renaissance Technologies, Richard Thaler, Robert Shiller, Robert Shiller, Snapchat, Stephen Hawking, Steve Jobs, Steve Wozniak, stocks for the long run, transcontinental railway, value at risk, Vanguard fund, Y Combinator

I was like no dice man, let this guy go.” GoPro went public in 2014 at a valuation just below $3 billion.12 He didn't have the chance to invest in GoPro, but Sacca said no to some of the most well‐known and storied businesses of the decade. “One of my constant recurring nightmares is about the stuff I passed on.” He tells a story about the time he met with Dropbox, whom he met while they were still in Y Combinator's early‐stage start‐up program. He didn't think they could beat Google, which was developing its own file‐sharing service, Drive. He went so far as to recommend that Dropbox pursue a different path. Lucky for Dropbox, they didn't take his advice. Sacca estimates his decision to not invest in Dropbox cost him “hundreds of millions of dollars.”13 At close to a $10 billion valuation, Dropbox is one of the biggest misses of Sacca's career.

., 51 VeriSign, Druckenmiller purchase, 104 Vranos, 133 Washington Post stocks, problems, 58 Wayne, Ronald, 148 Webster & Company bankruptcy, 31 problems, 30 Webster, Samuel Charles, 29 Wellington Fund, 48 merger, 49 operation, at‐cost basis, 51 Wellington Management, Bogle firing, 51 Wendy's, stock appreciation, 89 Wesco Financial, purchase, 142 Wheeler, Munger & Company, 141 Whiz Kids Take Over, The, 49 “Who Wants to Be a Millionaire” (Ackman), 90–91 Winning the Loser's Game (Ellis), 99 Woodman, Nick, 150 WordPress, 149 World War I, global monetary system, 122 Wozniak, Steve, 148 Wright Aeronautical, business demonstration, 3 Xerox, trading level, 70 Yahoo!, gains, 57 Y Combinator, 150 Zacks, Richard, 27 Zweig, Jason, 3 Zynga, trading, 157 WILEY END USER LICENSE AGREEMENT Go to www.wiley.com/go/eula to access Wiley’s ebook EULA.


pages: 169 words: 56,250

Startup Communities: Building an Entrepreneurial Ecosystem in Your City by Brad Feld

barriers to entry, cleantech, cloud computing, corporate social responsibility, G4S, Grace Hopper, job satisfaction, Kickstarter, Lean Startup, minimum viable product, Network effects, paypal mafia, Peter Thiel, place-making, pre–internet, Richard Florida, Ruby on Rails, Silicon Valley, Silicon Valley startup, smart cities, software as a service, Steve Jobs, text mining, Y Combinator, zero-sum game, Zipcar

They pointed to Ellison, Jobs, Gates, and Zuckerberg. They heard the calls from Peter Thiel to drop out of college (http://startuprev.com/o2). They were fascinated with TechStars, Y Combinator, and similar programs. As we tell entrepreneurs, when there is a crisis, there is great opportunity for innovation. So at MIT we took some of our own medicine and explored what we could do to meet this challenge of making the academic environment more conducive to successful entrepreneurial development. We looked at Stanford, Berkeley, Harvard, the University of Michigan, and the University of Washington. We discussed the issue with students and saw their high level of interest in TechStars, Y Combinator, Dogpatch Labs, General Assembly, and Rock Health. We recognized an opportunity to create a program unique to MIT’s mission, using our assets, which would fit well with existing university-based and outside programs.


pages: 246 words: 68,392

Gigged: The End of the Job and the Future of Work by Sarah Kessler

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, bitcoin, blockchain, business cycle, call centre, cognitive dissonance, collective bargaining, crowdsourcing, David Attenborough, Donald Trump, East Village, Elon Musk, financial independence, future of work, game design, gig economy, income inequality, information asymmetry, Jeff Bezos, job automation, law of one price, Lyft, Mark Zuckerberg, market clearing, minimum wage unemployment, new economy, payday loans, post-work, profit maximization, QR code, race to the bottom, ride hailing / ride sharing, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, TaskRabbit, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, working-age population, Works Progress Administration, Y Combinator

Martin Luther King Jr., the conservative economist Friedrich Hayek, and President Richard Nixon had all supported this idea, and modern boosters were no less varied. They included Andy Stern, the former president of the SEIU; the libertarian economist Charles Murray; and Robert Reich, the Bill Clinton–era labor secretary, who was fond of comparing the gig economy to a sweatshop. The tech incubator Y Combinator had recently committed to running a UBI experiment in California to understand how it worked. Facebook cofounder Chris Hughes endorsed UBI in a book. Terrence Davenport, though, was not a fan. He was nearly exasperated at what he saw as the ignorance inherent in the idea. “Do you know about the opioid crisis in this country?” he said. “Do you know that poor people in my community don’t know how to budget?”

See labor and trade unions United Construction Trades and Industrial Employees Union Universal Basic Income (UBI) UPS Upwork (freelance marketplace) US Department of Labor USA Today venture capital gig economy and Google Ventures Managed by Q and TechCrunch Disrupt and Uber and venture capitalists VentureBeat (blog) Walker, Anthony Walmart Warner, Mark Warren, Elizabeth Washington Post Washio (on-demand laundry startup) WeFuel (on-demand fuel startup) Weil, David Winthrop Rockefeller Foundation Wired (magazine) Woodhead, Carole workers advocacy groups workers’ compensation Xchange Leasing Y Combinator (tech incubator) Yelp (user review website) Zaarly (online marketplace) Zirtual (virtual assistant services) Zuckerberg, Mark About the Author SARAH KESSLER is a reporter at Quartz, where she writes about the future of work. Before joining Quartz in 2016, she covered the gig economy as a senior writer at Fast Company and managed startup coverage at Mashable. Her reporting has been cited by The Washington Post, New York magazine, and NPR.


pages: 271 words: 62,538

The Best Interface Is No Interface: The Simple Path to Brilliant Technology (Voices That Matter) by Golden Krishna

Airbnb, computer vision, crossover SUV, en.wikipedia.org, fear of failure, impulse control, Inbox Zero, Internet Archive, Internet of things, Jeff Bezos, Jony Ive, Kickstarter, Mark Zuckerberg, new economy, Oculus Rift, pattern recognition, QR code, RFID, self-driving car, Silicon Valley, Skype, Snapchat, Steve Jobs, technoutopianism, Tim Cook: Apple, Y Combinator, Y2K

Rachel Metz, “Every Step You Take, Tracked Automatically,” MIT Technology Review, February 12, 2013. http://www.technologyreview.com/news/510491/every-step-you-take-tracked-automatically/ 32 Sumathi Reddy, “Why We Keep Losing Our Keys,” Wall Street Journal, April 14, 2014. http://online.wsj.com/news/articles/SB10001424052702304117904579501410168111866 33 Esure, “We’re a Bunch of ‘Losers,’” esure.com, March 21, 2012. http://www.esure.com/media_centre/archive/wcmcap_100800.html 34 “Y Combinator-backed Lockitron aims to replace physical keys entirely by letting you control your door lock with your phone . . .” Alexia Tsotsis, “Lockitron Lets You Unlock Your Door with Your Phone,” TechCrunch, May 13, 2011. http://techcrunch.com/2011/05/13/lockitron-lets-you-unlock-your-door-with-your-phone/ 35 “It works like this. You replace either part or all of your door lock with Lockitron’s parts (depending on the kind of lock you have).

UX (user experience), 46–47, 80, 103 uniqueness, understanding, 169–170 University of Washington statistics, 128 user input vs. machine input, 139–140 relying on, 135 username, invalidity of, 131–132 users, considering needs of, 114 UX (user experience) design, explained, 30–31 UX/UI job listings, 45–46 V vending-machine interface, 43–44 Visa’s payWave, 107 Vitulli, Clark, 121 voice recognition, 175–176 W Want, Roy, 139 Weeks, Jack, 173 Weiser, Mark, 137–138, 140–141 Weiss, Rick, 65 Whirlpool washing machine commercial, 151, 154 white out, 76 Whitman, Meg, 46 Wi-Fi, Airport service, 188–189 WIMP (windows, icons, menus, pointers), 77 Winfrey, Oprah, 63 wireframes for car controls, 115 familiarity of, 116 Wood, Molly, 191 work day, number of hours in, 147 World Chess Championship, 129 X Xerox PARC research, 137–139 Y Y Combinator, 102 * * * Let’s keep chatting. Well, thanks for reading my book. I really appreciate it. The conversation continues through the hashtag #NoUI, and at www.nointerface.com. And don’t hesitate to reach out to me at golden.krishna@gmail.com or through Twitter via @goldenkrishna. You can also check out other great books by Peachpit at www.peachpit.com. * * *


pages: 238 words: 73,824

Makers by Chris Anderson

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

Maybe riches lie at the end of this rainbow, or maybe they don’t. But the point is that the path from “inventor” to “entrepreneur” is so foreshortened it hardly exists at all anymore. Indeed, startup factories such as Y Combinator now coin entrepreneurs first and ideas later. Their “startup schools” admit smart young people on the basis of little more than a PowerPoint presentation. Once admitted, the would-be entrepreneurs are given spending money, whiteboards, and desk space and told to dream up something worth funding in three weeks. Most do, which says as much about the Web’s ankle-high barriers to entry as it does about the genius of the participants. Over the past six years, Y Combinator has funded three hundred such companies, with such names as Loopt, Wufoo, Xobni, Heroku, Heyzap, and Bump. Incredibly, some of them (such as DropBox and Airbnb) are now worth billions of dollars.


pages: 293 words: 78,439

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

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

In the 1990s, Innosight cofounder Clayton Christensen published The Innovator’s Dilemma, whose cover proclaims that the book will show readers how “new technologies cause great companies to fail.” The titles grow more ominous over time. In 2013, Dave Ulmer drew on his experience at several large companies to detail The Innovator’s Extinction. His cover blurb? “How natural selection and best intentions will drive your company into the grave.” Another voice is that of Paul Graham, the founder of Y Combinator, a leading incubator that helped spur Dropbox, Airbnb, and hundreds of other companies. Graham perhaps summed up the zeitgeist best when he said, “Running a startup is like being punched in the face repeatedly, but working for a large company is like being waterboarded.” Coauthor Scott Anthony believed all this when he packed up his family and moved them to Singapore in 2010. He didn’t come to Singapore to expand Innosight’s consulting operations to Southeast Asia (although that’s what he ended up doing).

., 60 Walgreens, 60–61 Wanamaker, John, 67 warning signs, 102–113 assessment table, 213 catalysts, 104–105 circumstances, 103–104 how to spot, 107–110 impact, 106–107 underestimation of, 120 Wasson, Gregory, 60–61 Watson supercomputer, 70, 204 WebMD, 100 WeChat, 106 Welch, Jack, 177 WhatsApp, 48, 136 white space, 63, 66 will.i.am, 151 Williams, Ev, 49, 138 Wilson, Joseph C., 13 World Media Enterprises, 156 Wright brothers, 64–65 Xerox, 13–16 acquisitions and partnerships at, 67 arbitration at, 86 business model innovation at, 42, 63–64 capabilities link at, 14–15 focus at, 117 postdisruption job to be done at, 39 transformation journey at, 182 Xerox Global Services (XGS), 14, 63–64, 86 Yahoo, 49 Y Combinator, 72 Yelp, 50 Young Broadcasting, 156 YouTube, 97, 105, 108 Zillow, 50 Zipcar, 205 Zuckerberg, Mark, 48, 97 Acknowledgements From the team The central idea in Dual Transformation—that leaders need to simultaneously reposition today’s business and create tomorrow’s—has been core to each of our professional careers since 2000. In fact, if you looked at slides from the executive training sessions two of us (Clark and Mark) ran in 2001, you would see a version of the “two circle” chart that we have adapted to summarize the dual transformation framework.


pages: 300 words: 76,638

The War on Normal People: The Truth About America's Disappearing Jobs and Why Universal Basic Income Is Our Future by Andrew Yang

3D printing, Airbnb, assortative mating, augmented reality, autonomous vehicles, basic income, Ben Horowitz, Bernie Sanders, call centre, corporate governance, cryptocurrency, David Brooks, Donald Trump, Elon Musk, falling living standards, financial deregulation, full employment, future of work, global reserve currency, income inequality, Internet of things, invisible hand, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, Khan Academy, labor-force participation, longitudinal study, low skilled workers, Lyft, manufacturing employment, Mark Zuckerberg, megacity, Narrative Science, new economy, passive income, performance metric, post-work, quantitative easing, reserve currency, Richard Florida, ride hailing / ride sharing, risk tolerance, Ronald Reagan, Sam Altman, self-driving car, shareholder value, Silicon Valley, Simon Kuznets, single-payer health, Stephen Hawking, Steve Ballmer, supercomputer in your pocket, technoutopianism, telemarketer, The Wealth of Nations by Adam Smith, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, unemployed young men, universal basic income, urban renewal, white flight, winner-take-all economy, Y Combinator

Economists measured labor rates and found no reduction in hours worked—if anything they found people in the service industry expanded their businesses. This is hugely indicative because of the enormous sample size—Iran has 80 million people, equivalent to the combined total of New York, California, and Florida—over an extended period of time. Most recently, a small trial launched in the United States. Starting in early 2017 in Oakland, California, Sam Altman, the head of the technology firm Y Combinator, is giving 100 households in Oakland approximately $1,000 to $2,000 per month for about a year to measure the impacts on recipients. The goal is to roll out a larger five-year trial afterward. Sam and his friends are giving away $2 million and hiring researchers just to see what will happen. I love the fact that Sam is putting up the resources to study this problem. He’s demonstrating the kind of leadership and vision that, in an ideal world, our government would be capable of.

The most direct way to do so would be to move toward a single-payer health care system, in which the government both guarantees health care for all and negotiates fixed prices. Medicare—the government-provided health care program for Americans 65 and over—essentially serves this role for senior citizens and has successfully driven down costs and provided quality care for tens of millions. Most everyone loves Medicare—it’s politically bulletproof. Sam Altman, the head of Y Combinator, suggests rolling out Medicare across the population by gradually lowering the eligibility age over time. A gradual phase-in would give the industry time to plan and adjust. This is an excellent way forward, and a “Medicare-for-all” movement is currently gathering steam. There would inevitably remain a handful of private options for the super-affluent, but most everyone would use the generalized care.


pages: 267 words: 72,552

Reinventing Capitalism in the Age of Big Data by Viktor Mayer-Schönberger, Thomas Ramge

accounting loophole / creative accounting, Air France Flight 447, Airbnb, Alvin Roth, Atul Gawande, augmented reality, banking crisis, basic income, Bayesian statistics, bitcoin, blockchain, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Cass Sunstein, centralized clearinghouse, Checklist Manifesto, cloud computing, cognitive bias, conceptual framework, creative destruction, Daniel Kahneman / Amos Tversky, disruptive innovation, Donald Trump, double entry bookkeeping, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ford paid five dollars a day, Frederick Winslow Taylor, fundamental attribution error, George Akerlof, gig economy, Google Glasses, information asymmetry, interchangeable parts, invention of the telegraph, inventory management, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, job satisfaction, joint-stock company, Joseph Schumpeter, Kickstarter, knowledge worker, labor-force participation, land reform, lone genius, low cost airline, low cost carrier, Marc Andreessen, market bubble, market design, market fundamentalism, means of production, meta analysis, meta-analysis, Moneyball by Michael Lewis explains big data, multi-sided market, natural language processing, Network effects, Norbert Wiener, offshore financial centre, Parag Khanna, payday loans, peer-to-peer lending, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price mechanism, purchasing power parity, random walk, recommendation engine, Richard Thaler, ride hailing / ride sharing, Sam Altman, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, Snapchat, statistical model, Steve Jobs, technoutopianism, The Future of Employment, The Market for Lemons, The Nature of the Firm, transaction costs, universal basic income, William Langewiesche, Y Combinator

In addition, by giving everyone just enough to get by and no more, a UBI would not necessarily eliminate the incentive to work. Limited experiments in administering a UBI are underway in Finland and the Netherlands, and they will produce some empirical data about the effects of a UBI on human motivation. Switzerland held a national referendum on a UBI, but voters rejected the very generous scheme that was proposed (around $2,000 per month for every Swiss citizen). Beginning in 2016, start-up accelerator Y Combinator even sponsored a small project in the United States designed to investigate whether receiving a basic income would have an effect on people’s desire to work. Canada experimented with a version of basic income back in the 1970s, when it gave a monthly check to every eligible family in the small town of Dauphin, Manitoba. That led to improvements (albeit modest) in education rates and reductions in hospitalization and teenage pregnancy.

See universal basic income UniCredit bank, 136 Unilever, 75 United Kingdom, 134, 147, 164 United States banking crisis in, 134, 135 capital share of, 185 corporate taxes in, 197–198 health care sector in, 213 labor market of, 184, 185, 186, 195 market concentration in, 164 stock market investment options in, 143 subprime mortgage crisis in (see subprime mortgage crisis) universal basic income proposed in, 190, 191 universal basic income (UBI), 189–193, 205–206 University of Pennsylvania’s Wharton School, 36 Upstart, 151 Upwork, 3 used car market, 40 venture capital (VC) firms, 141, 142–143, 216 Vocatus, 55 Volkswagen, 182 Volvo, 182 Wall Street Journal, 203 Walmart, 28, 52 Walt Disney Company, 69 Watson (machine learning system), 109, 111, 113–114, 115, 117, 163, 183 Watt, James, 111, 113 wealth tax, 187 Webvan, 112 WeChat, 147, 163 Wedgwood, Josiah, 94 welfare reducing transactions, 73 Wenger, Albert, 156, 189 Wenig, Devin, 1–2, 209 Wharton School, 36 Which?, 52 Wiener, Norbert, 159–160, 179 Wikipedia, 21–22 Windows, 166 Wired magazine, 181 WordPress, 161 work. See labor market Y Combinator, 191 Yahoo, 2–3, 6 Yamaha, 30 Yegge, Steve, 88 YouTube, 67, 68–69 ZestFinance, 151 Zetsche, Dieter, 110, 121 Zopa, 152 Zulu Trade, 152


pages: 258 words: 74,942

Company of One: Why Staying Small Is the Next Big Thing for Business by Paul Jarvis

Airbnb, big-box store, Cal Newport, call centre, corporate social responsibility, David Heinemeier Hansson, effective altruism, Elon Musk, en.wikipedia.org, endowment effect, follow your passion, gender pay gap, glass ceiling, Inbox Zero, index fund, job automation, Kickstarter, Lyft, Mark Zuckerberg, Naomi Klein, passive investing, Paul Graham, pets.com, remote working, Results Only Work Environment, ride hailing / ride sharing, Ruby on Rails, side project, Silicon Valley, Skype, Snapchat, software as a service, Steve Jobs, supply-chain management, Tim Cook: Apple, too big to fail, uber lyft, web application, Y Combinator, Y2K

The Kauffman Foundation study also illustrated that almost 86 percent of companies that succeeded in the long term did not take VC money. Why? Because a company’s interests may not always align with the interests of its backers. Worse, investor interests may not always align with what’s best for a business’s end customers. Capital infusion can also leave a business with less control, resilience, speed, and simplicity—the main traits required for companies of one. Paul Graham, the cofounder of Y Combinator (one of the largest and most notable VC firms for startups) explains that VCs don’t invest millions in companies because that’s what those companies might need; rather, they invest the amount that their own VC business requires to see growth in their own portfolios, coming from the few companies that actually give them a positive return. Graham notes that sudden and large investments tend to turn companies into “armies of employees who sit around having meetings.”

See purpose Williams, Ev, 178 win-win relationships, 79, 96, 103, 115–17, 151, 188, 202–7 Womersley, Katie, 72 Word of Mouth Marketing Association, 152 word-of-mouth publicity, 107, 109, 110, 115–16, 144, 152–56 WordPress, 35, 176 work commitment to, 86–87 in company of one, 200–202 defined, 16 engaging work traits, 83 passion and, 82 workaholism, 54–56 World Domination Summit, 189 Y Y Combinator, 28 YouTube, 176 Z Zafirovski, Mike, 21 Zander, Ed, 177 Zanuck, Darryl, 177 Zingales, Luigi, 121 Zuckerberg, Mark, 47, 69, 193 About the Author Beginning as a corporate web designer and internet consultant, Paul Jarvis first spent years working with top professional athletes like Warren Sapp, Steve Nash, and Shaquille O’Neal with their online presence, and with large companies like Yahoo, Microsoft, Mercedes-Benz and Warner Music.


pages: 268 words: 75,850

The Formula: How Algorithms Solve All Our Problems-And Create More by Luke Dormehl

3D printing, algorithmic trading, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, Clayton Christensen, commoditize, computer age, death of newspapers, deferred acceptance, disruptive innovation, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Frank Levy and Richard Murnane: The New Division of Labor, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kodak vs Instagram, lifelogging, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, Panopticon Jeremy Bentham, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, the scientific method, The Signal and the Noise by Nate Silver, upwardly mobile, Wall-E, Watson beat the top human players on Jeopardy!, Y Combinator

The Selfish Gene (Oxford, UK; New York: Oxford University Press, 1989). 21 Consider, for instance, the way in which divorce cases are presumed—in their very “Smith v. Smith” language—to be adversarial, even when this might not be the case at all. 22 Fisher, Daniel. “Silicon Valley Sees Gold in Internet Legal Services.” Forbes, October 5, 2011. forbes.com/sites/danielfisher/2011/10/05/silicon-valley-sees-gold-in-internet-legal-services/. 23 Casserly, Meghan. “Can This Y-Combinator Startup’s Technology Keep Couples Out of Divorce Court?” Forbes, April 10, 2013. forbes.com/sites/meghancasserly/2013/04/10/wevorce-y-combinator-technology-divorce-court/. 24 “After Beta Period, Wevorce Software for Making Every Divorce Amicable Is Now Generally Available Nationwide.” May 22, 2013. marketwired.com/press-release/after-beta-period-wevorce-software-making-every-divorce-amicable-is-now-generally-available-1793675.htm. 25 Turkle, Sherry. Life on Screen: Identity in the Age of the Internet (New York: Simon & Schuster, 1995). 26 Lohr, Steve.


pages: 269 words: 70,543

Tech Titans of China: How China's Tech Sector Is Challenging the World by Innovating Faster, Working Harder, and Going Global by Rebecca Fannin

Airbnb, augmented reality, autonomous vehicles, blockchain, call centre, cashless society, Chuck Templeton: OpenTable:, cloud computing, computer vision, connected car, corporate governance, cryptocurrency, data is the new oil, Deng Xiaoping, digital map, disruptive innovation, Donald Trump, El Camino Real, Elon Musk, family office, fear of failure, glass ceiling, global supply chain, income inequality, industrial robot, Internet of things, invention of movable type, Jeff Bezos, Kickstarter, knowledge worker, Lyft, Mark Zuckerberg, megacity, Menlo Park, money market fund, Network effects, new economy, peer-to-peer lending, personalized medicine, Peter Thiel, QR code, RFID, ride hailing / ride sharing, Sand Hill Road, self-driving car, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart transportation, Snapchat, social graph, software as a service, South China Sea, sovereign wealth fund, speech recognition, stealth mode startup, Steve Jobs, supply-chain management, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, urban planning, winner-take-all economy, Y Combinator, young professional

A few months later, at the annual Baidu World forum in Beijing, cofounder Li set an upbeat tone with the program theme “Yes, AI do,” as he showed off a series of product introductions and upgrades that proved how far this leading search company is veering from its origins. Dressed in his classic white shirt emblazoned with a Baidu logo, he put a positive spin on Baidu’s latest innovations in artificial intelligence—not so easy to be upbeat since he had to step back into the CEO seat after his star hire Lu left in May 2018 to launch and run a China offshoot of US accelerator Y Combinator. And that was only a year after AI superstar Andrew Ng departed Baidu for a new AI mission in Silicon Valley. As Li spoke, flashy surround-sound videos displayed Baidu’s new technologies for autonomous driving, smart-city projects in Beijing and Shanghai, and voice-activated speakers and lights. The crowd at the packed ballroom of the China World Hotel cheered loudly and clapped with each introduction: a pilot launch of 100 self-driving taxis in China’s central city Changsha, a partnership with Volvo to develop self-driving electric vehicles for the large China market, and an alliance with China’s large auto manufacturer FAW Group to produce autonomous passenger vehicles and start testing them in 2019 in Beijing and the northeast Chinese city Changchun.

Certainly, Toutiao is outpacing traditional news portals in volume. Its content technology sorts and tags more than 200,000 articles and videos daily and personalizes news feeds based on analysis of data obtained through the users’ locations, phone model, and click history. Users open the app and access news through Toutiao’s 4,000 media partnerships without following other accounts, unlike Facebook or Twitter. Anu Hariharan, a partner with Y Combinator’s Continuity Fund in San Francisco, likens Toutiao to YouTube and technology news aggregator Techmeme in one. She finds the most interesting thing about Toutiao to be how it uses machine-and deep-learning algorithms to serve up personalized, high-quality content without any user inputs, social graphs, or product purchase history to rely on.19 From Sea to Shining Sea ByteDance has been moving up in recent years with content deals and smart acquisitions, fulfilling founder Zhang’s mission of making his startup borderless.


pages: 624 words: 127,987

The Personal MBA: A World-Class Business Education in a Single Volume by Josh Kaufman

Albert Einstein, Atul Gawande, Black Swan, business cycle, business process, buy low sell high, capital asset pricing model, Checklist Manifesto, cognitive bias, correlation does not imply causation, Credit Default Swap, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, David Ricardo: comparative advantage, Dean Kamen, delayed gratification, discounted cash flows, Donald Knuth, double entry bookkeeping, Douglas Hofstadter, en.wikipedia.org, Frederick Winslow Taylor, George Santayana, Gödel, Escher, Bach, high net worth, hindsight bias, index card, inventory management, iterative process, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Kickstarter, Lao Tzu, lateral thinking, loose coupling, loss aversion, Marc Andreessen, market bubble, Network effects, Parkinson's law, Paul Buchheit, Paul Graham, place-making, premature optimization, Ralph Waldo Emerson, rent control, side project, statistical model, stealth mode startup, Steve Jobs, Steve Wozniak, subscription business, telemarketer, the scientific method, time value of money, Toyota Production System, tulip mania, Upton Sinclair, Vilfredo Pareto, Walter Mischel, Y Combinator, Yogi Berra

Join me at personalmba.com to explore these ideas in more detail and learn how to apply them to your daily life and work. Let’s begin. 2 VALUE CREATION Make something people want . . . There’s nothing more valuable than an unmet need that is just becoming fixable. If you find something broken that you can fix for a lot of people, you’ve found a gold mine. —PAUL GRAHAM, FOUNDER OF Y COMBINATOR, VENTURE CAPITALIST, AND ESSAYIST AT PAULGRAHAM.COM Every successful business creates something of value. The world is full of opportunities to make other people’s lives better in some way, and your job as a businessperson is to identify things that people don’t have enough of, then find a way to provide them. The value you create can take on one of several different forms, but the purpose is always the same: to make someone else’s life a little bit better.

If you have enough profit to do the things you need to do to keep the business running and make it worth your time, you’re successful, no matter how much revenue your business brings in. Sufficiency is the point where a business is bringing in enough profit that the people who are running the business find it worthwhile to keep going for the foreseeable future. Paul Graham, venture capitalist and founder of Y Combinator (an early-stage venture capital firm), calls the point of sufficiency “ramen profitable”—being profitable enough to pay your rent, keep the utilities running, and buy inexpensive food like ramen noodles. You may not be raking in millions of dollars, but you have enough revenue to keep building your venture without going under. You can’t create value if you can’t pay the bills. If you’re not bringing in sufficient revenue to cover the operating expenses, that’s a major issue.

See Working with others testing Working with others attribution error authority bystander apathy clanning commander’s intent commitment and consistency communication overhead comparative advantage convergence and divergence golden trifecta importance, feeling of incentive-caused bias management modal bias option orientation planning fallacy and power Pygmalion effect reasons for action, giving recommended reading referrals safety, feeling of social proof social signals Wozniak, Steve Y Combinator Zappos


pages: 309 words: 81,975

Brave New Work: Are You Ready to Reinvent Your Organization? by Aaron Dignan

"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, Black Swan, blockchain, Buckminster Fuller, Burning Man, butterfly effect, cashless society, Clayton Christensen, clean water, cognitive bias, cognitive dissonance, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, David Heinemeier Hansson, deliberate practice, DevOps, disruptive innovation, don't be evil, Elon Musk, endowment effect, Ethereum, ethereum blockchain, Frederick Winslow Taylor, future of work, gender pay gap, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, hiring and firing, hive mind, income inequality, information asymmetry, Internet of things, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, Lean Startup, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, new economy, Paul Graham, race to the bottom, remote working, Richard Thaler, shareholder value, Silicon Valley, six sigma, smart contracts, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, source of truth, Stanford marshmallow experiment, Steve Jobs, TaskRabbit, the High Line, too big to fail, Toyota Production System, uber lyft, universal basic income, Y Combinator, zero-sum game

You’ll be surprised how easy it is to scale something that has been validated and improved by the people who have to use it every day. When your team is taking smaller bites, there’s a feeling of momentum, and the electricity of that is palpable. Other teams see it. They feel it. And they want it for themselves. None of this is to say that scale doesn’t matter, just that it’s not our first priority. Paul Graham, one of the cofounders of the startup incubator Y Combinator, advises his startups to “do things that don’t scale.” What he means is that in the early days of anything new, worrying about scale can prevent us from learning, growing, and being remarkable. Think systemically. Act locally. And let scale happen. Learn by Doing We are all experts in our current way of working. After years or even decades of practice, we know how to play the game, even if the game is flawed.

., 62, 86 Theory X and Theory Y, 39–41, 130 Thomison, Tom, 89 tipping point, 216 Torvalds, Linus, 132 Toyota, 20, 111, 235 TPG, 253 traffic flow, 9–12, 45 roundabouts for, 10–12, 13, 47, 55 signal-controlled intersections for, 9–12, 13, 46, 55 tragedy of the commons, 98 training, 6, 156–57 transparency, 129, 130–31, 134, 136, 190, 195, 258 compensation and, 168, 169–71, 173 radical, 152, 154 trust, 236 twenty percent time, 107 Twitter, 84 Urwick, Lyndall, 25 User Manual to Me, 147–48 value creation, 78, 111–14, 160 Valve Software, 66, 107 Vang-Jensen, Frank, 227 Vanguard, 48 venture capital, 253 Vrba, Elisabeth, 103 VUCA, 43 wages, 34, 166 see also compensation Wallander, Jan, 94, 227 Warby Parker, 96 waterline principle, 69–70, 72 Weber, Max, 25 WeWork, 87 Whole Foods, 59, 61, 170, 259 Wikipedia, 140 Williams, Ev, 84–85 workflow, 14, 54, 110–17 working in public, 132 work in progress (WIP), 115–16, 132 World War II, 6–7 Wright, Orville and Wilbur, 103 Y Combinator, 230 Zanini, Michele, 26 Zappos, 144 al-Zarqawi, Abu Musab, 129 Zobrist, Jean-François, 37, 42–43 Zuckerberg, Mark, 88 ABCDEFGHIJKLMNOPQRSTUVWXYZ About the Author Aaron Dignan is the founder of The Ready, an organization design and transformation firm that helps institutions like Johnson & Johnson, Charles Schwab, Kaplan, Microsoft, Lloyds Bank, Citibank, Edelman, Airbnb, Cooper Hewitt Smithsonian Design Museum, and charity: water change the way they work.


pages: 252 words: 78,780

Lab Rats: How Silicon Valley Made Work Miserable for the Rest of Us by Dan Lyons

Airbnb, Amazon Web Services, Apple II, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, business process, call centre, Clayton Christensen, clean water, collective bargaining, corporate governance, corporate social responsibility, creative destruction, cryptocurrency, David Heinemeier Hansson, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, full employment, future of work, gig economy, Gordon Gekko, greed is good, hiring and firing, housing crisis, income inequality, informal economy, Jeff Bezos, job automation, job satisfaction, job-hopping, John Gruber, Joseph Schumpeter, Kevin Kelly, knowledge worker, Lean Startup, loose coupling, Lyft, Marc Andreessen, Mark Zuckerberg, McMansion, Menlo Park, Milgram experiment, minimum viable product, Mitch Kapor, move fast and break things, move fast and break things, new economy, Panopticon Jeremy Bentham, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, precariat, RAND corporation, remote working, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Sam Altman, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, Skype, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, Stanford prison experiment, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, TaskRabbit, telemarketer, Tesla Model S, Thomas Davenport, Tony Hsieh, Toyota Production System, traveling salesman, Travis Kalanick, tulip mania, Uber and Lyft, Uber for X, uber lyft, universal basic income, web application, Whole Earth Catalog, Y Combinator, young professional

Women represent only 15 percent of decision-making roles. VCs claim that they make decisions based entirely on the strength of the company’s ideas, and without any regard for race or gender. But can you guess where the members of the White Man Club tend to put their money? “I can be tricked by anyone who looks like Mark Zuckerberg” is how Paul Graham, the founder of Y Combinator, a top Silicon Valley start-up incubator, once famously put it. Graham later claimed he was joking, but a glance through the roster of Y Combinator portfolio companies turns up an awful lot of nerdy young Zuckerberg clones. As for why there are so few women in venture capital, Michael Moritz, a partner at Sequoia Ventures, once said that it’s not because of gender bias but that “What we’re not prepared to do is to lower our standards.” The obtuseness, arrogance, and self-regard of that comment boggles the mind.


pages: 291 words: 90,771

Upscale: What It Takes to Scale a Startup. By the People Who've Done It. by James Silver

Airbnb, augmented reality, Ben Horowitz, blockchain, business process, call centre, credit crunch, crowdsourcing, DevOps, family office, future of work, Google Hangouts, high net worth, hiring and firing, Jeff Bezos, Kickstarter, Lean Startup, Lyft, Mark Zuckerberg, minimum viable product, Network effects, pattern recognition, ride hailing / ride sharing, Silicon Valley, Skype, Snapchat, software as a service, Uber and Lyft, uber lyft, women in the workforce, Y Combinator

‘That would also be TransferWise’s challenge, probably not for the next five years, but sometime after their ten-year anniversary - but they’ll be well prepared for it, I’m sure.’ It’s a challenge which Seedcamp itself - once the European disruptor and answer to Silicon Valley’s Y Combinator, but now in its second decade - also faces. While Sohoni’s startup blazed a trail as Europe’s first seed-stage startup accelerator, according to the European Accelerator Report there are now at least 113 tech accelerators across Europe - a host of rivals and also-rans against which Seedcamp must continue to stand out. Today, like Y Combinator, it has been repositioned as a seed fund. ‘People are invested in our old story because it’s emotional and it was well known [in the industry]. There is that embedding in people’s consciousness about who we were and, as we evolve, that in itself becomes the challenge.


pages: 669 words: 210,153

Tools of Titans: The Tactics, Routines, and Habits of Billionaires, Icons, and World-Class Performers by Timothy Ferriss

Airbnb, Alexander Shulgin, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Ben Horowitz, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Black Swan, blue-collar work, Boris Johnson, Buckminster Fuller, business process, Cal Newport, call centre, Charles Lindbergh, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, commoditize, correlation does not imply causation, David Brooks, David Graeber, diversification, diversified portfolio, Donald Trump, effective altruism, Elon Musk, fault tolerance, fear of failure, Firefox, follow your passion, future of work, Google X / Alphabet X, Howard Zinn, Hugh Fearnley-Whittingstall, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Kickstarter, Lao Tzu, lateral thinking, life extension, lifelogging, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, Menlo Park, Mikhail Gorbachev, MITM: man-in-the-middle, Nelson Mandela, Nicholas Carr, optical character recognition, PageRank, passive income, pattern recognition, Paul Graham, peer-to-peer, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, PIHKAL and TIHKAL, post scarcity, post-work, premature optimization, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, risk tolerance, Ronald Reagan, selection bias, sharing economy, side project, Silicon Valley, skunkworks, Skype, Snapchat, social graph, software as a service, software is eating the world, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, superintelligent machines, Tesla Model S, The Wisdom of Crowds, Thomas L Friedman, Wall-E, Washington Consensus, Whole Earth Catalog, Y Combinator, zero-sum game

When you’re thinking of how to make your business bigger, it’s tempting to try to think all the big thoughts, the world-changing, massive-action plans. But please know that it’s often the tiny details that really thrill someone enough to make them tell all their friends about you. Spirit animal: Black bear * * * Alexis Ohanian Alexis Ohanian (TW/IG: @alexisohanian, alexisohanian.com) is perhaps best known for being a co-founder of Reddit and Hipmunk. He was in the very first class of Y Combinator, arguably the world’s most selective startup “accelerator,” where he is now a partner. He is an investor or advisor in more than 100 startups, an activist for digital rights (e.g., SOPA/PIPA), and the best-selling author of Without Their Permission. “You Are a Rounding Error” “[I had] an executive at Yahoo! who brought me and Steve in [for a potential acquisition discussion]—this was early in Reddit—and told us we were a rounding error because our traffic was so small. . . .

A Damn-Giving Assignment of Less Than 15 Minutes Improve a notification email from your business (e.g., subscription confirmation, order confirmation, whatever): “Invest that little bit of time to make it a little bit more human or—depending on your brand—a little funnier, a little more different, or a little more whatever. It’ll be worth it, and that’s my challenge.” (See Derek Sivers’s best email ever on page 192.) ✸ One of his questions for founders who apply to Y Combinator: “What are you doing that the world doesn’t realize is a really big fucking deal?” Giving Feedback to Founders—How Do You Express Skepticism? Alexis has many approaches, of course, but I liked this example of what Cal Fussman (page 495) might call “letting the silence do the work”: “I really think a lot can be conveyed with a raised eyebrow.” Organizations Alexis introduced me to: Electronic Frontier Foundation (eff.org) is the leading nonprofit organization defending civil liberties in the digital world.

It’s therefore nearly impossible for you to get a good statistical spread with $60K per year. The math just doesn’t work. The math especially doesn’t work if you screw it up like I did by getting overexcited and dropping $50K on your first investment. Here’s how I did a course correction and dealt with this problem: First, I invested very small amounts in a few select startups, ideally those in close-knit “seed accelerator” (formerly called “incubator”) networks like Y Combinator and Techstars. Then, I did my best to deliver above and beyond the value of my investment. In other words, I wanted the founders to ask themselves, “Why the hell is this guy helping us so much for a ridiculously small amount of equity?” This was critical for establishing a reputation as a major value-add, someone who helped a lot for very little. Second, leaning on this burgeoning reputation, I began negotiating blended agreements with startups involving some investment, but additional advisory equity as a requirement.


pages: 299 words: 91,839

What Would Google Do? by Jeff Jarvis

23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, barriers to entry, Berlin Wall, business process, call centre, cashless society, citizen journalism, clean water, commoditize, connected car, credit crunch, crowdsourcing, death of newspapers, different worldview, disintermediation, diversified portfolio, don't be evil, fear of failure, Firefox, future of journalism, G4S, Google Earth, Googley, Howard Rheingold, informal economy, inventory management, Jeff Bezos, jimmy wales, Kevin Kelly, Mark Zuckerberg, moral hazard, Network effects, new economy, Nicholas Carr, old-boy network, PageRank, peer-to-peer lending, post scarcity, prediction markets, pre–internet, Ronald Coase, search inside the book, Silicon Valley, Skype, social graph, social software, social web, spectrum auction, speech recognition, Steve Jobs, the medium is the message, The Nature of the Firm, the payments system, The Wisdom of Crowds, transaction costs, web of trust, WikiLeaks, Y Combinator, Zipcar

Idealab, founded by nonstop entrepreneur Bill Gross, has launched a large number of companies as an incubator, including Overture (which became the basis for Yahoo’s—and, indirectly, Google’s—search-ad industry), PetSmart, Picasa (now Google’s photo software), Citysearch, and the electric-car company Aptera Motors. Both incubators provide space, office services, advice, and money. Then there is a series of next-generation incubators built to advise and invest in new web 2.0 enterprises. These include Y Combinator, which funds small entrepreneurs and helps them get from idea to company; Seed Camp, which runs regular competitions for start-up help in Europe; and Betaworks, which funds and advises early start-ups. Investors still need to reach into the dorms at MIT and Stanford—or farther back into my son’s high school—where ideas are hatching. I decided to teach because I was no longer able to effect enough change in a media company and figured I could do more in the cause of innovation helping students as inventors.

See vendor relationship management Waghorn, Rick, 56 Wales, Jimmy, 60, 87 Wall Street Journal, 129 Wal-Mart, 54–55, 101 Washlet, 181 Wattenberg, Laura, 233 Weinberger, David, 3, 82, 96–97, 137, 149, 232 Westlaw, 224 widgets, 36–37 Wikia, 60 Wikileaks.org, 92–93 Wikinomics (Tapscott), 113, 151, 225 Wikipedia communities and, 50 growth of, 66 mistakes in, 92–93 open-source and, 60 speed of, 106 wikitorials, 86–87 Williams, Evan, 105–6 Williams, Raymond, 63 Wilson, Fred, 35, 176, 189–92, 225, 237 Wine.com, 158 WineLibrary.TV, 157 The Winner Stands Alone (Coelho), 142 Wired, 33 wireless access, 166 airlines and, 182–83 wireless spectrum, 166 The Wisdom of Crowds (Surowiecki), 88 The Witch of Portobello (Coelho), 142–43 WNYC, 128 Wojcicki, Anne, 205 Wolf, Maryanne, 235 World Economic Forum, 48, 113 Wyman, Bob, 211 Yahoo, 5, 36, 58 China and, 99–100 communities and, 50 Yang, Jerry, 36 Y Combinator, 193 youth, 191–94, 212 YouTube, 6, 20, 33, 37 Zappos, 161 Zara, 103–4 Zazzle, 180 Zell, Sam, 129 zero-based budgeting, 79–80 Zillow, 75, 80, 187 Zipcar, 176 Zopa, 196 Zuckerberg, Mark, 4, 48–53, 94–95 About the Author Jeff Jarvis is the proprietor of one of the Web’s most popular and respected blogs about the internet and media, Buzzmachine.com. He also writes the new media column for the Guardian in London.


pages: 374 words: 89,725

A More Beautiful Question: The Power of Inquiry to Spark Breakthrough Ideas by Warren Berger

Airbnb, carbon footprint, Clayton Christensen, clean water, disruptive innovation, fear of failure, Google X / Alphabet X, Isaac Newton, Jeff Bezos, jimmy wales, Joi Ito, Kickstarter, late fees, Lean Startup, Mark Zuckerberg, minimum viable product, new economy, Paul Graham, Peter Thiel, Ray Kurzweil, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, Stanford marshmallow experiment, Stephen Hawking, Steve Jobs, Steven Levy, Thomas L Friedman, Toyota Production System, Watson beat the top human players on Jeopardy!, Y Combinator, Zipcar

Gebbia says, they now started to think, Why not make a business out of this? What if we could create this same experience in every major city? Here is where the two dreamers ran headfirst into conventional wisdom. Initially, no one, outside of Chesky, Gebbia, and a third partner they brought on, thought this was an idea that made business sense or was worth supporting. Paul Graham, a renowned angel investor in Silicon Valley who runs the start-up incubator firm Y Combinator, believed quite simply, “No one would want to stay in23 someone else’s bed.” The idea that would eventually become Airbnb was challenging a basic assumption: that you needed established, reputable hotels to provide accommodation for out-of-town visitors. Those paying close attention might have noticed that just a few years prior to this, lots of people held similar assumptions about cars—you could buy them, you could rent them, but there was no practical way to share them.

When they noticed, for example, that exchanging money with apartment hosts was awkward—“It just felt like the whole experience was relaxed and fun, until it came time to pay,” Gebbia recalls—this spurred them to ask, What if you could pay online? When they noticed that many of the visitors to their site were asking about foreign cities, this led to a big question: Why are we limiting this to the U.S.? What if we go global? Within less than two years, they were in more than a hundred countries, doing a million bookings, and flush with more than one hundred million investment dollars. They had even won over early skeptics such as Y Combinator’s Graham, who became one of their seed investors. These days, Gebbia and Chesky are asking a whole new set of questions about whether it’s feasible to create a “sharing economy.” At the core of this idea is the fundamental question Why should we, as a society, continue to buy things that we really don’t need to own? (Consider, for example, that the average power24 drill in the United States is used a total of thirteen minutes in its lifetime.)


pages: 326 words: 91,559

Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy by Nathan Schneider

1960s counterculture, Affordable Care Act / Obamacare, Airbnb, altcoin, Amazon Mechanical Turk, back-to-the-land, basic income, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Brewster Kahle, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Clayton Christensen, collaborative economy, collective bargaining, Community Supported Agriculture, corporate governance, creative destruction, crowdsourcing, cryptocurrency, Debian, disruptive innovation, do-ocracy, Donald Knuth, Donald Trump, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, Food sovereignty, four colour theorem, future of work, gig economy, Google bus, hydraulic fracturing, Internet Archive, Jeff Bezos, jimmy wales, joint-stock company, Joseph Schumpeter, Julian Assange, Kickstarter, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, mass immigration, means of production, multi-sided market, new economy, offshore financial centre, old-boy network, Peter H. Diamandis: Planetary Resources, post-work, precariat, premature optimization, pre–internet, profit motive, race to the bottom, Richard Florida, Richard Stallman, ride hailing / ride sharing, Sam Altman, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, Silicon Valley, Slavoj Žižek, smart contracts, Steve Jobs, Steve Wozniak, Stewart Brand, transaction costs, Turing test, Uber and Lyft, uber lyft, underbanked, undersea cable, universal basic income, Upton Sinclair, Vanguard fund, white flight, Whole Earth Catalog, WikiLeaks, women in the workforce, working poor, Y Combinator, Y2K, Zipcar

At the Singularity meeting, he was the chief proponent of universal basic income, an idea that at the time still seemed novel. He cited recent basic-income experiments in India that showed promise for combating poverty among people the tech economy has left behind. Diamandis later reported having been “amazed” by the potential.12 That year, also, celebrity investor Marc Andreessen told New York magazine that he considered basic income “a very interesting idea,” and Sam Altman of the elite startup accelerator Y Combinator called its implementation an “obvious conclusion.”13 Those were just the early salvos. What people generally mean by universal basic income is the idea of giving everyone enough money to provide for the necessities of life. Imagine, say, a $20,000 check every year for every US citizen. The idea appeals to hopeful longings for a humane, egalitarian sort of commonwealth—a recognition that people, including those who are currently poor, will know better than any top-down welfare program what to spend the money on.

That same week, an article appeared in the Atlantic making a “conservative case for a guaranteed basic income” on the basis of devolving federal powers.16 This is one of those rare notions that is sneaking into plausibility from both the political left and right, more quickly than many proponents expected. The idea gets less utopian by the moment. Barack Obama mentioned basic income approvingly in the waning days of his presidency. Governments from Finland to Hawaii are exploring policy options, and Y Combinator’s nonprofit arm is funding a private experiment of its own in Oakland. For years, the journalist and entrepreneur Peter Barnes has been calling for a universal dividend funded through the use of common goods, particularly a tax on carbon emissions; now, governments in places from California and Oregon to the District of Columbia have considered plans to implement such a system. One of Barnes’s champions is digital organizer Natalie Foster, who teamed up with Facebook co-founder Chris Hughes to mobilize executives, unions, and thought leaders of many stripes to unite behind payouts for all.17 Some basic income schemes bypass regular money altogether.


pages: 102 words: 27,769

Rework by Jason Fried, David Heinemeier Hansson

call centre, Clayton Christensen, Dean Kamen, Exxon Valdez, fault tolerance, James Dyson, Jeff Bezos, Ralph Nader, risk tolerance, Ruby on Rails, Steve Jobs, Tony Hsieh, Y Combinator

Fault-tolerant. Comfortable in Beta. Reworkable. The authors live by the credo ‘keep it simple, stupid’ and Rework possesses the same intelligence—and irreverence—of that simple adage.” —John Maeda, author of The Laws of Simplicity “Rework is like its authors: fast-moving, iconoclastic, and inspiring. It’s not just for startups. Anyone who works can learn from this.” —Jessica Livingston, partner, Y Combinator; author, Founders at Work INTRODUCTION FIRST The new reality TAKEDOWNS Ignore the real world Learning from mistakes is overrated Planning is guessing Why grow? Workaholism Enough with “entrepreneurs” GO Make a dent in the universe Scratch your own itch Start making something No time is no excuse Draw a line in the sand Mission statement impossible Outside money is Plan Z You need less than you think Start a business, not a startup Building to flip is building to flop Less mass PROGRESS Embrace constraints Build half a product, not a half-assed product Start at the epicenter Ignore the details early on Making the call is making progress Be a curator Throw less at the problem Focus on what won’t change Tone is in your fingers Sell your by-products Launch now PRODUCTIVITY Illusions of agreement Reasons to quit Interruption is the enemy of productivity Meetings are toxic Good enough is fine Quick wins Don’t be a hero Go to sleep Your estimates suck Long lists don’t get done Make tiny decisions COMPETITORS Don’t copy Decommoditize your product Pick a fight Underdo your competition Who cares what they’re doing?


pages: 368 words: 96,825

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

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

It syncs up with mobile devices. But mostly it’s an at-a-glance alert system—using its big flat screen to notify you about incoming cellular messages. The inPulse developed a core fan base, but because the first iteration worked only with a BlackBerry (this was 2008 and Migicovsky, like BlackBerry, was Canadian), it didn’t go big. Yet there was enough early initial traction that Migicovsky decided to move the project to Y Combinator in Silicon Valley, which is also where he found the seed money to start manufacturing an updated version of the inPulse. And that’s when he hit the wall. Some great customer feedback had led to further rounds of design improvements, which resulted in an entirely new watch, the Pebble. It’s a great watch. It syncs up with iPhone and Android, runs apps, and allows users to check their calendar.

Craig, 64, 65–66 Vicarious, 167, 295n video games, 38, 45, 117, 144 video surveillance, 43 Virgin Atlantic, 124, 125, 126 Virgin Galactic, 96–97, 115, 125, 127 Virgin Management group, 111, 127, 128 Virgin Music, 124, 125 voice recognition, 58 Voltaire, 275 Vor-Tek, 252–53 vWorker, 149 Wachs, Eli, 258 Walmart, 72, 133 Wardenclyffe (Tesla’s laboratory), 178 Watson (IBM supercomputer), 56–57, 59 Waze, 47 web browsers, 11, 27 Wendy Schmidt Oil Cleanup XCHALLENGE, 247, 250, 251–53, 262, 263, 264 Weston, Graham, 50, 51, 257 Wikipedia, 11, 156, 291n Wilson, Rainn, 200, 207 Winning the Oil Endgame (Lovins), 222 Wired, 10, 15, 43, 135–36, 138, 144, 194, 224, 255 Wojcicki, Susan, 84 X.com, see PayPal XPRIZE competitions, 54, 96, 109, 112, 172, 244–45, 248–49, 255, 262, 265, 267, 272, 299n Ansari XPRIZE, 76, 96, 115, 127, 134, 246, 249, 253, 260, 261, 262, 263, 264, 265, 266, 267, 268 Google Lunar, 139, 249 Qualcomm Tricorder XPRIZE, 253 Wendy Schmidt Oil Cleanup XCHALLENGE of, 247, 250, 251–53, 262, 263, 264 XPRIZE Foundation, xi, xv, 115, 139, 237, 250, 257, 267, 269, 279, 299n Yahoo!, 15, 167 Y Combinator, 176 YouTube, 128, 135, 138, 154, 213, 254 Yucatan Peninsula, Mexico, ix Zappos, 80 Zero-G, 96, 110 Zip2, 117 Zooniverse, 145–46, 221, 228 Zuckerberg, Mark, 167 Simon & Schuster 1230 Avenue of the Americas New York, NY 10020 www.SimonandSchuster.com Copyright © 2015 by PHD Ventures All rights reserved, including the right to reproduce this book or portions thereof in any form whatsoever.


pages: 443 words: 98,113

The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay by Guy Standing

3D printing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, asset-backed security, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Big bang: deregulation of the City of London, bilateral investment treaty, Bonfire of the Vanities, Boris Johnson, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cashless society, central bank independence, centre right, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, credit crunch, crony capitalism, crowdsourcing, debt deflation, declining real wages, deindustrialization, disruptive innovation, Doha Development Round, Donald Trump, Double Irish / Dutch Sandwich, ending welfare as we know it, eurozone crisis, falling living standards, financial deregulation, financial innovation, Firefox, first-past-the-post, future of work, gig economy, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, housing crisis, income inequality, information retrieval, intangible asset, invention of the steam engine, investor state dispute settlement, James Watt: steam engine, job automation, John Maynard Keynes: technological unemployment, labour market flexibility, light touch regulation, Long Term Capital Management, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, means of production, mini-job, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, Neil Kinnock, non-tariff barriers, North Sea oil, Northern Rock, nudge unit, Occupy movement, offshore financial centre, oil shale / tar sands, open economy, openstreetmap, patent troll, payday loans, peer-to-peer lending, plutocrats, Plutocrats, Ponzi scheme, precariat, quantitative easing, remote working, rent control, rent-seeking, ride hailing / ride sharing, Right to Buy, Robert Gordon, Ronald Coase, Ronald Reagan, Sam Altman, savings glut, Second Machine Age, secular stagnation, sharing economy, Silicon Valley, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, Stephen Hawking, Steve Ballmer, structural adjustment programs, TaskRabbit, The Chicago School, The Future of Employment, the payments system, The Rise and Fall of American Growth, Thomas Malthus, Thorstein Veblen, too big to fail, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Y Combinator, zero-sum game, Zipcar

In 2016, pilots were being planned in nineteen Dutch municipalities, led by the city of Utrecht, and in Finland, where the government put aside funds (initially €20 million) for a pilot to last two years. On the other side of the Atlantic, the provincial government in Ontario, Canada, is planning a basic income experiment, and the provinces of Quebec and Alberta have indicated interest. There are also private initiatives that show up the timidity of politicians. In California, Sam Altman, president of Y Combinator, a start-up ‘accelerator’, has committed funds to a five-year basic income experiment. GiveDirectly, a charity that channels money directly from online donors to recipients, has moved from giving random individuals a basic income to more community-oriented experiments in Africa. In Germany, a crowdfunding scheme selects individuals by lottery to receive a basic income for a year. The challenge is to make these experiments into genuine basic income pilots in which everybody in a community is given an equal amount, not just selected individuals.

W. 1 Phillips curve 1 ‘pig cycle’ effects 1 Piketty, Thomas 1, 2 Pinochet, Augusto 1, 2, 3 platform debt 1 Plato 1 plutocracy 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 Polanyi, Karl 1 policing 1 political consultancy 1 Politico magazine 1 Ponzi schemes 1 Poor Law Amendment Act (1834) 1 POPS (privately owned public spaces) 1 Portfolio Recovery Associates 1 ‘postcapitalism’ 1 poverty traps 1, 2, 3 precariat and commons 1, 2, 3, 4, 5 and debt 1, 2 and democracy 1, 2 emergence of 1 growth of 1, 2 and rentier platforms 1, 2, 3 revolt of see revolt of precariat predatory creditors 1 ‘primitive rebel’ phase 1 Private Landlords Survey (2010) 1 privatisation and commons 1, 2, 3, 4, 5, 6, 7, 8, 9 and debt 1, 2 and democracy 1 and neo-liberalism 1 and rentier platforms 1 and revolt of precariat 1 and shaping of rentier capitalism 1, 2, 3, 4, 5, 6, 7 professionalism 1 ‘profit shifting’ 1 Property Law Act (1925) 1 Proudhon, Pierre-Joseph 1 Public and Commercial Services Union 1 PricewaterhouseCoopers (PwC) 1, 2, 3. 4, 5, 6 QE (quantitative easing) 1, 2, 3, 4, 5, 6 Quayle, Dan 1 QuickQuid 1 Reagan, Ronald 1, 2 reCAPTCHA security system 1 ‘recognition’ phase 1 ‘redistribution’ phase 1 Regeneron Pharmaceuticals 1 rentier platforms and automation 1 and cloud labour 1 and commodification 1 and ‘concierge’ economy 1 ecological and safety costs 1 and occupational dismantling 1 and on-call employees 1 and precariat 1, 2, 3 and revolt of precariat 1, 2 and ‘sharing economy’ 1, 2, 3, 4 and underpaid labour 1 and venture capital 1 rentiers ascendency of 1, 2 and British Disease 1 classical images of 1 and commons see commons and debt 1, 2, 3, 4, 5, 6, 7 and democracy 1, 2, 3, 4, 5, 6, 7 digital/tasking platforms see rentier platforms ‘euthanasia’ of 1, 2, 3, 4, 5, 6, 7 lies of rentier capitalism 1, 2, 3 revolt of precariat see revolt of precariat shaping of see shaping of rentier capitalism subsidies for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ‘representation’ phase 1 ‘repression effect’ 1 Research of Gartner 1 revolt of precariat and basic income systems 1 and commons 1, 2, 3, 4, 5 ‘euthanasia’ of rentiers 1, 2, 3, 4, 5 inequality of rentier capitalism 1, 2, 3 and intellectual property 1, 2, 3 and neo-liberalism 1, 2, 3, 4, 5, 6 organisational forms 1 potential growth of movement 1 progressive political reengagement 1, 2 and rentier platforms 1, 2 rights as demands 1 sovereign wealth funds 1 wage and labour regulation 1, 2 ‘right to buy’ schemes 1, 2, 3, 4 Robbins, Lionel 1 Rockefeller, David 1 Rockefeller, John D. 1 Rolling Stone 1 Romney, Mitt 1 Roosevelt, Franklin D. 1 Ross, Andrew 1 Ross, Michael 1 Rothermere, Viscount 1, 2 Royal Bank of Scotland 1, 2 Royal Mail 1 Royal Parks 1 Rubin, Robert 1, 2 Rudd, Amber 1 Ruralec 1 Ryan, Conor 1 Sainsbury, Lord 1 Samsung 1, 2, 3 Sanders, Bernie 1, 2, 3 Sassen, Saskia 1 school–business partnerships 1 Schröder, Gerhard 1 Schwab Holdings 1 Schwarz, Dieter 1 Scottish Water 1 Second Gilded Age 1, 2, 3 Securitas 1 securitisation 1, 2, 3 selective tax rates 1 Selma 1 shaping of rentier capitalism branding 1 Bretton Woods system 1, 2, 3 and copyright 1 and ‘crony capitalism’ 1, 2, 3 dispute settlement systems 1, 2, 3 global architecture of rentier capitalism 1 lies of rentier capitalism 1 and neo-liberalism 1, 2 patents 1 and privatisation 1, 2, 3, 4, 5, 6, 7 and ‘shock therapy’ 1, 2 trade and investment treaties 1 ‘sharing economy’ 1, 2, 3, 4, 5, 6 Shelter 1 ‘shock therapy’ 1, 2, 3, 4 Shore Capital 1 Sierakowski, Slawomir 1, 2, 3, 4 silicon revolution 1 Simon, Herbert 1 Sirius Minerals 1 Skoll Centre for Social Entrepreneurship 1 Sky UK 1, 2 SLABS (student loan asset-backed securities) 1, 2 Slim, Carlos 1, 2 Smith, Adam 1 Snow, John 1 Social Care Act (2012) 1 social commons 1, 2, 3 social dividend systems 1, 2 social housing 1 ‘social income’ 1, 2, 3, 4, 5, 6, 7, 8 social strike 1 SoFi (Social Finance) 1 Solidarność (Solidarity) movement 1 South West Water 1 sovereign wealth funds 1 spatial commons 1, 2 Speenhamland system 1, 2, 3 Spielberg, Steven 1 Springer 1 ‘squeezed state’ 1 Statute of Anne (1710) 1 Statute of Monopolies (1624) 1 StepChange 1 Stevens, Simon 1 ‘strategic’ debt 1 strike action/demonstrations 1, 2, 3 student debt 1, 2 subsidies 1 and austerity 1, 2 and bank ‘bailouts’ 1 and charities 1 and ‘competitiveness’ 1 direct subsidies 1 and moral hazards 1 and ‘non-dom’ status 1 and quantitative easing 1, 2 for rentiers 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 selective tax rates 1 and sovereign wealth funds 1 subsidised landlordism 1 tax avoidance and evasion 1 tax breaks 1, 2, 3, 4, 5 tax credits 1 Summers, Larry 1, 2 Sun, The 1, 2 Sunday Telegraph 1 Sunday Times 1 Sutton Trust 1 ‘sweetheart deals’ 1 tasking platforms see rentier platforms TaskRabbit 1, 2, 3, 4, 5 Tatler magazine 1 tax avoidance/evasion 1 tax breaks 1, 2, 3, 4, 5 tax credits 1, 2, 3 Tax Justice Network 1 Tax Research UK 1 Taylor & Francis 1 Tennessee Valley Authority 1 ‘tertiary time’ regime 1 Tesco 1 Texas Permanent School Fund 1 Textor, Mark 1 Thames Water 1 Thatcher, Margaret 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 The Bonfire of the Vanities 1 The Constitution of Liberty 1 The General Theory of Employment, Interest and Money 1 The Innovator’s Dilemma 1 think tanks 1 ‘thinner’ democracy 1 ‘Third-Way’ thinking 1, 2, 3 Times, The 1 TISA (Trade in Services Agreement) 1 Tottenham Court Road underground station 1 TPP (Trans-Pacific Partnership) 1, 2, 3 Trades Union Congress 1, 2 ‘tragedy of the commons’ 1 ‘tranching’ of loans 1 Treaty of Detroit (1950) 1, 2 Treuhand 1 TRIPS (Agreement on Trade-Related Aspects of Intellectual Property Rights) 1, 2, 3, 4 trolling (of patents) 1 Trump, Donald 1, 2 TTIP (Trans-Atlantic Trade and Investment Partnership) 1, 2, 3, 4 Turnbull, Malcolm 1 Turner, Adair 1 Twain, Mark 1 Uber 1, 2, 3, 4, 5, 6, 7 ‘ultra-loose’ monetary policy 1 underpaid labour 1 UNESCO (UN Educational, Scientific and Cultural Organization) 1 UNHCR (UN refugee agency) 1 Unison 1 Unite 1 UnitedHealth Group 1 universal credit scheme 1 universal justice 1 UpCounsel 1 Upwork 1, 2 Uruguay Round 1, 2, 3 USPTO (US Patent and Trademark Office) 1 Vattenfall 1 Veblen, Thorstein 1 venture capital 1 Veolia 1 Vero Group 1 Victoria, Queen 1 Villeroy de Galhau, François 1 Vlieghe, Gertjan 1 Warner Chappell Music 1 Watt, James 1 welfare abuse/fraud 1 Wilde, Oscar 1 Wilson, Fergus 1 Wilson, Judith 1 WIPO (World Intellectual Property Organization) 1, 2, 3, 4, 5, 6 Wolf, Martin 1, 2 Wolfe, Tom 1 Wonga 1, 2 Work Capability Assessment 1 Work Programme 1 World Bank 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 World Economic Forum 1 world heritage sites 1 Wriglesworth Consultancy 1 WTO (World Trade Organization) 1, 2, 3, 4, 5, 6 Y Combinator 1 Yanukovych, Viktor 1 Yukos 1 de Zayas, Alfred-Maurice 1 van Zeeland, Marcel 1 Zell, Sam 1 zero-hours contracts 1, 2, 3 Zipcar 1 Copyright First published in Great Britain in 2016 by Biteback Publishing Ltd Westminster Tower 3 Albert Embankment London SE1 7SP Copyright © Guy Standing 2016 Guy Standing has asserted his right under the Copyright, Designs and Patents Act 1988 to be identified as the author of this work.


pages: 344 words: 96,020

Hacking Growth: How Today's Fastest-Growing Companies Drive Breakout Success by Sean Ellis, Morgan Brown

Airbnb, Amazon Web Services, barriers to entry, Ben Horowitz, bounce rate, business intelligence, business process, correlation does not imply causation, crowdsourcing, DevOps, disruptive innovation, Elon Musk, game design, Google Glasses, Internet of things, inventory management, iterative process, Jeff Bezos, Khan Academy, Kickstarter, Lean Startup, Lyft, Mark Zuckerberg, market design, minimum viable product, Network effects, Paul Graham, Peter Thiel, Ponzi scheme, recommendation engine, ride hailing / ride sharing, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, software as a service, Steve Jobs, subscription business, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, working poor, Y Combinator, young professional

MB: For Erika, Banks, and Audrey Grace Cover Title Page Copyright Dedication INTRODUCTION PART I : THE METHOD CHAPTER ONE: BUILDING GROWTH TEAMS CHAPTER TWO: DETERMINING IF YOUR PRODUCT IS MUST-HAVE CHAPTER THREE: IDENTIFYING YOUR GROWTH LEVERS CHAPTER FOUR: TESTING AT HIGH TEMPO PART II : THE GROWTH HACKING PLAYBOOK CHAPTER FIVE: HACKING ACQUISITION CHAPTER SIX: HACKING ACTIVATION CHAPTER SEVEN: HACKING RETENTION CHAPTER EIGHT: HACKING MONETIZATION CHAPTER NINE: A VIRTUOUS GROWTH CYCLE ACKNOWLEDGMENTS NOTES When I (Sean) got a call from Dropbox founder Drew Houston in 2008, I was immediately intrigued by the predicament the one-year-old start-up was in. The company’s cloud-based file storage and sharing service had built up a good early fan base, concentrated primarily among the tech-savvy community centered in Silicon Valley. Even before the product was completely built, Houston had pushed a video prototype online illustrating how the service would work, which had earned him the backing of the powerful Y Combinator start-up incubator and drawn a flood of early adopters. It became pretty clear that Houston was on to something when the waiting list he was keeping for the beta version grew from 5,000 to 75,000 in a blink of an eye when a second video was posted on news aggregator site Digg and went viral.1 The next wave of users who signed up after the public launch were happy with the service, but Houston was still running into a wall trying to break out beyond the tech elite.

As Facebook’s original growth team lead, Chamath Palihapitiya, wisely cautioned in one talk, “If you can’t be extremely clinical and extremely unemotionally detached from the thing that you’re building, you will make these massive mistakes and things won’t grow because you don’t understand what’s happened.”9 To clarify how dedication to improving a North Star metric helps make difficult decisions about how to spend time and resources, let’s look at how the Airbnb founders decided to conduct an experiment they thought might generate more nights booked—their North Star. To begin, they looked at their data to identify markets where bookings were lagging and, to their surprise, discovered that New York City was underachieving. Clearly, New York is a major tourist destination, so they dug in, with early investor Paul Graham of Y Combinator, to analyze why bookings weren’t stronger. Reviewing the apartment listings for the city, cofounder Joe Gebbia recalls that “the photos were really bad. People were using camera phones and taking Craigslist-quality pictures. Surprise! No one was booking because you couldn’t see what you were paying for.” Graham recommended that the two experiment with a hack to improve bookings that was low tech and high effort—but it was fast to execute on and wound up incredibly effective.


pages: 100 words: 31,338

After Europe by Ivan Krastev

affirmative action, bank run, Berlin Wall, central bank independence, clean water, conceptual framework, creative destruction, deindustrialization, Donald Trump, eurozone crisis, failed state, Fall of the Berlin Wall, Francis Fukuyama: the end of history, illegal immigration, job automation, mass immigration, moral panic, open borders, post-work, postnationalism / post nation state, Silicon Valley, Slavoj Žižek, too big to fail, Wolfgang Streeck, World Values Survey, Y Combinator

The fear of a barbarian invasion coexists with a fear of a robot-driven transformation of the workplace. In the technological dystopia that we see dawning, there will be no jobs left for human beings. According to a recent UK government study, over the next thirty years, 43 percent of current jobs in the EU will be automated. How society will function when work is a privilege and not a right or duty is not a theoretical question. Y Combinator, a big start-up incubator, has already announced it will conduct a basic income experiment with roughly one hundred families in Oakland, California, giving them between $1,000 and $2,000 a month for up to a year, no strings attached, to see what people do when they do not need to work to earn a living. The prospect of a jobless future is a major intellectual and existential challenge. How people will be capable of producing meaning in their lives in a postwork society is a question no less pressing than how democracy itself can function in a posttruth political world.


pages: 406 words: 109,794

Range: Why Generalists Triumph in a Specialized World by David Epstein

Airbnb, Albert Einstein, Apple's 1984 Super Bowl advert, Atul Gawande, Checklist Manifesto, Claude Shannon: information theory, Clayton Christensen, clockwork universe, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, deliberate practice, Exxon Valdez, Flynn Effect, Freestyle chess, functional fixedness, game design, Isaac Newton, Johannes Kepler, knowledge economy, lateral thinking, longitudinal study, Louis Pasteur, Mark Zuckerberg, medical residency, meta analysis, meta-analysis, Mikhail Gorbachev, Nelson Mandela, Netflix Prize, pattern recognition, Paul Graham, precision agriculture, prediction markets, premature optimization, pre–internet, random walk, randomized controlled trial, retrograde motion, Richard Feynman, Richard Feynman: Challenger O-ring, Silicon Valley, Stanford marshmallow experiment, Steve Jobs, Steve Wozniak, Steven Pinker, Walter Mischel, Watson beat the top human players on Jeopardy!, Y Combinator, young professional

,” their work indicated that it is better to be a scientist of yourself, asking smaller questions that can actually be tested—“Which among my various possible selves should I start to explore now? How can I do that?” Be a flirt with your possible selves.* Rather than a grand plan, find experiments that can be undertaken quickly. “Test-and-learn,” Ibarra told me, “not plan-and-implement.” Paul Graham, computer scientist and cofounder of Y Combinator—the start-up funder of Airbnb, Dropbox, Stripe, and Twitch—encapsulated Ibarra’s tenets in a high school graduation speech he wrote, but never delivered: It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it’s hard to get an accurate picture of most jobs. . . . Most of the work I’ve done in the last ten years didn’t exist when I was in high school. . . .

Brewer, “Ester Ledecka Is the Greatest Olympian at the Games, Even If She Doesn’t Know It,” Washington Post, February 24, 2018, online ed. “I was doing so many different sports”: J. Drenna, “Vasyl Lomachenko: ‘All Fighters Think About Their Legacy. I’m No Different,’” Guardian, April 16, 2018, online ed. “young people are just smarter”: M. Coker, “Startup Advice for Entrepreneurs from Y Combinator,” VentureBeat, March 26, 2007. a tech founder who is fifty: P. Azoulay et al., “Age and High-Growth Entrepreneurship,” NBER Working Paper No. 24489 (2018). “No one imagined silos like that”: G. Tett, The Silo Effect: The Peril of Expertise and the Promise of Breaking Down Barriers (New York: Simon & Schuster, 2015 [Kindle ebook]). if they were admitted during a national cardiology meeting: A.


pages: 397 words: 102,910

The Idealist: Aaron Swartz and the Rise of Free Culture on the Internet by Justin Peters

4chan, activist lawyer, Any sufficiently advanced technology is indistinguishable from magic, Bayesian statistics, Brewster Kahle, buy low sell high, crowdsourcing, disintermediation, don't be evil, global village, Hacker Ethic, hypertext link, index card, informal economy, information retrieval, Internet Archive, invention of movable type, invention of writing, Isaac Newton, John Markoff, Joi Ito, Lean Startup, moral panic, Paul Buchheit, Paul Graham, profit motive, RAND corporation, Republic of Letters, Richard Stallman, selection bias, semantic web, Silicon Valley, social web, Steve Jobs, Steven Levy, Stewart Brand, strikebreaker, Vannevar Bush, Whole Earth Catalog, Y Combinator

“Animals,” Graham called them: tenacious and intelligent young self-starters who didn’t need Ping-Pong tables in the office as long as they had a case of Dr Pepper and a reliable Internet connection. Graham decided to test his hypothesis and, in March 2005, announced that he was soliciting applications for a project he called the Summer Founders Program—an early version of what would eventually become the renowned start-up incubator Y Combinator. “The SFP is like a summer job, except that instead of salary we give you seed funding to start your own company with your friends,” he wrote on his blog.11 Aspiring young entrepreneurs proposed ideas for start-up companies to Graham; the most promising applicants would be invited to move to Cambridge, Massachusetts, and participate in a sort of start-up summer camp. The participants would each receive approximately $6,000 in seed funding and would spend the summer developing their businesses and learning from Graham and his well-connected friends.

., 25, 32, 33 Woodhull, Nathan, 10, 259 WordPress, 241 work as identity, 146 WorldCat, 179 World War I, 77 World War II, 78, 82, 208 World Wide Web: anniversary of, 237–38 archiving all of, 135–36, 173 commercial potential of, 112 as infinite library, 127–28 and Internet, 98, 108–10 introduction of, 98, 108 linking capacity of, 108, 238 malignant forces vs., 238 open, collaborative, 178, 237 popularization of, 112 World Wide Web Consortium (W3C), 127–29 Wyden, Ron, 226, 231 Xerox photocopy machine, 87–88 Xerox Sigma V mainframe, 95–97, 113 Yahoo, 185 Y Combinator, 147 Young America, 50–53 Zanger, Jules, 44 SCRIBNER An Imprint of Simon & Schuster, Inc. 1230 Avenue of the Americas New York, NY 10020 www.SimonandSchuster.com Copyright © 2016 by Justin Peters All rights reserved, including the right to reproduce this book or portions thereof in any form whatsoever. For information, address Scribner Subsidiary Rights Department, 1230 Avenue of the Americas, New York, NY 10020.


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, Charles Lindbergh, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, disruptive innovation, Donald Trump, Electric Kool-Aid Acid Test, 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, Joan Didion, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, 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

And people who like those kinds of things can go there and experience that. It’s not only Page. Jeff Bezos and Elon Musk dream of establishing Learyesque space colonies, celestial Burning Mans. Peter Thiel is slightly more down to earth. His Seasteading Institute hopes to set up floating technology incubation camps on the ocean, outside national boundaries. “If you can start a new business, why can you not start a new country?” he asks. In a speech last fall at the Y Combinator Startup School, venture capitalist Balaji Srinivasan channeled Leary when he called for “Silicon Valley’s Ultimate Exit”—the establishment of a new country beyond the reach of the U.S. government and other allegedly failed states. “You know, they fled religious persecution, the American Revolutionaries which left England’s orbit,” Srinivasan said, referring to the Pilgrims. “Then we started moving west, leaving the East Coast bureaucracy.”

(Starr), 218 When We Are No More (Rumsey), 325–27 Whitman, Walt, 20, 183, 184 wicks, 229–30 Wiener, Anthony, 315 wiki, as term, 19 “wikinomics,” 84 Wikipedia, xvi, 21, 192 in fact-mongering, 58 hegemony of, 68 ideological split in, 18–20 slipshod quality of, 5–8 wiki-sects, 18 Wilde, Oscar, 174, 308 Williams, Anthony, 84 Wilson, Fred, 11 Windows Home Server, 32 Winer, Dave, 35 wings, human fascination with, 329–30, 335, 340–42 wingsuits, 341–42 Wired, xvii, xxi, 3, 4, 106, 156, 162, 174, 195, 232 Wittgenstein, Ludwig, 215 Wolf, Gary, 163 Wolf, Maryanne, 234 Wolfe, Tom, 170 work: as basis for society, 310–11, 313 in contemplative state, 298–99 efficiency in, 165–66, 237–38 job displacement in, 164–65, 174, 310 trivial alternatives to, 64 World Brain (Wells), 267 World Health Organization, 244 World of Warcraft, 59 Wozniac, Steve “Woz,” 32 Wright brothers, 299 writing: archiving of, 325–27 and invention of paper, 286–87 writing skills, changes in, 231–32, 234–35, 240 Xbox, 64, 93, 260 X-Ray Spex, 63 Yahoo, 67, 279–80 Yahoo People Search, 256 Y Combinator Startup School, 172 Yeats, William Butler, 88 Yelp, 31 Yosemite Valley, 341–42 youth culture, 10–11 as apolitical, 294–95 music and, 125 TV viewing in, 80–81 YouTube, 29, 31, 58, 75, 81, 102, 186, 205, 225, 314 technology marketing on, 108–9 Zittrain, Jonathan, 76–77 zombies, 260, 263 Zuckerberg, Mark, xvii, xxii, 53, 115, 155, 158, 215, 225 Facebook Q & A session of, 210–11, 213, 214 imagined as jackal, xv ALSO BY NICHOLAS CARR The Glass Cage The Shallows The Big Switch Does IT Matter?


pages: 647 words: 43,757

Types and Programming Languages by Benjamin C. Pierce

Albert Einstein, combinatorial explosion, experimental subject, finite state, Henri Poincaré, Perl 6, Russell's paradox, sorting algorithm, Turing complete, Turing machine, type inference, Y Combinator

Putting all this together, suppose we have a whole program that does some complicated calculation with numbers to yield a boolean result. If we replace all the numbers and arithmetic operations with lambda-terms representing them and evaluate the program, we will get the same result. Thus, in terms of their effects on the overall results of programs, there is no observable difference between the real numbers and their Church-numeral representation. [7]It is often called the call-by-value Y-combinator. Plotkin (1975) called it Z. [8]Note that the simpler call-by-name fixed point combinator Y = λf. (λx. f (x x)) (λx. f (x x)) is useless in a call-by-value setting, since the expression Y g diverges, for any g. [9]It is also possible to derive the definition of fix from first principles (e.g., Friedman and Felleisen, 1996, Chapter 9), but such derivations are also fairly intricate.

—Albert Einstein * * * * * * Index symbol Î alternate notation for type membership, 92 ⇒ arrow kind, 441 ⇓ big-step evaluation, 42 Π dependent function type, 463 :: derivation of, 203 ↑ divergence, 16 dom(Г) domain of Г, 101 ⋆ "quick check" exercise, xviii ⋆⋆ easy exercise, xviii ⋆⋆⋆ moderate exercise, xviii ⋆⋆⋆⋆ challenging exercise, xviii ↛ exercise without solution, xviii → function type, 100 :: kind membership, 449 →* multi-step evaluation, 39 → one-step evaluation, 36 ⇛ parallel reduction of types, 454 L record labels, 129 R+ transitive closure of R, 17 R* reflexive, transitive closure, 17 ▸ sample output from system, 25 \ set difference, 15 ↑d() shifting, 79 σ ∘ γ substitution composition, 318 <: subtyping, 181 ↓ termination, 16 ≡ type equivalence, 447, 453 : type membership, 92 _ wildcard binder, 46, 121 α conversion, 71 * * * * * * Index A abbreviations, see also derived forms parametric type-, 439 Abel, 409 abstract data types, 11, 226, 368–372 parametric, 450–453 partially abstract, 406 vs. objects, 374–377 abstract machine, 32 with store, 160 abstract syntax, 25, 53 tree, 53 abstraction full, 143 functional, 52 type abstraction and ascription, 123 abstraction principle, 339 abstractions, protecting user-defined, 3, 5, 368–377 activation record, 174 ad-hoc polymorphism, 340 ADT, see abstract data type Algol-60, 11 Algol-68, 11 Algorithm W (Damas and Milner), 337 algorithmic subtyping, 209–213, 417–436 algorithmic typing, 213–218 aliasing, 155–157 compiler analysis of, 170 allocation of references, 154 allsome implementation, 381–387 alpha-conversion, 71 Amadio-Cardelli algorithm for recursive subtyping, 309–311 Amber, 311 rule, 311, 312 AnnoDomini, 9 annotations and uniqueness of types, 135, 141 datatype constructors as, 355 implicit, 330–331 antisymmetric relation, 16 applications of type systems, 8–9 arith implementation, 23–49 arithmetic expressions typed, 91–98 untyped, 23–44 arrays bounds checking, 7 subtyping, 198–199 arrow types, 99–100 ascription, 121–123, 193, see also casting and subtyping, 193–196 assembly language, typed, 11 assignment to references, 153, 154 associativity of operators, 53 atomic types, see base types Automath, 11 automatic storage management, see garbage collection axiom, 27 axiomatic semantics, 33 * * * * * * Index B β-reduction, 56 Barendregt convention, 75 Barendregt cube, 465 base types, 117–118 and subtyping, 200 behavioral equivalence, 64 beta-reduction, 56 big-step operational semantics, 32, 43 binary methods, 375–377 binary operations on abstract data, 375–377 strong vs. weak, 375 binary relation, 15 binder, 55 binding (OCaml datatype of bindings), 85, 113–115 bisimulation, 284 BNF (Backus-Naur form), 24 booleans, 23–44, see also Church encodings Bot type, 191–193 algorithmic issues, 220 with bounded quantification, 436 bot implementation, 220 bottom-up subexpressions of a recursive type, 304 bound variables, 55, 69–72 bounded meet, 219 bounded quantification, 11, 389–409 and intersection types, 400, 409 existential types, 406–408, 435–436 higher-order, 467–473 joins and meets, 432–435 object encodings, 411–416 typechecking algorithms, 417–436 undecidability, 427–431 with Bot type, 436 bounded type operators, 467, 473 bounds checking, see arrays boxed values, 201 boxed vs. unboxed argument passing, 341 * * * * * * Index C C, 6, 45 C#, 7, see also Java C++, 6, 226, see also Java c0, c1, c2, etc. (Church numerals), 60 calculus of constructions, 11, 465 call stack and exception handling, 173–174 call-by-name evaluation, 57 call-by-need evaluation, 57 call-by-value evaluation, 57 call-by-value Y-combinator, 65 call/cc, see continuations candidate, reducibility, 150 canonical forms lemma, 96, 105, 190, 405, 458 capture-avoiding substitution, 70 cartesian product type, 126–127 casting, 193–196, 247–264, 357, see also ascription and abstraction, 194 and reflection, 196 as substitute for polymorphism, 195–196 implementation, 196 categorial grammar, 9 category theory, 12 CCS, 34 Cecil, 226, 340 cell, see references chain, 18 channel types, 200 and subtyping, 200 chapter dependencies, xv Church encodings booleans, 58–59 in System F, 347–353 numerals, 60–63 pairs, 60, 396–400 records, 396–400 subtyping, 396–400 Church-Rosser property, 455 Church-style presentation, 111 class, 227, 231 granularity of, 231 classification, type systems as formalisms for, 2 Clean, 338 CLOS, 226, 340 closed set, 282 closed term, 55 closure, 17 property, 289 CLU, 11, 408 codomain of a relation, 16 coercion semantics for subtyping, 200–206, 224 coherence, 204–206 coinduction, 281–313 defined, 282–284 collection classes, 195–196 colored local type inference, 355 combinator, 55 combinatory logic, 76 complete induction, 19 completely bounded quantification, 431 completeness, 212 composition of substitutions, 318 compositionality, 2 comprehension notation for sets, 15 computation rules, 35, 72 computational effects, 153 concrete rule, 27 concrete syntax, 53 confluence, see Church-Rosser property congruence rules, 35, 72 conservativity of type analyses, 2, 92, 99–100 consistent set, 282 constraint types, 337 constraint-based typing rules, 321–326 constructive logic, 108 constructive type theory, 2, 11 constructors, see type operators contexts, 76–78 ML implementation, 83–85, 113–115 naming, 77 typing, 101 continuations, 178, 377 contractiveness, 300 contravariant position in a type, 185 type operator, 473 correctness by construction, 464 countable set, 15 counting subexpressions of μ-types, 304–309 course syllabi, xvii covariant position in a type, 185 type operator, 473 cube, Barendregt, 465 Curry-Howard correspondence, 2, 108–109, 341, 429 Curry-style presentation, 111 currying, 58, 73 of type operators, 440 cut elimination, 109 * * * * * * Index D Damas-Milner polymorphism, 331 dangling reference, 158 databases, 9, 142, 207 datatypes, 355, see also abstract data types constructors as type annotations, 355 parametric, 444-445 recursive, 277-278 vs. variant types, 140-142 de Bruijn indices, 75-81, 83-88, 381-387 levels, 81 pronunciation, 76 terms, 76 decidability, see also undecidability of Fω, 459-460 of kernel F<: subtyping, 423 declarative subtyping and typing relations, 210 decreasing chain, 18 definedness, 16 definitional equivalence of types, 441, 447 definitions formalization of, 441 of programming languages, 7 delegation, 227, 264 denotational semantics, 33 dependencies between chapters, xv dependent function types, 463 kinds, 445 types, 7, 11, 462-466, 473 depth of a term, 29 depth subtyping, 183 dereferencing, 154 derivable statement, 36 derivations evaluation, 36 induction on, 37 subtyping, 183-187 trees, 36, 102 typing, 94 derived forms, 51, 53, 119-121 desugaring, 121 determinacy of one-step evaluation, 37 diamond property, 455, 494 dimension analysis, 4 disjoint union, 142 divergent combinator, 65 divergeT, 145 documentation, types as, 5, 121 domain of a relation, 16 domain theory, 33 down-cast, see casting Dylan, 226 Dynamic type, 142 dynamic dispatch, 226 dynamic type testing, see casting dynamic typing, 2 * * * * * * Index E Edinburgh Logical Framework, see LF effects, 11, 153 efficiency, type systems and, 8 elaboration, 120 elimination rule, 108 encapsulation, 226 encodings, see object encodings enumerated type, 138 environment, 88 type-, 101 equi-recursive types, 280, 281 equirec implementation, 281-313 equi-recursive types, 275, 281-313 equivalence, see type equivalence equivalence, behavioral, 64 equivalence relation, 17 erasure, 109-110, 354-358 error, run-time, 42 error detection, use of types for, 4-5 evaluation, 34-43, 72-73 contexts, 261, 262 determinacy of, 37 lazy, 57 ML implementation, 47-49, 87 multi-step, 39 normalization by, 152 of nameless terms, 80-81 strategy, 35 strict vs. non-strict, 57 type-directed partial, 152 untyped lambda-calculus, 55-58 vs. reduction (terminology), 34 exceptions, 171-178 handlers, 171, 174 in Java and ML, 174 subtyping vs. polymorphism in typing of, 192 exercises, difficulty ratings, xviii existential objects, see objects, existential existential types, 11, 363-379 and modules, 364 bounded, 406-408 existential unificands, 320 expansion, 98, 108 explicit substitutions, 76, 88 explicitly typed languages, 101 exponential behavior of ML type reconstruction, 334 exposure, type-, 417-418 expressions vs. terms (termionology), 24 extended calculus of constructions, 11 Extended Static Checking, 3 extensible records, see row variables extensible variant type, 177 extensions of the simply typed lambda-calculus, 117-146 external language, 53, 120 * * * * * * Index F F, see System F Fω, see System Fω , see System F<:, see System F<: F-bounded quantification, 393, 408 F-closed set, 282 F-consistent set, 282 F1, F2, F3, etc., 461 factorial, 52 fail, 16 failure vs. undefinedness, 16 families (of terms, types), 462 Featherweight Java, 247–264 fields, see instance variables; records finalizers, 515 finding type errors, 545 finite tree type, 285 finite-state generating function, 294 first-class polymorphism, 340 fixed point, 142–145 combinator, 65 of a generating function, 282 theorem (Tarski-Knaster), 283 typing, using recursive types, 273 FJ, see Featherweight Java flattened data structures, 341 Float type, 117 fold function, 63 fomsub implementation, 467–473 formal methods, lightweight, 1 Forsythe, 11, 199 Fortran, 8, 11 fragments of System F, 358–359 fragments of System Fω, 461 free variable, 55, 69 fresh variable, 120 full abstraction, 143 full beta-reduction, 56 full F<:, 391 fullequirec implementation, 267–280 fullerror implementation, 171–178 fullfomsub implementation, 389–409, 467–473 fullfsub implementation, 389–409, 417–436 fullfsubref implementation, 411–416 fullisorec implementation, 275–278 fullomega implementation, 439–466 fullpoly implementation, 339–379 fullrecon implementation, 317–338 fullref implementation, 153–170, 225–245 fullsimple implementation, 99–111, 117–146 fullsub implementation, 181–208 fulluntyped implementation, 51–73 fullupdate implementation, 475–489 <fun>, 118 function types, 99–100 functional languages, mostly, 153 functions, 16 higher-order, 58 multi-argument, 58 on types, see type operators Funnel, 409 FX, 11 * * * * * * Index G garbage collection, 45, 158–165, 514–515 tag free, 341 general recursion, 142–145 generating function, 282 generating set, 290 generation lemma, see inversion lemma generators, classes as, 229 generics, 341 gfp algorithm, 292, 295–298 GJ, 195, 248, 409 grammar, 24 graph reduction, 57 greatest fixed point of a generating function, 283 greatest lower bound, see joins and meets greedy type inference, 355 * * * * * * Index H hash consing, 222 Haskell, 6, 45 heap, 153 hidden representation type, 364 higher-order bounded quantifiers, 468 higher-order functions, 58 higher-order polymorphism, 449–466 history of type systems, 10 hungry functions, 270 hybrid object models, 377 * * * * * * Index I identity, object, 245 identity function, 55 imperative objects, see objects, imperative implementations allsome, 381–387 arith, 23–49 bot, 220 equirec, 281–313 fomsub, 467–473 fullequirec, 267–280 fullerror, 171–178 fullfomsub, 389–409, 467–473 fullfsub, 389–409, 417–436 fullfsubref, 411–416 fullisorec, 275–278 fullomega, 439–466 fullpoly, 339–379 fullrecon, 317–338 fullref, 153–170, 225–245 fullsimple, 99–111, 117–146 fullsub, 181–208 fulluntyped, 51–73 fullupdate, 475–489 joinexercise, 223 joinsub, 218–220 purefsub, 417–436 rcdsub, 181–224 recon, 317–338 reconbase, 330 simplebool, 113–116 tyarith, 91–98 untyped, 83–88 implicit type annotations, 330–331 implicitly typed languages, 101 impredicative polymorphism, 340, 360–361 impure language features, 153 induction, 19 lexicographic, 19 logical relations proof technique, 150 mathematical foundations, 282–284 on derivations, 37 on natural numbers, 19 on terms, 29–32 inductive definitions, 23–29 inference, see type reconstruction inference rules, 26 mathematical foundations, 283 infinite types, 284–286 inheritance, 227 overrated, 245 injection into a sum type, 133 instance of an inference rule, 36 instance variables, 228, 230, 233–234 instanceof, 341 instantiation of a polymorphic function, 317–320, 342 intensional polymorphism, 340 interface, 226 interface types, 479 interfaces (in Java), 261 interference, syntactic control of, 170 intermediate language, 161 intermediate languages, typed, 11 internal language, 53, 120 internet, see web intersection types, 11, 206–207, 359, 489 and bounded quantification, 400, 409 and normal forms, 206 introduction rule, 108 invariant, 33 inversion lemma subtyping, 188 typing, 94, 104, 188, 457 iso-recursive types, 275, 280 subtyping, 311–312 * * * * * * Index J Java, 6, 8–10, 45, 119, 137, 154, 174, 177, 178, 193, 195, 196, 198–199, 226, 232, 247–264, 341, 444 exception handling in, 174 parametric polymorphism, 195 reflection, 196 JINI, 9 joinexercise implementation, 223 joins and meets, 17 algorithms for calculating, 218–220 in System F<:, 432–435 joinsub implementation, 218–220 judgment, 36 * * * * * * Index K KEA, 226 kernel F<:, 391 kinding, 439–447, 459 kinds dependent, 445 power, 445 row, 445 singleton, 445 Knaster-Tarski fixed point theorem, 283 * * * * * * Index L λ-calculus, see lambda-calculus λNB, 63-66 λ→, see simply typed lambda-calculus λω, see System λω λ<:, see simply typed lambda-calculus with subtyping label, 129 lambda cube, 465 lambda-& calculus, 226, 340 lambda-calculi, typed, 2 lambda-calculus, 51, 52 enriched, 63-68 simply typed, see simply typed lambda-calculus untyped, see untyped lambda-calculus lambda-term, 53 language definition, defined, 7 language design and type systems, 9-10 language features, pure, 153 late binding, see objects, open recursion latent type system, 2 lazy evaluation, 57 least fixed point of a generating function, 283 least upper bound, see joins and meets left-associativity of application, 54 let bindings, 124-125 let-polymorphism, 331-336, 340 exponential behavior, 334 levels, de Bruijn, 81 lexical analysis, 53 lexicographic induction, 19 lexicographic order, 19 LF, 11, 465 lfp algorithm, 294 lightweight formal methods, 1 linear logic and type systems, 11, 109 linking, 367 lists, 146 Church encoding, 350-353, 500 defined using recursive types, 267-270 polymorphic functions for, 345-347 subtyping, 197 local type inference, 355 location, 159 logic and type systems, 108 origins, 11 type systems in, 2 logical framework, 465 logical relations, 149 * * * * * * Index M μ, see least fixed point μ notation for recursive types, 299–304 marshaling, 252, 341 Martin-Löf type theory, see constructive type theory match function, 131 matching, pattern-, 130–131 matching relation on object types, 480 mathematics, formalization of, 11 meaning of terms, 32–34 meet, see joins and meets membership checking for (co-)inductively defined sets, 290–298 Mercury, 338 message, 226 meta-mathematics, 24 metalanguage, 24 metatheory, 24 metavariables, 24 naming conventions, 565 method, 226, 228 invocation, 226 multi-, see multi-method override, 233, 264 Milner-Mycroft Calculus, 338 minimal types, 218, 418–420 minimal typing theorem, 419 mini-ML, 337 ML, 6, 8, 9, 11, 174, 177 exception handling in, 174 history, 336–338 module system, 379 parametric datatypes, 445 polymorphism, 331–336 ML implementations evaluation, 87 simply typed lambda-calculus, 113–116 subtyping, 221–224 System F, 381–387 untyped arithmetic expressions, 45–49 untyped lambda-calculus, 83–88 ML-style polymorphism, 340 modal logics, 109 model checking, 1, 284 Modula-3, 7 modularity, 3 module systems, 364, 379, 465 monads, 153 monitoring, run-time, 1 monotone function, 282 monotype, 359 most general unifier, 327 mostly functional languages, 153 multi-argument functions, 58 multi-method, 226, 340 multiple inheritance, 489 multiple representations (of object types), 226 multi-step evaluation, 39 mutually recursive functions, 144 types, 253 v, see greatest fixed point nameless form, see de Bruijn indices naming context, 77 naming conventions for metavariables and rules, 565–566 narrowing lemmas, 401, 425 National Science Foundation, xx natural deduction, 26 natural semantics, 32, 34, 43 natural-number induction, 19 nested induction, 19 NextGen, 196 nominal type systems, 251–254, 312 normal forms, 38 and intersection types, 206 uniqueness of, 39 normal order, 56 normalization, 149–152 by evaluation, 152 strong, 152 normalization theorem, 39, 152, 353 numeric values, 40 NuPRL, 11 * * * * * * Index O object calculus, 11, 51, 184, 248, 251 object language, 24 Objective Caml see OCaml, xvii objects, 228, 368 as recursive records, 272 bounded quantification and, 411–416 encodings vs. primitive objects, 262–263 existential, 372–377, 475–489 hybrid object models, 377 identity, 245 imperative, 157, 225–245, 411–416 interface types, 479 Java-style, 247–264 matching relation on object types, 480 object-oriented programming, defined, 225–227 open recursion, 227, 235–244 purely functional, 372–377, 475–489 vs. abstract data types, 374–377 OCaml, xvii, 7, 45, 208, 231, 489 OCaml implementations, see ML implementations occur check, 327, 338 omega, 65 open recursion, see objects, open recursion operational semantics, 32, see also evaluation big-step, 43 small-step, 42 operator associativity, 53 operator precedence, 53 Option type, 137–138 order, well-founded, 18 ordered sets, basic definitions, 16–18 ordinary induction, 19 overloading, 340 finitary, 206 overriding of method definitions, 233 * * * * * * Index P P(S) powerset of S, 15 package, existential, 364 pairs, 126–127 Church encodings, see Church encodings, pairs parallel reduction, 454 parametric abbreviation, 439 data type, 142, 444 polymorphism, 319, 340 parametricity, 359–360 parentheses and abstract syntax, 25, 52 parsing, 53 partial evaluation, 109 partial function, 16 partial order, 17 partially abstract types, 406 Pascal, 11 pattern matching, 130–131 PCF, 143 Pebble, 465 Penn translation, 204 Perl, 6 permutation, 18 permutation lemma, 106 permutation rule for record subtyping, 184 performance issues, 201–202 pi-calculus, 51 Pict, 200, 356, 409 Pizza, 195 pointer, 154, see references arithmetic, 159 pointwise subtyping of type operators, 468 polarity, 473 PolyJ, 195 polymorphic functions for lists, 345–347 identity function, 342 recursion, 338 update, 482–485 polymorphism, 331 ad hoc, 340 data abstraction, 368–377 existential, see existential types existential types, 363–379 exponential behavior of ML-style, 334 F-bounded, 393, 408 higher-order, 449–466 impredicativity and predicativity, 360–361 intensional, 340 ML-style, 331–336 parametric, 339–361 parametricity, 359–360 predicative, 360 prenex, 359 rank-2, 359 safety problems with references, 335–336 stratified, 360 subtype, see subtyping universal, see universal types varieties of, 340–341 polytype, 359 portability, types and, 7 positive subtyping, 489 Postscript, 6 power types, 445, 472 precedence of operators, 53 predecessor for Church numerals, 62 predicate, 15 predicative polymorphism, 360–361 prenex polymorphism, 359 preorder, 17 preservation of a predicate by a relation, 16 preservation of shapes under type reduction, 456 preservation of types during evaluation, 95–98, 107, 168, 173, 189, 261, 353, 404, 457 preservation of typing under type substitution, 318 principal type, 317, 329–330 types theorem, 329 typing, 337 unifier, 327 principal solution, 329 principle of safe substitution, 182 product type, 126–127 programming languages Abel, 409 Algol-60, 11 Algol-68, 11 Amber, 311 C, 6, 45 C#, 7 C++, 6, 226 Cecil, 226, 340 Clean, 338 CLOS, 226, 340 CLU, 11, 408 Dylan, 226 Featherweight Java, 247–264 Forsythe, 11, 199 Fortran, 8, 11 Funnel, 409 FX, 11 GJ, 195, 248, 409 Haskell, 6, 45 Java, 6, 8–10, 45, 119, 137, 154, 174, 177, 178, 193, 195, 196, 198–199, 226, 232, 247–264, 341, 444 KEA, 226 Mercury, 338 ML, 6, 8, 9, 11, 174, 177, see also OCaml, Standard ML Modula-3, 7 NextGen, 196 Objective Caml, see OCaml OCaml, xvii, 7, 208, 231, 489 Pascal, 11 Pebble, 465 Perl, 6 Pict, 200, 356, 409 Pizza, 195 PolyJ, 195 Postscript, 6 Quest, 11, 409 Scheme, 2, 6, 8, 45 Simula, 11, 207 Smalltalk, 226 Standard ML, xvii, 7, 45 Titanium, 8 XML, 9, 207, 313 progress theorem, 38, 95–98, 105, 169, 173, 190, 262, 353, 405, 458 projection (from pairs, tuples, records), 126–131 promotion, 418 proof, defined, 20 proof-carrying code, 9 proof theory, 2 proper types, 442 propositions as types, 109 pure λ→, 102 pure lambda-calculus, 51 pure language features, 153 pure type systems, xiv, 2, 444, 466 purefsub implementation, 417–436 * * * * * * Index Q qualified types, 338 quantification, see polymorphism Quest, 11, 409 * * * * * * Index R ramified theory of types, 2 range of a relation, 16 rank-2 polymorphism, 359 raw type, 248 rcdsub implementation, 181–224 reachableF, 294 recon implementation, 317–338 reconbase implementation, 330 reconstruction, see type reconstruction record kinds, 445 records, 129–131 Cardelli-Mitchell calculus, 207 Church encoding, 396–400 concatenation, 207 row variables, 208, 337 recursion, 65–66, 142–145 fixed-point combinator, 65 polymorphic, 338 recursive types, 253, 267–280 Amadio-Cardelli algorithm, 309–311 and subtyping, 279 equi-recursive vs. iso-recursive, 275 history, 279–280 in ML, 277–278 in nominal systems, 253 metatheory, 281–313 μ notation, 299–304 subtyping, 281–290, 298–313 type reconstruction, 313, 338 recursive values from recursive types, 273 redex, 56 reduce function, 63 reducibility candidates, 150 reduction vs. evaluation (terminology), 34 references, 153–170 allocation, 154 and subtyping, 199–200 assignment, 154 dereferencing, 154 subtyping, 198 type safety problems, 158 type safety problems with polymorphism, 335–336 refinement types, 207 reflection, 196, 252 and casting, 196 reflexive closure, 17 reflexive relation, 16 reflexivity of subtyping, 182 region inference, 8 regular trees, 298–299 relation, 15 logical, see logical relations removenames, 78 representation independence, 371 representation of numbers by Church numerals, 67 representation type (of an object), 230 restorenames, 78 row kinds, 445 row variables, 11, 208, 337, 489 rule computation, 35, 72 congruence, 35, 72 naming conventions, 565 schema, 27 rule, inference, 27 rule schema, 27 rules B-IFFALSE, 43 B-IFTRUE, 43 B-ISZEROSUCC, 43 B-ISZEROZERO, 43 B-PREDSUCC, 43 B-PREDZERO, 43 B-SUCC, 43 B-VALUE, 43 CT-ABS, 322, 542 CT-ABSINF, 330 CT-APP, 322, 542 CT-FALSE, 322 CT-FIX, 543 CT-IF, 322 CT-ISZERO, 322 CT-LETPOLY, 332 CT-PRED, 322 CT-PROJ, 545 CT-SUCC, 322 CT-TRUE, 322 CT-VAR, 322, 542 CT-ZERO, 322 E-ABS, 502 E-APP1, 72, 103, 160, 166, 186, 343, 392, 446, 450, 470, 502, 503 E-APP2, 72, 103, 160, 166, 186, 343, 392, 446, 450, 470, 502 E-APPABS, 72, 81, 103, 160, 166, 186, 342, 343, 392, 446, 450, 470, 502, 503 E-APPERR1, 172 E-APPERR2, 172 E-APPRAISE1, 175 E-APPRAISE2, 175 E-ASCRIBE, 122, 194 E-ASCRIBE1, 122 E-ASCRIBEEAGER, 123 E-ASSIGN, 161, 166 E-ASSIGN1, 161, 166 E-ASSIGN2, 161, 166 E-CASE, 132, 136 E-CASEINL, 132, 135 E-CASEINR, 132, 135 E-CASEVARIANT, 136 E-CAST, 258 E-CASTNEW, 258 E-CONS1, 147 E-CONS2, 147 E-DEREF, 161, 166 E-DEREFLOC, 161, 166 E-DOWNCAST, 195 E-FIELD, 258 E-FIX, 144 E-FIXBETA, 144 E-FLD, 276 E-FUNNY1, 40 E-FUNNY2, 40 E-GC, 514 E-HEAD, 147 E-HEADCONS, 147 E-IF, 34 E-IF-WRONG, 42 E-IFFALSE, 34 E-IFTRUE, 34 E-INL, 132, 135 E-INR, 132, 135 E-INVK-ARG, 258 E-INVK-RECV, 258 E-INVKNEW, 258 E-ISNIL, 147 E-ISNILCONS, 147 E-ISNILNIL, 147 E-ISZERO, 41 E-ISZERO-WRONG, 42 E-ISZEROSUCC, 41 E-ISZEROZERO, 41 E-LET, 124, 131, 335 E-LETV, 124, 131, 332 E-NEW-ARG, 258 E-PACK, 366, 452 E-PAIR1, 126 E-PAIR2, 126 E-PAIRBETA1, 126 E-PAIRBETA2, 126 E-PRED, 41 E-PRED-WRONG, 42 E-PREDSUCC, 41, 48 E-PREDZERO, 41 E-PROJ, 128, 129, 187 E-PROJ1, 126 E-PROJ2, 126 E-PROJNEW, 258 E-PROJRCD, 129, 187, 201, 484 E-PROJTUPLE, 128 E-RAISE, 175 E-RAISERAISE, 175 E-RCD, 129, 187, 484 E-REF, 162, 166 E-REFV, 162, 166 E-SEQ, 120 E-SEQNEXT, 120 E-SUCC, 41 E-SUCC-WRONG, 42 E-TAIL, 147 E-TAILCONS, 147 E-TAPP, 343, 392, 450, 470 E-TAPPTABS, 342, 343, 385, 392, 450, 470 E-TRY, 174, 175 E-TRYERROR, 174 E-TRYRAISE, 175 E-TRYV, 174, 175 E-TUPLE, 128 E-TYPETEST1, 195 E-TYPETEST2, 195 E-UNFLD, 276 E-UNFLDFLD, 276 E-UNPACK, 366 E-UNPACKPACK, 366, 367, 452 E-UPDATEV, 484 E-VARIANT, 136 E-WILDCARD, 507 K-ABS, 446, 450, 470 K-ALL, 450, 470 K-APP, 446, 450, 470 K-ARROW, 446, 450, 470 K-SOME, 452 K-TOP, 470 K-TVAR, 446, 450, 470 M-RCD, 131 M-VAR, 131 P-RCD, 509 P-RCD', 509 P-VAR, 509 Q-ABS, 446, 451, 471 Q-ALL, 451, 471 Q-APP, 446, 451, 471 Q-APPABS, 441, 446, 451, 471 Q-ARROW, 446, 451, 471 Q-REFL, 446, 451, 471 Q-SOME, 452 Q-SYMM, 446, 451, 471 Q-TRANS, 446, 451, 471 QR-ABS, 454 QR-ALL, 454 QR-APP, 454 QR-APPABS, 454 QR-ARROW, 454 QR-REFL, 454 S-ABS, 468, 471 S-ALL, 392, 394, 395, 427, 471 S-AMBER, 311 S-APP, 468, 471 S-ARRAY, 198 S-ARRAYJAVA, 198 S-ARROW, 184, 186, 211, 392, 471 S-ASSUMPTION, 311 S-BOT, 192 S-EQ, 468, 471 S-INTER1, 206 S-INTER2, 206 S-INTER3, 206 S-INTER4, 206 S-LIST, 197 S-PRODDEPTH, 187 S-PRODWIDTH, 187 S-RCD, 211 S-RCDDEPTH, 183, 187, 484 S-RCDPERM, 184, 187 S-RCDVARIANCE, 484 S-RCDWIDTH, 183, 187, 484 S-REF, 198 S-REFL, 182, 186, 211, 392 S-REFSINK, 199 S-REFSOURCE, 199 S-SINK, 199 S-SOME, 406, 476, 556 S-SOURCE, 199 S-TOP, 185, 186, 211, 392, 471 S-TRANS, 183, 186, 209, 211, 392, 471 S-TVAR, 392, 394, 471 S-VARIANTDEPTH, 197 S-VARIANTPERM, 197 S-VARIANTWIDTH, 197 SA-ALL, 422, 424 SA-ARROW, 212, 422, 424 SA-BOT, 220 SA-RCD, 212 SA-REFL-TVAR, 422, 424 SA-TOP, 212, 422, 424 SA-TRANS-TVAR, 422, 424 T-ABS, 101, 103, 167, 186, 343, 392, 447, 451, 471 T-APP, 102, 103, 167, 181, 186, 343, 392, 447, 451, 471 T-ASCRIBE, 122, 194 T-ASSIGN, 159, 165, 167, 199 T-CASE, 132, 136 T-CAST, 530 T-CONS, 147 T-DCAST, 259 T-DEREF, 159, 165, 167, 199 T-DOWNCAST, 194 T-EQ, 441, 447, 451 T-ERROR, 172 T-EXN, 175 T-FALSE, 93 T-FIELD, 259 T-FIX, 144 T-FLD, 276 T-HEAD, 147 T-IF, 93, 102, 218 T-INL, 132, 135 T-INR, 132, 135 T-INVK, 259 T-ISNIL, 147 T-ISZERO, 93 T-LET, 124, 332, 509 T-LETPOLY, 332, 333 T-LOC, 164, 167 T-NEW, 259 T-NIL, 147 T-PACK, 365, 366, 406, 452 T-PAIR, 126 T-PRED, 93 T-PROJ, 128, 129, 187, 484 T-PROJ1, 126 T-PROJ2, 126 T-RCD, 129, 187, 484 T-REF, 159, 165, 167 T-SCAST, 259 T-SEQ, 120 T-SUB, 182, 186, 209, 392, 471 T-SUCC, 93 T-TABS, 342, 343, 392, 395, 451, 471 T-TAIL, 147 T-TAPP, 342, 343, 392, 395, 451, 471 T-TRUE, 93 T-TRY, 174, 175 T-TUPLE, 128 T-TYPETEST, 195 T-UCAST, 259 T-UNFLD, 276 T-UNIT, 119, 167 T-UNPACK, 366, 406, 435, 452 T-UPDATE, 484 T-VAR, 101, 103, 167, 186, 259, 343, 392, 447, 451, 471 T-VARIANT, 136, 197 T-WILDCARD, 507 T-ZERO, 93 TA-ABS, 217, 419 TA-APP, 217, 419 TA-APPBOT, 220 TA-IF, 220, 526 TA-PROJ, 217 TA-PROJBOT, 220 TA-RCD, 217 TA-TABS, 419 TA-TAPP, 419 TA-UNPACK, 436 TA-VAR, 217, 419 XA-OTHER, 418 XA-PROMOTE, 418 run-time code generation, 109 run-time error, 42 trapped vs. untrapped, 7 run-time monitoring, 1 * * * * * * Index S safety, 3, 6-8, 95-98 problems with references, 158 problems with references and polymorphism, 335-336 satisfaction of a constraint set by a substitution, 321 saturated sets, 150 Scheme, 2, 6, 8, 45 units, 368 scope, 55 scoping of type variables, 393-394 second-order lambda-calculus, 341, 461 security, type systems and, 9 self, 227, 234-244, 486-488 semantics alternative styles, 32-34 axiomatic, 33 denotational, 33 operational, 32 semi-unification, 338 semistructured databases, 207 sequences, basic notations, 18 sequencing notation, 119-121 and references, 155 sets, basic operations on, 15 sharing, 445, 465 shifting (of nameless terms), 78-80 ML implementation, 85-87 side effects, 153 simple theory of types, 2 simple types, 100 simplebool implementation, 113-116 simply typed lambda-calculus, 2, 11, 99-111 extensions, 117-146 ML implementation, 113-116 pure, 102 with type operators, 445 Simula, 11, 207 single-field variant, 138-140 singleton kinds, 441, 445, 465 size of a term, 29 small-step operational semantics, 32, 42 Smalltalk, 226 soundness, see safety soundness and completeness, 212 of algorithmic subtyping, 423 of constraint typing, 325 Source and Sink constructors, 199 spurious subsumption, 253 Standard ML, xvii, 7, 45 statement, 36 static distance, 76 static vs. dynamic typing, 2 store, 153 store typing, 162-165 stratified polymorphism, 360 streams, 270-271 strict vs. non-strict evaluation, 57 String type, 117 strong binary operations, 376 strong normalization, 152, 353 structural operational semantics, 32, 34 structural unfolding, 489 structural vs. nominal type systems, 251-254 stuck term, 41 stupid cast, 259-260 subclass, 227, 232 subexpressions of μ-types, 304-309 subject expansion, 98, 108 subject reduction, see preservation subscripting conventions, 566 subset semantics of subtyping, 182, 201-202 substitution, 69-72, 75-81, 83-88 capture-avoiding, 70 ML implementation, 85-87 type-, 317 substitution lemma, 106, 168, 189, 453 substitution on types, 342 ML implementation, 382 subsumption, 181-182 postponement of, 214 subtraction of Church numerals, 62 subtype polymorphism, see subtyping subtyping, 181-224, see also bounded quantification Top and Bot types, 191-193 algorithm, 209-213, 417-436 algorithmic, in nominal systems, 253 and ascription, 193-196 and base types, 200 and channel types, 200 and objects, 227 and references, 199-200 and type reconstruction, 338, 355 and variant types, 196-197 arrays, 198-199 coercion semantics, 200-206 depth, 183 higher-order, 11, 467-473 intersection types, 206-207 iso-recursive types, 311-312 joins and meets in System F<:, 432-435 lists, 197 ML implementation, 221-224 objects, 229-230 positive, 489 power types, 472 record permutation, 184 recursive types, 279, 281-290, 298-313 references, 198 reflexivity, 182 subset semantics, 182, 201-202 subtype relation, 182-187 transitivity, 183 type operators, 467-473 undecidability of System F<:, 427-431 union types, 206-207 vs. other forms of polymorphism, 341 width, 183 sum types, 132-135 super, 234 supertype, 182 support, 290 surface syntax, 53 syllabi for courses, xvii symmetric relation, 16 syntactic control of interference, 170 syntactic sugar, 121 syntax, 26-29, 52-55, 69 ML implementation, 46-47, 383-385 syntax-directedness, 209 System F, 11, 339-361 fragments, 358-359 history, 341 ML implementation, 381-387 System Fω, 449-466 and higher-order logic, 109 fragments, 461 System , 467-473 System F<:, 389-409 kernel and full variants, 391 System λω, 445-447 * * * * * * Index T T, see terms tag, type-, 2 tag-free garbage collection, 341 tagged representation of atomic values, 201 tagging creating new types by, 133 tail recursion, 296 TAL, 11 Tarski-Knaster fixed point theorem, 283 termination measure, 39 terminology, reduction vs. evaluation, 34 terms, 24, 26 and expressions (terminology), 24 closed, 55 depth, 29 induction on, 29–32 inductive definition of (nameless form), 77 ML implementation, 46, 83–85 nameless form, see de Bruijn indices size, 29 stuck, 41 theorem proving, types in, 9, 464 this, see self thunk, 239 TinkerType, xx Titanium, 8 Top type, 185, 191–193 top-down subexpressions of a recursive type, 304 Top[K], 468 total function, 16 total order, 17 transitive closure, 17, 289 transitive relation, 16 transitivity and coinduction, 288–290 transitivity of subtyping, 183 translucent types, 11 trapped vs. untrapped errors, 7 tree, 538 abstract syntax, 25 derivation, 36 regular, 298–299 type, 285 treeof, 300 tuples, 126–129 two-counter machines, 430 tyarith implementation, 91–98 typability, 93, 109–110, 354–357 type abstraction, 342 type annotations, 3, 10, 111 type application, 342 type classes, 337, 338 type constructors, see type operators type destructors, 489 type environment, 101 type equivalence, 447, 453–456 type erasure, 110, 354 type errors, 3 finding, 545 type exposure, 417–418 type inference, see type reconstruction type names, 251 type operators, 100, 439–447 bounded, 473 co- and contravariant, 473 definition equivalence, 441 in nominal systems, 254 quantification over, 449–466 subtyping, 467–473 type reconstruction, 317–338, 354–357 colored local type inference, 355 greedy, 355 history, 336–338 local type inference, 355 recursive types, 313, 338 subtyping, 338, 355 type safety, see safety type scheme, 359 type substitution, 317 ML implementation, 382 type systems and efficiency, 8 and portability, 7 and security, 9 and theorem provers, 9, 464 applications, 8–9 as formal methods, 1 category theory and, 12 defined, 1–4 history, 10 in mathematics and logic, 2 language design and, 9–10 role in computer science, 1–4 type tags, 2, 196, 252 type theory, see type systems constructive, 2 type variables, 319–320 type-assignment systems, 101 type-directed partial evaluation, 152 type-erasure semantics, 357 type-passing semantics, 357 typecase, 341 typed arithmetic expressions, 91–98 typed assembly language, 11 typed intermediate languages, 11 typed lambda-calculi, 2 types, 92 typing context, 101 typing derivations, 94 desugaring of, 125 semantics defined on, 111, 200–206 typing relation, 92–95, 100–103 algorithm, 213–218 ML implementation, 113–116 properties, 104–108 * * * * * * Index U undecidability of full type reconstruction for System F, 354 of partial type reconstruction for System F, 354 of subtyping for System F<:, 427–431 undefinedness vs. failure, 16 unification, 321, 326–329 union types, 142, 206–207 disjoint, 142 uniqueness of normal forms, 39 uniqueness of types, 94, 104, 511 and annotations, 135, 141 and sums, 134–135 Unit type, 118–119 unit value, 118–119 units (in Scheme), 368 universal domain, 273 universal set, 282 universal types, 339–361 unsafe declarations, 7 untyped implementation, 83–88 untyped arithmetic expressions, 23–44 untyped lambda-calculus, 11, 51–73 representation using recursive types, 273–275 up-cast, see casting update, polymorphic, 482–485 * * * * * * Index V value, 34, 57 numeric, 40 value restriction, 336, 358 variable capture, 70 variables bound, 55, 69-72 free, 55 variant types, 132-142 and subtyping, 196-197 extensible, 177 single-field, 138-140 vs. datatypes, 140-142 * * * * * * Index W weak binary operations, 375 weak head reduction, 460 weak pointers, 515 weak type variable, 336 weakening lemma, 106 web resources, xx well-formed context, 459 well-founded order, 18 set, 18 well-typed term, 93 width subtyping, 183 wildcard bindings, 119-121 witness type, 364 wrong, 42, 73 * * * * * * Index X XML, 9, 207, 313 * * * * * * Index Y Y combinator, 65 Year 2000 problem, 9 * * * * * * Index Z Z combinator, 65 * * * * * * List of Figures Preface Figure P-1: Chapter Dependencies Figure P-2: Sample Syllabus for an Advanced Graduate Course Chapter 1: Introduction Figure 1-1: Capsule History of Types in Computer Science and Logic Chapter 3: Untyped Arithmetic Expressions Figure 3-1: Booleans (B) Figure 3-2: Arithmetic Expressions (NB) Chapter 5: The Untyped Lambda-Calculus Figure 5-1: The Predecessor Function's "Inner Loop" Figure 5-2: Evaluation of factorial c3 Figure 5-3: Untyped Lambda-Calculus (λ) Chapter 8: Typed Arithmetic Expressions Figure 8-1: Typing Rules for Booleans (B) Figure 8-2: Typing Rules for Numbers (NB) Chapter 9: Simply Typed Lambda-Calculus Figure 9-1: Pure Simply Typed Lambda-Calculus (λ→) Chapter 11: Simple Extensions Figure 11-1: Uninterpreted Base Types Figure 11-2: Unit Type Figure 11-3: Ascription Figure 11-4: Let Binding Figure 11-5: Pairs Figure 11-6: Tuples Figure 11-7: Records Figure 11-8: (Untyped) Record Patterns Figure 11-9: Sums Figure 11-10: Sums (With Unique Typing) Figure 11-11: Variants Figure 11-12: General Recursion Figure 11-13: Lists Chapter 13: References Figure 13-1: References Chapter 14: Exceptions Figure 14-1: Errors Figure 14-2: Error Handling Figure 14-3: Exceptions Carrying Values Chapter 15: Subtyping Figure 15-1: Simply Typed Lambda-Calculus with Subtyping (λ<:) Figure 15-2: Records (Same as Figure 11-7) Figure 15-3: Records and Subtyping Figure 15-4: Bottom Type Figure 15-5: Variants and Subtyping Chapter 16: Metatheory of Subtyping Figure 16-1: Subtype Relation with Records (Compact Version) Figure 16-2: Algorithmic Subtyping Figure 16-3: Algorithmic Typing Chapter 19: Case Study: Featherweight Java Figure 19-1: Featherweight Java (Syntax and Subtyping) Figure 19-2: Featherweight Java (Auxiliary Definitions) Figure 19-3: Featherweight Java (Evaluation) Figure 19-4: Featherweight Java (Typing) Chapter 20: Recursive Types Figure 20-1: Iso-Recursive Types (λμ) Chapter 21: Metatheory of Recursive Types Figure 21-1: Sample Tree Types.

., 461 factorial, 52 fail, 16 failure vs. undefinedness, 16 families (of terms, types), 462 Featherweight Java, 247–264 fields, see instance variables; records finalizers, 515 finding type errors, 545 finite tree type, 285 finite-state generating function, 294 first-class polymorphism, 340 fixed point, 142–145 combinator, 65 of a generating function, 282 theorem (Tarski-Knaster), 283 typing, using recursive types, 273 FJ, see Featherweight Java flattened data structures, 341 Float type, 117 fold function, 63 fomsub implementation, 467–473 formal methods, lightweight, 1 Forsythe, 11, 199 Fortran, 8, 11 fragments of System F, 358–359 fragments of System Fω, 461 free variable, 55, 69 fresh variable, 120 full abstraction, 143 full beta-reduction, 56 full F<:, 391 fullequirec implementation, 267–280 fullerror implementation, 171–178 fullfomsub implementation, 389–409, 467–473 fullfsub implementation, 389–409, 417–436 fullfsubref implementation, 411–416 fullisorec implementation, 275–278 fullomega implementation, 439–466 fullpoly implementation, 339–379 fullrecon implementation, 317–338 fullref implementation, 153–170, 225–245 fullsimple implementation, 99–111, 117–146 fullsub implementation, 181–208 fulluntyped implementation, 51–73 fullupdate implementation, 475–489 <fun>, 118 function types, 99–100 functional languages, mostly, 153 functions, 16 higher-order, 58 multi-argument, 58 on types, see type operators Funnel, 409 FX, 11 * * * * * * Index G garbage collection, 45, 158–165, 514–515 tag free, 341 general recursion, 142–145 generating function, 282 generating set, 290 generation lemma, see inversion lemma generators, classes as, 229 generics, 341 gfp algorithm, 292, 295–298 GJ, 195, 248, 409 grammar, 24 graph reduction, 57 greatest fixed point of a generating function, 283 greatest lower bound, see joins and meets greedy type inference, 355 * * * * * * Index H hash consing, 222 Haskell, 6, 45 heap, 153 hidden representation type, 364 higher-order bounded quantifiers, 468 higher-order functions, 58 higher-order polymorphism, 449–466 history of type systems, 10 hungry functions, 270 hybrid object models, 377 * * * * * * Index I identity, object, 245 identity function, 55 imperative objects, see objects, imperative implementations allsome, 381–387 arith, 23–49 bot, 220 equirec, 281–313 fomsub, 467–473 fullequirec, 267–280 fullerror, 171–178 fullfomsub, 389–409, 467–473 fullfsub, 389–409, 417–436 fullfsubref, 411–416 fullisorec, 275–278 fullomega, 439–466 fullpoly, 339–379 fullrecon, 317–338 fullref, 153–170, 225–245 fullsimple, 99–111, 117–146 fullsub, 181–208 fulluntyped, 51–73 fullupdate, 475–489 joinexercise, 223 joinsub, 218–220 purefsub, 417–436 rcdsub, 181–224 recon, 317–338 reconbase, 330 simplebool, 113–116 tyarith, 91–98 untyped, 83–88 implicit type annotations, 330–331 implicitly typed languages, 101 impredicative polymorphism, 340, 360–361 impure language features, 153 induction, 19 lexicographic, 19 logical relations proof technique, 150 mathematical foundations, 282–284 on derivations, 37 on natural numbers, 19 on terms, 29–32 inductive definitions, 23–29 inference, see type reconstruction inference rules, 26 mathematical foundations, 283 infinite types, 284–286 inheritance, 227 overrated, 245 injection into a sum type, 133 instance of an inference rule, 36 instance variables, 228, 230, 233–234 instanceof, 341 instantiation of a polymorphic function, 317–320, 342 intensional polymorphism, 340 interface, 226 interface types, 479 interfaces (in Java), 261 interference, syntactic control of, 170 intermediate language, 161 intermediate languages, typed, 11 internal language, 53, 120 internet, see web intersection types, 11, 206–207, 359, 489 and bounded quantification, 400, 409 and normal forms, 206 introduction rule, 108 invariant, 33 inversion lemma subtyping, 188 typing, 94, 104, 188, 457 iso-recursive types, 275, 280 subtyping, 311–312 * * * * * * Index J Java, 6, 8–10, 45, 119, 137, 154, 174, 177, 178, 193, 195, 196, 198–199, 226, 232, 247–264, 341, 444 exception handling in, 174 parametric polymorphism, 195 reflection, 196 JINI, 9 joinexercise implementation, 223 joins and meets, 17 algorithms for calculating, 218–220 in System F<:, 432–435 joinsub implementation, 218–220 judgment, 36 * * * * * * Index K KEA, 226 kernel F<:, 391 kinding, 439–447, 459 kinds dependent, 445 power, 445 row, 445 singleton, 445 Knaster-Tarski fixed point theorem, 283 * * * * * * Index L λ-calculus, see lambda-calculus λNB, 63-66 λ→, see simply typed lambda-calculus λω, see System λω λ<:, see simply typed lambda-calculus with subtyping label, 129 lambda cube, 465 lambda-& calculus, 226, 340 lambda-calculi, typed, 2 lambda-calculus, 51, 52 enriched, 63-68 simply typed, see simply typed lambda-calculus untyped, see untyped lambda-calculus lambda-term, 53 language definition, defined, 7 language design and type systems, 9-10 language features, pure, 153 late binding, see objects, open recursion latent type system, 2 lazy evaluation, 57 least fixed point of a generating function, 283 least upper bound, see joins and meets left-associativity of application, 54 let bindings, 124-125 let-polymorphism, 331-336, 340 exponential behavior, 334 levels, de Bruijn, 81 lexical analysis, 53 lexicographic induction, 19 lexicographic order, 19 LF, 11, 465 lfp algorithm, 294 lightweight formal methods, 1 linear logic and type systems, 11, 109 linking, 367 lists, 146 Church encoding, 350-353, 500 defined using recursive types, 267-270 polymorphic functions for, 345-347 subtyping, 197 local type inference, 355 location, 159 logic and type systems, 108 origins, 11 type systems in, 2 logical framework, 465 logical relations, 149 * * * * * * Index M μ, see least fixed point μ notation for recursive types, 299–304 marshaling, 252, 341 Martin-Löf type theory, see constructive type theory match function, 131 matching, pattern-, 130–131 matching relation on object types, 480 mathematics, formalization of, 11 meaning of terms, 32–34 meet, see joins and meets membership checking for (co-)inductively defined sets, 290–298 Mercury, 338 message, 226 meta-mathematics, 24 metalanguage, 24 metatheory, 24 metavariables, 24 naming conventions, 565 method, 226, 228 invocation, 226 multi-, see multi-method override, 233, 264 Milner-Mycroft Calculus, 338 minimal types, 218, 418–420 minimal typing theorem, 419 mini-ML, 337 ML, 6, 8, 9, 11, 174, 177 exception handling in, 174 history, 336–338 module system, 379 parametric datatypes, 445 polymorphism, 331–336 ML implementations evaluation, 87 simply typed lambda-calculus, 113–116 subtyping, 221–224 System F, 381–387 untyped arithmetic expressions, 45–49 untyped lambda-calculus, 83–88 ML-style polymorphism, 340 modal logics, 109 model checking, 1, 284 Modula-3, 7 modularity, 3 module systems, 364, 379, 465 monads, 153 monitoring, run-time, 1 monotone function, 282 monotype, 359 most general unifier, 327 mostly functional languages, 153 multi-argument functions, 58 multi-method, 226, 340 multiple inheritance, 489 multiple representations (of object types), 226 multi-step evaluation, 39 mutually recursive functions, 144 types, 253 v, see greatest fixed point nameless form, see de Bruijn indices naming context, 77 naming conventions for metavariables and rules, 565–566 narrowing lemmas, 401, 425 National Science Foundation, xx natural deduction, 26 natural semantics, 32, 34, 43 natural-number induction, 19 nested induction, 19 NextGen, 196 nominal type systems, 251–254, 312 normal forms, 38 and intersection types, 206 uniqueness of, 39 normal order, 56 normalization, 149–152 by evaluation, 152 strong, 152 normalization theorem, 39, 152, 353 numeric values, 40 NuPRL, 11 * * * * * * Index O object calculus, 11, 51, 184, 248, 251 object language, 24 Objective Caml see OCaml, xvii objects, 228, 368 as recursive records, 272 bounded quantification and, 411–416 encodings vs. primitive objects, 262–263 existential, 372–377, 475–489 hybrid object models, 377 identity, 245 imperative, 157, 225–245, 411–416 interface types, 479 Java-style, 247–264 matching relation on object types, 480 object-oriented programming, defined, 225–227 open recursion, 227, 235–244 purely functional, 372–377, 475–489 vs. abstract data types, 374–377 OCaml, xvii, 7, 45, 208, 231, 489 OCaml implementations, see ML implementations occur check, 327, 338 omega, 65 open recursion, see objects, open recursion operational semantics, 32, see also evaluation big-step, 43 small-step, 42 operator associativity, 53 operator precedence, 53 Option type, 137–138 order, well-founded, 18 ordered sets, basic definitions, 16–18 ordinary induction, 19 overloading, 340 finitary, 206 overriding of method definitions, 233 * * * * * * Index P P(S) powerset of S, 15 package, existential, 364 pairs, 126–127 Church encodings, see Church encodings, pairs parallel reduction, 454 parametric abbreviation, 439 data type, 142, 444 polymorphism, 319, 340 parametricity, 359–360 parentheses and abstract syntax, 25, 52 parsing, 53 partial evaluation, 109 partial function, 16 partial order, 17 partially abstract types, 406 Pascal, 11 pattern matching, 130–131 PCF, 143 Pebble, 465 Penn translation, 204 Perl, 6 permutation, 18 permutation lemma, 106 permutation rule for record subtyping, 184 performance issues, 201–202 pi-calculus, 51 Pict, 200, 356, 409 Pizza, 195 pointer, 154, see references arithmetic, 159 pointwise subtyping of type operators, 468 polarity, 473 PolyJ, 195 polymorphic functions for lists, 345–347 identity function, 342 recursion, 338 update, 482–485 polymorphism, 331 ad hoc, 340 data abstraction, 368–377 existential, see existential types existential types, 363–379 exponential behavior of ML-style, 334 F-bounded, 393, 408 higher-order, 449–466 impredicativity and predicativity, 360–361 intensional, 340 ML-style, 331–336 parametric, 339–361 parametricity, 359–360 predicative, 360 prenex, 359 rank-2, 359 safety problems with references, 335–336 stratified, 360 subtype, see subtyping universal, see universal types varieties of, 340–341 polytype, 359 portability, types and, 7 positive subtyping, 489 Postscript, 6 power types, 445, 472 precedence of operators, 53 predecessor for Church numerals, 62 predicate, 15 predicative polymorphism, 360–361 prenex polymorphism, 359 preorder, 17 preservation of a predicate by a relation, 16 preservation of shapes under type reduction, 456 preservation of types during evaluation, 95–98, 107, 168, 173, 189, 261, 353, 404, 457 preservation of typing under type substitution, 318 principal type, 317, 329–330 types theorem, 329 typing, 337 unifier, 327 principal solution, 329 principle of safe substitution, 182 product type, 126–127 programming languages Abel, 409 Algol-60, 11 Algol-68, 11 Amber, 311 C, 6, 45 C#, 7 C++, 6, 226 Cecil, 226, 340 Clean, 338 CLOS, 226, 340 CLU, 11, 408 Dylan, 226 Featherweight Java, 247–264 Forsythe, 11, 199 Fortran, 8, 11 Funnel, 409 FX, 11 GJ, 195, 248, 409 Haskell, 6, 45 Java, 6, 8–10, 45, 119, 137, 154, 174, 177, 178, 193, 195, 196, 198–199, 226, 232, 247–264, 341, 444 KEA, 226 Mercury, 338 ML, 6, 8, 9, 11, 174, 177, see also OCaml, Standard ML Modula-3, 7 NextGen, 196 Objective Caml, see OCaml OCaml, xvii, 7, 208, 231, 489 Pascal, 11 Pebble, 465 Perl, 6 Pict, 200, 356, 409 Pizza, 195 PolyJ, 195 Postscript, 6 Quest, 11, 409 Scheme, 2, 6, 8, 45 Simula, 11, 207 Smalltalk, 226 Standard ML, xvii, 7, 45 Titanium, 8 XML, 9, 207, 313 progress theorem, 38, 95–98, 105, 169, 173, 190, 262, 353, 405, 458 projection (from pairs, tuples, records), 126–131 promotion, 418 proof, defined, 20 proof-carrying code, 9 proof theory, 2 proper types, 442 propositions as types, 109 pure λ→, 102 pure lambda-calculus, 51 pure language features, 153 pure type systems, xiv, 2, 444, 466 purefsub implementation, 417–436 * * * * * * Index Q qualified types, 338 quantification, see polymorphism Quest, 11, 409 * * * * * * Index R ramified theory of types, 2 range of a relation, 16 rank-2 polymorphism, 359 raw type, 248 rcdsub implementation, 181–224 reachableF, 294 recon implementation, 317–338 reconbase implementation, 330 reconstruction, see type reconstruction record kinds, 445 records, 129–131 Cardelli-Mitchell calculus, 207 Church encoding, 396–400 concatenation, 207 row variables, 208, 337 recursion, 65–66, 142–145 fixed-point combinator, 65 polymorphic, 338 recursive types, 253, 267–280 Amadio-Cardelli algorithm, 309–311 and subtyping, 279 equi-recursive vs. iso-recursive, 275 history, 279–280 in ML, 277–278 in nominal systems, 253 metatheory, 281–313 μ notation, 299–304 subtyping, 281–290, 298–313 type reconstruction, 313, 338 recursive values from recursive types, 273 redex, 56 reduce function, 63 reducibility candidates, 150 reduction vs. evaluation (terminology), 34 references, 153–170 allocation, 154 and subtyping, 199–200 assignment, 154 dereferencing, 154 subtyping, 198 type safety problems, 158 type safety problems with polymorphism, 335–336 refinement types, 207 reflection, 196, 252 and casting, 196 reflexive closure, 17 reflexive relation, 16 reflexivity of subtyping, 182 region inference, 8 regular trees, 298–299 relation, 15 logical, see logical relations removenames, 78 representation independence, 371 representation of numbers by Church numerals, 67 representation type (of an object), 230 restorenames, 78 row kinds, 445 row variables, 11, 208, 337, 489 rule computation, 35, 72 congruence, 35, 72 naming conventions, 565 schema, 27 rule, inference, 27 rule schema, 27 rules B-IFFALSE, 43 B-IFTRUE, 43 B-ISZEROSUCC, 43 B-ISZEROZERO, 43 B-PREDSUCC, 43 B-PREDZERO, 43 B-SUCC, 43 B-VALUE, 43 CT-ABS, 322, 542 CT-ABSINF, 330 CT-APP, 322, 542 CT-FALSE, 322 CT-FIX, 543 CT-IF, 322 CT-ISZERO, 322 CT-LETPOLY, 332 CT-PRED, 322 CT-PROJ, 545 CT-SUCC, 322 CT-TRUE, 322 CT-VAR, 322, 542 CT-ZERO, 322 E-ABS, 502 E-APP1, 72, 103, 160, 166, 186, 343, 392, 446, 450, 470, 502, 503 E-APP2, 72, 103, 160, 166, 186, 343, 392, 446, 450, 470, 502 E-APPABS, 72, 81, 103, 160, 166, 186, 342, 343, 392, 446, 450, 470, 502, 503 E-APPERR1, 172 E-APPERR2, 172 E-APPRAISE1, 175 E-APPRAISE2, 175 E-ASCRIBE, 122, 194 E-ASCRIBE1, 122 E-ASCRIBEEAGER, 123 E-ASSIGN, 161, 166 E-ASSIGN1, 161, 166 E-ASSIGN2, 161, 166 E-CASE, 132, 136 E-CASEINL, 132, 135 E-CASEINR, 132, 135 E-CASEVARIANT, 136 E-CAST, 258 E-CASTNEW, 258 E-CONS1, 147 E-CONS2, 147 E-DEREF, 161, 166 E-DEREFLOC, 161, 166 E-DOWNCAST, 195 E-FIELD, 258 E-FIX, 144 E-FIXBETA, 144 E-FLD, 276 E-FUNNY1, 40 E-FUNNY2, 40 E-GC, 514 E-HEAD, 147 E-HEADCONS, 147 E-IF, 34 E-IF-WRONG, 42 E-IFFALSE, 34 E-IFTRUE, 34 E-INL, 132, 135 E-INR, 132, 135 E-INVK-ARG, 258 E-INVK-RECV, 258 E-INVKNEW, 258 E-ISNIL, 147 E-ISNILCONS, 147 E-ISNILNIL, 147 E-ISZERO, 41 E-ISZERO-WRONG, 42 E-ISZEROSUCC, 41 E-ISZEROZERO, 41 E-LET, 124, 131, 335 E-LETV, 124, 131, 332 E-NEW-ARG, 258 E-PACK, 366, 452 E-PAIR1, 126 E-PAIR2, 126 E-PAIRBETA1, 126 E-PAIRBETA2, 126 E-PRED, 41 E-PRED-WRONG, 42 E-PREDSUCC, 41, 48 E-PREDZERO, 41 E-PROJ, 128, 129, 187 E-PROJ1, 126 E-PROJ2, 126 E-PROJNEW, 258 E-PROJRCD, 129, 187, 201, 484 E-PROJTUPLE, 128 E-RAISE, 175 E-RAISERAISE, 175 E-RCD, 129, 187, 484 E-REF, 162, 166 E-REFV, 162, 166 E-SEQ, 120 E-SEQNEXT, 120 E-SUCC, 41 E-SUCC-WRONG, 42 E-TAIL, 147 E-TAILCONS, 147 E-TAPP, 343, 392, 450, 470 E-TAPPTABS, 342, 343, 385, 392, 450, 470 E-TRY, 174, 175 E-TRYERROR, 174 E-TRYRAISE, 175 E-TRYV, 174, 175 E-TUPLE, 128 E-TYPETEST1, 195 E-TYPETEST2, 195 E-UNFLD, 276 E-UNFLDFLD, 276 E-UNPACK, 366 E-UNPACKPACK, 366, 367, 452 E-UPDATEV, 484 E-VARIANT, 136 E-WILDCARD, 507 K-ABS, 446, 450, 470 K-ALL, 450, 470 K-APP, 446, 450, 470 K-ARROW, 446, 450, 470 K-SOME, 452 K-TOP, 470 K-TVAR, 446, 450, 470 M-RCD, 131 M-VAR, 131 P-RCD, 509 P-RCD', 509 P-VAR, 509 Q-ABS, 446, 451, 471 Q-ALL, 451, 471 Q-APP, 446, 451, 471 Q-APPABS, 441, 446, 451, 471 Q-ARROW, 446, 451, 471 Q-REFL, 446, 451, 471 Q-SOME, 452 Q-SYMM, 446, 451, 471 Q-TRANS, 446, 451, 471 QR-ABS, 454 QR-ALL, 454 QR-APP, 454 QR-APPABS, 454 QR-ARROW, 454 QR-REFL, 454 S-ABS, 468, 471 S-ALL, 392, 394, 395, 427, 471 S-AMBER, 311 S-APP, 468, 471 S-ARRAY, 198 S-ARRAYJAVA, 198 S-ARROW, 184, 186, 211, 392, 471 S-ASSUMPTION, 311 S-BOT, 192 S-EQ, 468, 471 S-INTER1, 206 S-INTER2, 206 S-INTER3, 206 S-INTER4, 206 S-LIST, 197 S-PRODDEPTH, 187 S-PRODWIDTH, 187 S-RCD, 211 S-RCDDEPTH, 183, 187, 484 S-RCDPERM, 184, 187 S-RCDVARIANCE, 484 S-RCDWIDTH, 183, 187, 484 S-REF, 198 S-REFL, 182, 186, 211, 392 S-REFSINK, 199 S-REFSOURCE, 199 S-SINK, 199 S-SOME, 406, 476, 556 S-SOURCE, 199 S-TOP, 185, 186, 211, 392, 471 S-TRANS, 183, 186, 209, 211, 392, 471 S-TVAR, 392, 394, 471 S-VARIANTDEPTH, 197 S-VARIANTPERM, 197 S-VARIANTWIDTH, 197 SA-ALL, 422, 424 SA-ARROW, 212, 422, 424 SA-BOT, 220 SA-RCD, 212 SA-REFL-TVAR, 422, 424 SA-TOP, 212, 422, 424 SA-TRANS-TVAR, 422, 424 T-ABS, 101, 103, 167, 186, 343, 392, 447, 451, 471 T-APP, 102, 103, 167, 181, 186, 343, 392, 447, 451, 471 T-ASCRIBE, 122, 194 T-ASSIGN, 159, 165, 167, 199 T-CASE, 132, 136 T-CAST, 530 T-CONS, 147 T-DCAST, 259 T-DEREF, 159, 165, 167, 199 T-DOWNCAST, 194 T-EQ, 441, 447, 451 T-ERROR, 172 T-EXN, 175 T-FALSE, 93 T-FIELD, 259 T-FIX, 144 T-FLD, 276 T-HEAD, 147 T-IF, 93, 102, 218 T-INL, 132, 135 T-INR, 132, 135 T-INVK, 259 T-ISNIL, 147 T-ISZERO, 93 T-LET, 124, 332, 509 T-LETPOLY, 332, 333 T-LOC, 164, 167 T-NEW, 259 T-NIL, 147 T-PACK, 365, 366, 406, 452 T-PAIR, 126 T-PRED, 93 T-PROJ, 128, 129, 187, 484 T-PROJ1, 126 T-PROJ2, 126 T-RCD, 129, 187, 484 T-REF, 159, 165, 167 T-SCAST, 259 T-SEQ, 120 T-SUB, 182, 186, 209, 392, 471 T-SUCC, 93 T-TABS, 342, 343, 392, 395, 451, 471 T-TAIL, 147 T-TAPP, 342, 343, 392, 395, 451, 471 T-TRUE, 93 T-TRY, 174, 175 T-TUPLE, 128 T-TYPETEST, 195 T-UCAST, 259 T-UNFLD, 276 T-UNIT, 119, 167 T-UNPACK, 366, 406, 435, 452 T-UPDATE, 484 T-VAR, 101, 103, 167, 186, 259, 343, 392, 447, 451, 471 T-VARIANT, 136, 197 T-WILDCARD, 507 T-ZERO, 93 TA-ABS, 217, 419 TA-APP, 217, 419 TA-APPBOT, 220 TA-IF, 220, 526 TA-PROJ, 217 TA-PROJBOT, 220 TA-RCD, 217 TA-TABS, 419 TA-TAPP, 419 TA-UNPACK, 436 TA-VAR, 217, 419 XA-OTHER, 418 XA-PROMOTE, 418 run-time code generation, 109 run-time error, 42 trapped vs. untrapped, 7 run-time monitoring, 1 * * * * * * Index S safety, 3, 6-8, 95-98 problems with references, 158 problems with references and polymorphism, 335-336 satisfaction of a constraint set by a substitution, 321 saturated sets, 150 Scheme, 2, 6, 8, 45 units, 368 scope, 55 scoping of type variables, 393-394 second-order lambda-calculus, 341, 461 security, type systems and, 9 self, 227, 234-244, 486-488 semantics alternative styles, 32-34 axiomatic, 33 denotational, 33 operational, 32 semi-unification, 338 semistructured databases, 207 sequences, basic notations, 18 sequencing notation, 119-121 and references, 155 sets, basic operations on, 15 sharing, 445, 465 shifting (of nameless terms), 78-80 ML implementation, 85-87 side effects, 153 simple theory of types, 2 simple types, 100 simplebool implementation, 113-116 simply typed lambda-calculus, 2, 11, 99-111 extensions, 117-146 ML implementation, 113-116 pure, 102 with type operators, 445 Simula, 11, 207 single-field variant, 138-140 singleton kinds, 441, 445, 465 size of a term, 29 small-step operational semantics, 32, 42 Smalltalk, 226 soundness, see safety soundness and completeness, 212 of algorithmic subtyping, 423 of constraint typing, 325 Source and Sink constructors, 199 spurious subsumption, 253 Standard ML, xvii, 7, 45 statement, 36 static distance, 76 static vs. dynamic typing, 2 store, 153 store typing, 162-165 stratified polymorphism, 360 streams, 270-271 strict vs. non-strict evaluation, 57 String type, 117 strong binary operations, 376 strong normalization, 152, 353 structural operational semantics, 32, 34 structural unfolding, 489 structural vs. nominal type systems, 251-254 stuck term, 41 stupid cast, 259-260 subclass, 227, 232 subexpressions of μ-types, 304-309 subject expansion, 98, 108 subject reduction, see preservation subscripting conventions, 566 subset semantics of subtyping, 182, 201-202 substitution, 69-72, 75-81, 83-88 capture-avoiding, 70 ML implementation, 85-87 type-, 317 substitution lemma, 106, 168, 189, 453 substitution on types, 342 ML implementation, 382 subsumption, 181-182 postponement of, 214 subtraction of Church numerals, 62 subtype polymorphism, see subtyping subtyping, 181-224, see also bounded quantification Top and Bot types, 191-193 algorithm, 209-213, 417-436 algorithmic, in nominal systems, 253 and ascription, 193-196 and base types, 200 and channel types, 200 and objects, 227 and references, 199-200 and type reconstruction, 338, 355 and variant types, 196-197 arrays, 198-199 coercion semantics, 200-206 depth, 183 higher-order, 11, 467-473 intersection types, 206-207 iso-recursive types, 311-312 joins and meets in System F<:, 432-435 lists, 197 ML implementation, 221-224 objects, 229-230 positive, 489 power types, 472 record permutation, 184 recursive types, 279, 281-290, 298-313 references, 198 reflexivity, 182 subset semantics, 182, 201-202 subtype relation, 182-187 transitivity, 183 type operators, 467-473 undecidability of System F<:, 427-431 union types, 206-207 vs. other forms of polymorphism, 341 width, 183 sum types, 132-135 super, 234 supertype, 182 support, 290 surface syntax, 53 syllabi for courses, xvii symmetric relation, 16 syntactic control of interference, 170 syntactic sugar, 121 syntax, 26-29, 52-55, 69 ML implementation, 46-47, 383-385 syntax-directedness, 209 System F, 11, 339-361 fragments, 358-359 history, 341 ML implementation, 381-387 System Fω, 449-466 and higher-order logic, 109 fragments, 461 System , 467-473 System F<:, 389-409 kernel and full variants, 391 System λω, 445-447 * * * * * * Index T T, see terms tag, type-, 2 tag-free garbage collection, 341 tagged representation of atomic values, 201 tagging creating new types by, 133 tail recursion, 296 TAL, 11 Tarski-Knaster fixed point theorem, 283 termination measure, 39 terminology, reduction vs. evaluation, 34 terms, 24, 26 and expressions (terminology), 24 closed, 55 depth, 29 induction on, 29–32 inductive definition of (nameless form), 77 ML implementation, 46, 83–85 nameless form, see de Bruijn indices size, 29 stuck, 41 theorem proving, types in, 9, 464 this, see self thunk, 239 TinkerType, xx Titanium, 8 Top type, 185, 191–193 top-down subexpressions of a recursive type, 304 Top[K], 468 total function, 16 total order, 17 transitive closure, 17, 289 transitive relation, 16 transitivity and coinduction, 288–290 transitivity of subtyping, 183 translucent types, 11 trapped vs. untrapped errors, 7 tree, 538 abstract syntax, 25 derivation, 36 regular, 298–299 type, 285 treeof, 300 tuples, 126–129 two-counter machines, 430 tyarith implementation, 91–98 typability, 93, 109–110, 354–357 type abstraction, 342 type annotations, 3, 10, 111 type application, 342 type classes, 337, 338 type constructors, see type operators type destructors, 489 type environment, 101 type equivalence, 447, 453–456 type erasure, 110, 354 type errors, 3 finding, 545 type exposure, 417–418 type inference, see type reconstruction type names, 251 type operators, 100, 439–447 bounded, 473 co- and contravariant, 473 definition equivalence, 441 in nominal systems, 254 quantification over, 449–466 subtyping, 467–473 type reconstruction, 317–338, 354–357 colored local type inference, 355 greedy, 355 history, 336–338 local type inference, 355 recursive types, 313, 338 subtyping, 338, 355 type safety, see safety type scheme, 359 type substitution, 317 ML implementation, 382 type systems and efficiency, 8 and portability, 7 and security, 9 and theorem provers, 9, 464 applications, 8–9 as formal methods, 1 category theory and, 12 defined, 1–4 history, 10 in mathematics and logic, 2 language design and, 9–10 role in computer science, 1–4 type tags, 2, 196, 252 type theory, see type systems constructive, 2 type variables, 319–320 type-assignment systems, 101 type-directed partial evaluation, 152 type-erasure semantics, 357 type-passing semantics, 357 typecase, 341 typed arithmetic expressions, 91–98 typed assembly language, 11 typed intermediate languages, 11 typed lambda-calculi, 2 types, 92 typing context, 101 typing derivations, 94 desugaring of, 125 semantics defined on, 111, 200–206 typing relation, 92–95, 100–103 algorithm, 213–218 ML implementation, 113–116 properties, 104–108 * * * * * * Index U undecidability of full type reconstruction for System F, 354 of partial type reconstruction for System F, 354 of subtyping for System F<:, 427–431 undefinedness vs. failure, 16 unification, 321, 326–329 union types, 142, 206–207 disjoint, 142 uniqueness of normal forms, 39 uniqueness of types, 94, 104, 511 and annotations, 135, 141 and sums, 134–135 Unit type, 118–119 unit value, 118–119 units (in Scheme), 368 universal domain, 273 universal set, 282 universal types, 339–361 unsafe declarations, 7 untyped implementation, 83–88 untyped arithmetic expressions, 23–44 untyped lambda-calculus, 11, 51–73 representation using recursive types, 273–275 up-cast, see casting update, polymorphic, 482–485 * * * * * * Index V value, 34, 57 numeric, 40 value restriction, 336, 358 variable capture, 70 variables bound, 55, 69-72 free, 55 variant types, 132-142 and subtyping, 196-197 extensible, 177 single-field, 138-140 vs. datatypes, 140-142 * * * * * * Index W weak binary operations, 375 weak head reduction, 460 weak pointers, 515 weak type variable, 336 weakening lemma, 106 web resources, xx well-formed context, 459 well-founded order, 18 set, 18 well-typed term, 93 width subtyping, 183 wildcard bindings, 119-121 witness type, 364 wrong, 42, 73 * * * * * * Index X XML, 9, 207, 313 * * * * * * Index Y Y combinator, 65 Year 2000 problem, 9 * * * * * * Index Z Z combinator, 65 * * * * * * List of Figures Preface Figure P-1: Chapter Dependencies Figure P-2: Sample Syllabus for an Advanced Graduate Course Chapter 1: Introduction Figure 1-1: Capsule History of Types in Computer Science and Logic Chapter 3: Untyped Arithmetic Expressions Figure 3-1: Booleans (B) Figure 3-2: Arithmetic Expressions (NB) Chapter 5: The Untyped Lambda-Calculus Figure 5-1: The Predecessor Function's "Inner Loop" Figure 5-2: Evaluation of factorial c3 Figure 5-3: Untyped Lambda-Calculus (λ) Chapter 8: Typed Arithmetic Expressions Figure 8-1: Typing Rules for Booleans (B) Figure 8-2: Typing Rules for Numbers (NB) Chapter 9: Simply Typed Lambda-Calculus Figure 9-1: Pure Simply Typed Lambda-Calculus (λ→) Chapter 11: Simple Extensions Figure 11-1: Uninterpreted Base Types Figure 11-2: Unit Type Figure 11-3: Ascription Figure 11-4: Let Binding Figure 11-5: Pairs Figure 11-6: Tuples Figure 11-7: Records Figure 11-8: (Untyped) Record Patterns Figure 11-9: Sums Figure 11-10: Sums (With Unique Typing) Figure 11-11: Variants Figure 11-12: General Recursion Figure 11-13: Lists Chapter 13: References Figure 13-1: References Chapter 14: Exceptions Figure 14-1: Errors Figure 14-2: Error Handling Figure 14-3: Exceptions Carrying Values Chapter 15: Subtyping Figure 15-1: Simply Typed Lambda-Calculus with Subtyping (λ<:) Figure 15-2: Records (Same as Figure 11-7) Figure 15-3: Records and Subtyping Figure 15-4: Bottom Type Figure 15-5: Variants and Subtyping Chapter 16: Metatheory of Subtyping Figure 16-1: Subtype Relation with Records (Compact Version) Figure 16-2: Algorithmic Subtyping Figure 16-3: Algorithmic Typing Chapter 19: Case Study: Featherweight Java Figure 19-1: Featherweight Java (Syntax and Subtyping) Figure 19-2: Featherweight Java (Auxiliary Definitions) Figure 19-3: Featherweight Java (Evaluation) Figure 19-4: Featherweight Java (Typing) Chapter 20: Recursive Types Figure 20-1: Iso-Recursive Types (λμ) Chapter 21: Metatheory of Recursive Types Figure 21-1: Sample Tree Types.


pages: 138 words: 40,787

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

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

In the next chapter we will take a look at the investment attractiveness of the M2M space. 27 Luke Dempsey, “Monty Python’s Flying Circus: Complete and Annotated … All the Bits,” Python Productions, Ltd., 159. (Source: http://en.wikipedia.org/wiki/Kilimanjaro_Expedition.) 28 Donald A. Norman, The Design of Everyday Things (New York: Basic Books, 1988). Chapter 7 WHERE TO INVEST All creative people want to do the unexpected. ~ Hedy Lamarr According to Paul Graham of Y Combinator, the best way to get start-up ideas is not to think of start-up ideas. Instead, one should focus on problems one has firsthand experience with.29 This is great advice for both start-up and corporate entrepreneurs, but what about investors? How would investors know where to put their money if they are not familiar with the space and specific problems? Sometimes investors can take their cues from entrepreneurs, but they will also need to develop their own opinions.


pages: 412 words: 128,042

Extreme Economies: Survival, Failure, Future – Lessons From the World’s Limits by Richard Davies

agricultural Revolution, air freight, Anton Chekhov, artificial general intelligence, autonomous vehicles, barriers to entry, big-box store, cashless society, clean water, complexity theory, deindustrialization, eurozone crisis, failed state, financial innovation, illegal immigration, income inequality, informal economy, James Hargreaves, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, large denomination, Livingstone, I presume, Malacca Straits, mandatory minimum, manufacturing employment, means of production, megacity, meta analysis, meta-analysis, new economy, off grid, oil shale / tar sands, pension reform, profit motive, randomized controlled trial, school choice, school vouchers, Scramble for Africa, side project, Silicon Valley, Simon Kuznets, Skype, spinning jenny, The Chicago School, the payments system, trade route, Travis Kalanick, uranium enrichment, urban planning, wealth creators, white picket fence, working-age population, Y Combinator, young professional

What made him a winner was his big idea – a new way to grow plants – and the fact that Estonia is a country that loves innovators: Ajujaht is one of many inventors’ contests and translates roughly as ‘brain hunt’. The victorious Mr Lepp received a prize of €30,000, and significant media coverage. Seven years later his company, Click and Grow, has 35 staff and recently raised $9 million in funding, including investments from Y Combinator, an influential Silicon Valley investment fund. Mr Lepp shows me the first part of his invention. It looks like a massive pack of paracetamol designed for giants – flat tinfoil on one side with a series of large plastic bubbles on the other. Rather than holding a pill, each of the capsules contains a clump of soil, shaped like the root ball that comes out when you empty a dried plant pot. A user takes this ‘smart soil’ and slots it into the second part of his new system, a sleek machine in which plants – in this case, basil – will grow.

Abercrombie, Sir Patrick 203 Aceh 2–39, 10, 331, 332, 333, 334, 335 ‘building back better’ 24–5, 29–31, 42 civil war 32–3 education 13, 31 financial system 20–22 history 17–18 Memorandum of Understanding (MOU) 32, 33 tsunami 2–3, 6, 12–14, 15, 16, 18–19, 23 ageing populations 6, 212–49, 331 agglomeration see industrial agglomeration AI see artificial intelligence Akita, Japan 212–49 ageing population/ low birth rate 7, 213–25, 227–49, 331 suicides 225–6 Allende, Salvador 296–8, 301 amoral familism 196, 202 Anglo-Dutch wars 25 Angola: Kongo people 83 Angola (Louisiana penitentiary) 5, 76–104, 331, 335, Angolite, The 80 Argentina 110, 144, 291, 303 Arkwright, Richard 267 Arrol, Sir William 191 artificial intelligence (AI) 245, 268–9, 270, 284, 286, 287, 378 automation: and job losses 253 see also technology Azraq refugee camp 57–67, 71, 72, 144, 334, 340, 348–9 Bajo Chiquito, Panama 106, 108–9, 1112, 133, 136, 139 Banda Aceh 13, 16, 18, 20, 26–7, 34–5 Bandal, Kinshasa 144, 162 Bandudu, Congo 164, 165 banks 97, 99 in Aceh 19, 21, 22 Chilean 296, 297, 302 in Kinshasa/ Congo 151, 158 online 99, 278 Panamanian 131 Barbour, Mary 203, 366 barter economy, prison 89–90 Bevan, Aneurin 201 birth rates, falling 215–16, 226–7, 233, 247 Blockbuster Video 97 blood circulation (William Harvey) 3–4 borders: and conservation of common resources 126–7 Borland, Francis: History of Darien 107 Brazil: ageing population 213, 214 Brazzaville, Congo 174–5 Bruce, Robert 203 Brumberg, Richard 218 buccaneers and Darien 112–14 business start-up rates 54 Calabria, negative social integration 195–6 Calton, Glasgow 179, 190, 191, 192 Cambridge University 26, 182 Cameron, Verney Lovett 141, 143, 149 cannabinoids, synthetic 93–4, 95–6, 352 cartels, Chilean 321–3 Casement, Roger: on Congo Free State 150 cash vs. barter 89–90 Castro, Fidel 298 Castro, Sergio de 301 centenarians, Japanese 215, 216 Chesterton, George Laval 77 Chicago Boys 294–5, 296, 300, 301, 314, 325 El Ladrillo (economic plan) 301–5, 315–16, 317, 323–4, 325–6 protests against 305, 317 Chile Allende period 296–8, 301 education 294, 295, 302, 304–5, 310, 311–12, 312, 313–17, 318, 324, 326, 327 national income 291–3 nationalization 296–7 Pinochet dictatorship 298, 300–1, 305, 322, 383 tsunami 15 see also Chicago Boys ‘Chilean Winter’ 317–18 Clyde shipyards 178–9, 181, 183–4, 185 Cold Bath Fields prison 91 Coleridge, Samuel Taylor 113 Colombian peace accord (2016) 111, 134 common resources and conservation 124–5 depletion paradox 122–39 overgrazed land 122–3 and self-regulation 125, 126–8 Confucian ethics 220 Congo, Democratic Republic of ‘Crisis’ 151–8 GDP per capita 153, 173 independence (1960) 151 unemployment 142–3 see also Kinshasa; Mobutu, Sese Seko; Zaire consumerism as slavery 319 copper mining 143, 151, 156, 296, 323–4 corruption 133 in Kinshasa 143, 145–6, 148, 159–61, 168, 333, 361 credit: and poverty 308–10 Crompton, Samuel 267 crop rotation 279 Cunard Line 185 currencies cacao beans 91 cigarette papers 91 cigarettes/tobacco 92, 95 coffee 77, 96, 100 commodities 90–91 ‘dot’ payment system 97–100 dual-currency system 166–7 ‘EMAK’ (edible mackerel) 92 postage stamps 92 in prisons 91–101 ramen noodles 92 roles played (Jevons) 90 on Rossel Island 91 salt 91 Yoruk people 91 Cut Nyak Dhien 35 Dael, Syria: refugees 42–4 Dagahaley settlement, Kenya 45, 46 Dampier, William 113, 114 Daraa: and Syrian civil war 44 Darien Gap 6, 106, 107–39, 332, 333, 334 borders and common resource conservation 126–7 buccaneers’ accounts 112–14 eco-tourism 132 environmental damage 6, 120–21, 129–31 ethnic rivalry 126–8 externalities 131, 138, 183, 186, 332 illegal immigrants 132–7 market failure 109–10, 122–3, 129, 138 Scottish disaster 114–15, 133, 137–8 Darien National Park 126, 132 deaths lonely 225, 226, 236, 237, 248 premature (‘Glasgow effect’) 192–3 suicide 194, 213, 224, 225–6, 236, 248, 366 see also life expectancy digital divide 254, 281, 377 digital ID 277, 279 digital infrastructure, Estonian 259 drugs in Angola (prison) 81, 82, 88, 93–4, 95–6, 97, 99, 100, 101, 352 in Chile 306, 310, 322 in Darien 110, 111, 128, 134, 135 in Scotland 191–2, 193 in Tallinn 206 Dunlop, John Boyd 150 Durkheim, Emile: La Suicide 194, 196, 206 e-democracy (Estonia) 284, 287 e-Residency (Estonia) 277–8, 279, 283, 287, 379 education in Aceh 13, 31 in Chile/Santiago 295, 302, 304–5, 310, 311–12, 312, 313–17, 326, 327 in Italy 195 in Japan 220, 223, 229 in Louisiana 81 in Zaatari camp 67, 71, 349 see also universities Embera tribe 108, 109, 111, 119, 127, 128, 129, 133, 136, 137, 138–9, 357 entrepreneurs 331 in Aceh 19, 22, 23, 24, 27, 30, 39 in Akita, Japan 236–7, 238 in Angola (prison) 89, 102–3 Chilean 295, 296 in Darien 5, 114 Estonian 270, 275, 278–9, 281 in Glasgow 181, 182 in Kinshasa 162, 171 in Zaatari camp 43, 46, 54, 55–8, 62–3, 71 environmental damage see Darien Gap Estonia 256–7, 259 Ajujaht competition 252, 260, 275, 276, 278, 283–3 companies 281 economic revival 275–87 e-Government services 254–5 as ESSR 257–9, 272–4 labour shortage 280 Russia border 271–2 Russian population 272–4, 281–3 technology 252–6, 259–87 externalities 183, 206 Darien Gap 131, 138, 183, 186, 332 Glasgow 183–4, 186, 189–90, 333 and markets 332 extractive economy 122–39 Fairfield Heritage 349 Fairfield shipyard 178, 186, 189, 200, 206 FARC guerrillas 111, 132, 133, 134–5, 137, 355, 357 Ffrench-Davis, Ricardo 302 Foljambe, Joseph 265–6 Force Publique 150 foreign aid 23, 27–9, 54, 170 foreign exchange traders 166–7 Franklin, Isaac 83 free markets 128, 131, 174, 296, 300–3, 316, 320, 326–7, 331–2, 356 Frente Amplio coalition 318, 384 Friedman, Milton 289, 295, 303, 319, 326, 383, 384 GAM (Gerakan Aceh Merdeka) freedom fighters 18, 32, 346 Gbadolite 159 GDP see Gross Domestic Product Gécamines 155–6 Geddes, Reay: report 189–90 gender roles, Japanese 223–4, 232 Germany 187, 195, 222, 227, 247, 249, 292, 302, 360 Glasgow 6–7, 176, 177–207, 333 culture 180 drug users 191–2 externalities 183–4, 186, 189–90, 333 population density 197 shipbuilding 178–9, 181, 184–6, 187–8, 189, 190–91, 199–200, 206–7, 333, 334 tenement homes and social capital 196, 197–202, 205, 335 unemployment 190 see also Calton; Gorbals; Govan and below Glasgow City Council (GCC) 202–4 Glasgow City Improvement Trust 202–3, 366 ‘Glasgow effect’, isolation 205–6 Glassford, John 181 Glenlee 179 gold in Aceh 17, 20–22, 37, 332, 334 in the Congo 143 in Darien 109, 113, 117, 120, 356 Golden Island 114–15 Good Neighbor Policy (USA) 294, 383 Goodyear, Charles 150 Gorbals, Glasgow 176, 191, 192, 204, 205, 367 Govan, Glasgow 176, 178, 184, 186, 192, 197–8, 201–3, 206, 207 Great Depression 26 Gross Domestic Product (GDP) 26 Aceh 27, 37–8 Chile 316 Congo 153, 173 Estonia 259 Hagadera refugee camp, Kenya 45 Han, Byung-Chul 319 Harberger, Arnold ‘Alito’ 295, 305, 326 Hargreaves, James 266, 267 Harris, Walter 115 Harvey, William 1, 3–4, 5, 6, 329, 330, 336 Heinla, Ahti 263–4, 268, 282, 284, 285 Hinohara, Shigeaki 211 housing 90 Aceh 12–13, 16, 19, 24, 26, 27, 28, 29–30, 26, 38, 39 Akita, Japan 223, 228, 229, 230, 232, 233, 236–7, 239, 248 Azraq and Zaatari camps 44, 45, 48, 54, 55, 59, 61, 63, 70, 71 Chile 296, 297, 300, 302, 204, 306, 207, 308, 326 Darien 118, 139 Glasgow 197–9, 202–6 Kinshasa 142 Louisiana 95, 102 human capital 38–9, 168, 305, 335, 346–7 human rights abuses 300–1 Hyakumoto, Natsue 235 ID cards, personal data 260–61 Ifo refugee camp, Kenya 45 incarceration rates, USA 76–7, 78 industrial agglomeration 182–6, 200, 206, 330–31, 333, 365 inequality 6, 18, 254, 331, 337 in Chile 6, 291–2, 292, 293, 297, 298, 304, 308, 311, 317, 318, 324–7 intergenerational (Japan) 221–3, 238, 248 informal economies 122–5, 214–15, 331, 333–4, 336 Aceh 21–2, 24, 30, 31, 34, 37 Akita 233, 248 Chile 297, 306–7, 310, 323 Darien 122, 128, 129 Estonia 258 and Glasgow 204, 206, 334 Italy 196, 336 Kinshasa 142, 146, 148, 163–6, 167–8, 170, 173–5, 334 in prisons 77, 78–9, 86–7, 91, 93, 96, 99, 100–1, 102 in Zaatari camp 43, 45, 47, 57, 61, 64, 71, 72, 86 Innophys 245 innovation in Chile 315 and currency 97, 99–100 and economies 43, 79, 80, 87, 100, 122, 162, 333, 334 in Estonia 252, 256–7, 258–87 in Glasgow 179, 180, 182, 185, 188, 192, 201 technological 97–8, 183, 187, 252, 256–7, 258–87 intergenerational inequality (Japan) 221–3, 238, 248 International African Association (IAA) 149 International Cooperation Administration (ICA) 294 International Monetary Fund 303 inventions 265–6 in Estonia 252–3, 260, 265, 275–6, 282–3 isolation, ‘Glasgow effect’ 205–6 Italy 195–6, 201, 202, 335–6, 366 ageing population 213, 220, 222, 243, 331 population decline 227, 230, 233, 249 ivory trade 149 Jackie Chan Village 35–7, 39 Jackson, Giorgio 317–20 Jadue, Daniel 322, 332 Japan ageing population 6, 213–25, 227–49, 331 common forest conservation 124, 125 education 220, 223, 229 shipyards innovation/ competition 187–8, 189 tsunamis 15 Japan Football Association (JFA) 212–13 Jendi, Mohammed 54–5, 56, 71 Jevons, William Stanley 75, 89–90, 99, 352 Kabila family 154, 161, 162, 173 Kajiwara, Kenji 238 Kakuma refugee camp, Kenya 45 Kalanick, Travis 57 Kasa-Vubu, Joseph 151 Katanga 143, 151 Katumba refugee camp, Tanzania 45 Kenya: refugee camps 45, 46 Keynes, John Maynard 5, 7 Kinshasa 6, 140, 141–75, corruption 143, 145–6, 148, 159–61, 168, 333, 361 informal economy 142, 146, 148, 163, 166, 167–8, 170, 173, 334 natural wealth 143 pillages 157–8 police 159–61 roads as informal markets 163–6 tax system 145–6, 147–8, 16 Kirkaldy, David 4, 5, 6, 330 Kuala Lumpur 293 Kuna tribe 126, 340 Laar, Mart 258 labour pools, industrial agglomeration 183, 184–5, 200 Ladrillo, El see Chicago Boys Lagos 293 Lampuuk 2–3, 6, 13, 14, 22–3, 26, 32, 33, 35, 37, 345 Lancashire 266, 267 Las Condes 288, 290, 293, 304, 306, 307, 308, 309, 321, 322, 325 Lasnamäe, Tallinn 272, 281 Le Corbusier: Cité radieuse 203 Leontief, Wassily: Machines and Man 251, 377 Leopold II, King of the Belgians 149–50 Lhokgna 10, 12–13, 14, 26, 27–8, 29, 31, 33, 34, 35, 38, 345 life-cycle hypothesis 218–19, 248 life expectancy Glasgow 179, 190, 191–3 Japan 215 Russia 273–4 Swaziland 179 Lima 293 Liverpool 89, 177, 192, 193, 205–6 Livingstone, David 148–9 Lloyd, William Forster 122–3 lonely deaths 225, 226, 236, 237, 248 Louisiana 74, 76, 81 Department of Public Safety and Corrections 83 Prison Enterprises 83–4, 85, 351 State Penitentiary see Angola Lüders, Rolf 293, 295, 304, 305, 325 Lumumba, Patrice 151 machine learning 268–70 Makarova, Marianna 272, 274 Malacca Strait 10, 17,. 18, 35, 39 Malahayati, Admiral Laksamana 34–5 Maluku steel mill, Kinshasa 155, 156–7 Manchester 192, 193, 205–6 market economies Chile 297, 302, 305, 317 prison 78, 79, 87, 89, 100, 101, 103 markets 71, 122, 332–3, 336 Aceh 20–22, 36–7, 38, 144, 331 Azraq camp 62–4, 71, 144 Chile 295, 296, 297, 298–9, 304, 309, 319, 320–23 Darien 122, 126–7, 128, 129, 131, 138 free 128, 131, 174, 296, 300–3, 316, 320, 326–7, 331–2, 356 Glasgow 181, 190 Japan 232, 233, 248, 249 Kinshasa 143, 145, 146–7, 162, 163–6, 167, 173, 174 Zaatari supermarkets 48–53, 64, 348 Marshall, Alfred 182–3, 184, 185, 186, 187, 189, 190, 194, 200, 206, 329, 330, 365 Maslow, Abraham 41, 65–7, 68, 71, 72, 286, 319, 326, 349 Meikle, Andrew 266 Melvin, Jean 197, 198, 199, 200, 201, 202, 205 ménage lending system 201, 334 Menger, Carl 90, 99, 352 Michelin brothers 150 military coup, Pinochet’s 298 Mill, John Stuart 11, 38, 335, 346–7 minimum wages 94, 267, 296, 307–8, 310 Mishamo refugee camp, Tanzania 45 Mississippi River 74, 76 Mobutu, Sese Seko (formerly Joseph-Désiré) 141, 151–2, 154–9, 161, 162, 166, 173, 297, 333, 360–61 Modigliani, Franco 218–19, 372 Mojo (synthetic cannabis) 92–4, 95–6, 97 monopolies, facilitated 319 Montgomery, Hugh 3–4 Moore, Gordon 269 Morgan, Henry 112–13 Narva, Estonia 250, 271, 272, 274, 283, 287, 378 National Health Service 201–2 nationalization 187, 296, 301–2, 383 natural disasters: and economic growth 24–5 New Caledonia 114, 356 New Orleans 74, 76, 79, 93, 101, 102, 103 Ninagawa, Yukio 234–5 norms, economics and 196, 200, 201, 323, 334, 336 obesity 81, 309, 326, 351 opportunism: and depletion of common resources 126–38 Organization for Economic Cooperation and Development (OECD) 291, 316, 326, 377 Ostrom, Elinor 123–5, 137 Pan-American Highway 106, 110, 111, 115–17, 118–19, 121, 139, 355 Panama 106, 108-9, 110, 111, 113, 117, 118, 121, 130, 131, 356–7 see also Darien Gap; FARC guerrillas Panian refugee camp, Pakistan 45 Paro robot 243–5 Paterson, William: A Proposal to Plant a Colony in Darien 107 pawn shops 200, 334, 367 Penguins’ Revolution 317 pepper: global boom 17, 345 Pepper robot 246–7 personal data 260–61 Petty, William 25–6, 38n, 346 Piñera, Sebastián 309 Pinochet, General Augustine 298, 300–1, 305, 322, 383 pirate economies see informal economies population 122, 125, 330, 347 Aceh 14, 16, 18 Chile/Santiago 291, 324 China 76 Congo/Kinshasa 143, 150 Dael 42 Darien Gap 126, 128 Estonia 255, 256, 265, 272 Glasgow 179, 197 Greece 238 Japan 226–7, 229 Portugal 238 refugee camps 44, 45, 49, 57, 348 Sweden 238 US prisons 76–7 see also ageing populations Portugal 213, 227, 230, 233, 238, 243, 249, 291, 331, 351, 360 poverty Chile 291, 293, 300, 301, 303–4, 305, 208, 311. 15. 326 Congo/Kinshasa 143, 144, 160, 169, 11, 173 Glasgow 192 Italy 195 Japan 220, 226, 233, 248 Louisiana 81, 351 prices 147–8, 302 Pride of York 207 Prisoner’s Dilemma 174 privatization 169, 173, 301–2, 315, 326, 361 Pugnido refugee camp, Ethiopia 45 Putnam, Robert 195–6, 201, 202, 335–6, 366 Rahmatullah mosque, Aceh 14 rainforest destruction 121, 128–31 Rand, Rait 260, 275–6, 283, 284 Red Road Estate, Glasgow 203 refugee camps 45, 46, 55, 173 see also Azraq; Zaatari Reid, Alexander 180 resilience 3, 5, 6, 13, 16, 22, 31, 34, 35–9, 78, 103, 109, 122, 123, 146, 170, 248, 293, 325, 333–7, 384 Revolutionary Armed Forces of Colombia see FARC Rideau, Wilbert 79–80, 82, 87–8, 100, 351 Rio Chucunaque 117, 119 robotics/ robots and care 243–4, 245–7, 248 delivery robots 262–4 for egalitarian economies 284–5 human overseers/ minders 280 ‘last-mile problem’ 264 machine learning 268–70 Sony AIBO robotic dogs 245 trams, driverless 264 Roosevelt, Franklin D. 294, 356 rosewood trees 120, 128, 138 rubber trade 149–50 Russian-Estonians 272–4, 281–4, 286–7 salarymen, retired 223–4, 228, 248 Samuel, Arthur 269 Santiago 7, 288, 289–327 see also Chile schools/ schooling markets 165, 311–15 Scotland Darien disaster 114–15, 133, 137–8 see also Glasgow self-governance 125–8 shipbuilding 178–9, 181, 184–6, 187–8, 189–91, 199–200 Sikkut, Siim 259, 277, 284 Skype 254, 263, slavery 82–6 smuggling 42, 46–8, 68 social capital 195–6, 199, 200, 202, 323, 325, 335–6, 366 social inequality 142–3, 324–5 Somalia 15 South Korea 213, 214, 220, 227, 233, 247, 319, 373 Spain 115, 137, 213, 222, 227, 243, 331 Spice (synthetic cannabis) 352 Spice Islands 17 Spiers, Alexander 181 Spinning Jenny 267, 269, 274, 378 Sri Lanka 15, 17, 49 Stanley, Henry Morton 148–9 Stanyforth, Disney 266 Starship Technologies 262–4, 269, 280 stateless people 255 store cards, prepaid 97–8 students 81, 168, 218, 221, 223, 236–7, 238, 248, 282, 283, 294–5, 304–5, 311–14, 315–18 suicide 194, 213, 224, 225–6, 236, 248, 366 Sumatra 17-18, see also Aceh supermarkets, Zaatari 48–53, 64, 348 Swing Riots 266, 378 synthetic cannabis see Mojo; Spice Takahashi, Kiyoshi 235, 236 Tallinn 7, 250, 251–87 Russian population 272–4, 281–4, 286–7 start-up paradise 254 Tallinn, Harry 278, 282–3 Tanzania: refugee camps 45 taxation 25, 346 Aceh 32 Chile 295, 302, 307, 315–17, 325 Darien 111, 130 Estonia 256–7, 259, 273, 278, 287 Glasgow 190 Japan 220, 231 Kinshasa 145–6, 147–8, 151, 152, 158, 161–2, 165, 167–8, 169, 173–4 in Zaatari refugee camp 48, 56 Tay Bridge collapse 5 teak trees 116, 130–31, 138, 333, 356, 357 technology and inequality 253–4 innovation 97–8, 183, 187, 256–7, 258–9 spill-overs 183, 189 and unemployment 253, 262, 270, 279, 286, 287, 377, 379 tectonic plates 13–14 tenement buildings, Glaswegian 196, 197–202, 205, 335 Thailand 15, 144, 213 tobacco 77, 85–6, 92, 95, 100, 143, 156, 181, 191, 202, 365 Tomaya, Yoichi 235 Törbel, Switzerland: forest conservation 124 towerblocks 203, 204, 205 trade in prison 97–100 in Zaatari camp 43–57, 67–70 see also markets traditions, economic resilience and 21, 22, 24, 34, 196, 336 trust 148, 150, 174, 196, 199, 201, 206, 248, 261, 295, 321, 323, 325, 335 Tshisekedi, Félix 154 tsunamis 2–3, 12–14, 15, 16, 18–19, 22–3, 25 Tull, Jethrow 266 Turkey 28, 58, 144, 213 Uber 57 Ukegawa, Sachiko 234 underground economies 77–9, 87–101 see also informal economies unemployment 64–5, 142–3, 190, 275 Chile 290, 297, 302, 307, 311 Congo 142, 359 Estonia 270, 273, 275, 279, 283, 379 Glasgow 179, 190, 191 and technology 253, 262, 270, 279, 286, 287, 377, 379 United Kingdom 4, 18, 26, 181, 187, 188, 199, 213, 223, 278, 335 agriculture 265, 267 housing 232 jails 86, 91, 96, 352 National Health Service 201, 203 population 226 and technology 253, 254, 257, 260, 262, 264 see also Glasgow; Scotland United Nations High Commissioner for Refugees (UNHCR) 44, 46, 48, 54, 57, 72, 348 World Food Programme (WFP), and Zaatari 48, 49–50 universities Aceh 13, 33, 34 Akita, Japan 221, 223 Chile 294, 305, 313, 314, 315, 316–17, 318, 324, 326 Congo/Kinshasa 151, 160, 166, 168 Estonia 275, 282, 283 Upper Clyde Shipbuilders (UCS) 189 urbanization: and agglomeration forces 330–31 United States 26, 54, 76, 83, 93, 213, 223, 253, 262, 279, 292, 294, 297–8 prisons 76–7, 78, 81, 91–2, see also Angola population 226 and technology 260, 262, 264, 267, 269, 276 USAID 28, 29 Valdez, Samuel 121, 128–9, 130 Vallejo, Camila 317–18, 384 Van Gogh, Vincent 180 Vatter, Ott 277, 278 Viik, Linnar 257, 258–60, 261–2 Wafer, Lionel 113–14, 134, 355 Waisbluth, Mario 313 Walpole, Sir Spencer: A History of England 177 Walsh, David: History, Politics and Vulnerability … 177 Watanabe, Hiroshi 234 wealth 4–5, 159, 218–19, 324–5, 329, 334–6 nation’s 25, 38n, 346–7 natural 109, 132, 143 workforce 184–5, 264–8, 275, 297 World Bank 303, 305, 346 World Health Organization (WHO) 63, 215 World Trade Organization 303 Wounan tribe 126, 127 X-Road data system 261, 274–5, 279, 283, 377 Y Combinator 252 Yamamoto, Ryo 236–7 Yaviza, Panama 110, 111, 116–20, 127, 132, 135, 138, 144, 356 Yida refuge camp, South Sudan 45 Zaatari Syrian refugee camp 6, 40, 41–73, 86, 89, 100, 163, 173, 308, 331, 332, 334, 335, 348, 349 declining population 57 education 67, 71, 349 informal economy 43, 45, 47, 57, 61, 64, 71, 72, 86 smuggler children 42, 46–8, 68 supermarkets 48–53, 64, 348 trade development 43–57, 67–70, 71, 72 UNHCR cedes control 44–6 Zaire 152, 154, 155–6, 159, 361 Zorrones 324 TRANSWORLD PUBLISHERS 61–63 Uxbridge Road, London W5 5SA penguin.co.uk Transworld is part of the Penguin Random House group of companies whose addresses can be found at global.penguinrandomhouse.com.


pages: 163 words: 46,523

The Kickstarter Handbook: Real-Life Success Stories of Artists, Inventors, and Entrepreneurs by Steinberg, Don

3D printing, crowdsourcing, Kickstarter, Skype, Y Combinator

Here are some of these types of sources: AlphaLab, Pittsburgh, PA (alphalab.org) Bootup Labs, Vancouver, BC (bootuplabs.com) Capital Factory, Austin, TX (capitalfactory.com) DreamIt Ventures, Philadelphia, PA (dreamitventures.com) Good Company Ventures, Philadelphia, PA (goodcompanygroup.org) Junto Partners, Salt Lake City, UT (juntopartners.com) Seed Hatchery, Memphis, TN (seedhatchery.com) TechStars, Boulder, CO (techstars.com) Y-Combinator, Mountain View, CA (ycombinator.com) KICKSTARTER CAMPAIGNS are a lot of work, so you’ll want to make a good plan well in advance of the launch date. This Prelaunch Worksheet asks important questions you’ll need to answer before presenting your project to the world. Some of these answers will need to be input directly into Kickstarter.com. Others are simply useful for planning, organizing, and marketing your campaign.


pages: 199 words: 43,653

Hooked: How to Build Habit-Forming Products by Nir Eyal

Airbnb, AltaVista, Cass Sunstein, choice architecture, cognitive bias, cognitive dissonance, en.wikipedia.org, framing effect, game design, Google Glasses, IKEA effect, Inbox Zero, invention of the telephone, iterative process, Jeff Bezos, Lean Startup, Mahatma Gandhi, Mark Zuckerberg, meta analysis, meta-analysis, Oculus Rift, Paul Buchheit, Paul Graham, Peter Thiel, QWERTY keyboard, Richard Thaler, Silicon Valley, Silicon Valley startup, Snapchat, TaskRabbit, telemarketer, the new new thing, Toyota Production System, Y Combinator

With both Pinterest and Instagram, tiny teams generated huge value—not by cracking hard technical challenges, but by solving common interaction problems. Likewise, the fast ascent of mobile devices, including tablets, has spawned a new revolution in interface changes—and a new generation of start-up products and services designed around mobile user needs and behaviors. To uncover where interfaces are changing, Paul Buchheit, a partner at Y Combinator, encourages entrepreneurs to “live in the future.”10 A profusion of interface changes are just a few years away. Wearable technologies like Google Glass, the Oculus Rift virtual reality goggles, and the Pebble smartwatch promise to change how users interact with the real and digital worlds. By looking forward to anticipate where interfaces will change, the enterprising designer can uncover new ways to form user habits.


pages: 457 words: 128,838

The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey

Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, buy and hold, California gold rush, capital controls, carbon footprint, clean water, collaborative economy, collapse of Lehman Brothers, Columbine, Credit Default Swap, cryptocurrency, David Graeber, disintermediation, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, intangible asset, Internet of things, inventory management, Joi Ito, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, Pearl River Delta, peer-to-peer, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, QR code, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, seigniorage, shareholder value, sharing economy, short selling, Silicon Valley, Silicon Valley startup, Skype, smart contracts, special drawing rights, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, supply-chain management, Ted Nelson, The Great Moderation, the market place, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, Turing complete, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, underbanked, WikiLeaks, Y Combinator, Y2K, zero-sum game, Zimmermann PGP

Plug and Play is the brainchild of Saeed Amidi, a garrulous Iranian immigrant who started the accelerator in 2006 and has turned the successful idea into a global franchise that recruits start-ups worldwide. Plug and Play units are now in Canada, Spain, Singapore, Jordan, Dagestan, Russia, Poland, and Mexico, as well as at four other sites in the United States. A number of these kinds of programs exist around the world and in the Valley: Boost, Hero City, Y Combinator, 500 Startups, all with roughly the same idea. The difference between “incubator” and “accelerator” is somewhat vague, but the main idea behind the latter is to move fast. Billing itself as “Silicon Valley in a box,” Plug and Play brings together start-ups, corporations, venture capital, and universities all in one place and bangs out companies. It’s been a phenomenally successful, frenetic model.

Gox and trust industries Turing Festival 20Mission Twitter Uber U-Haul Ulbricht, Ross Ultimate Frisbee unbanked people Unenumerated Unfair Trade, The (Casey) UnionPay Union Square Partners United Kingdom Utah utilities value: of bitcoins of coins of cryptocurrencies of dollar of gold intrinsic of money van der Laan, Wladimir Vaurum venture capitalists (VCs) Ver, Roger Verisign Verizon Vessenes, Peter VHS Virgin Group VirtEx Visa Vodafone Volabit Volcker, Paul Voltaire Voorhees, Erik voting Wall Street Wall Street Journal Walmart Washington State wealth bitcoin and Wealth of Nations, The (Smith) Web Designs WeChat Wedbush Securities Weill, Sanford Wei Dai Weimar Republic welfare state Wells Fargo Western Union Whelan, Jason Whelan, John WikiLeaks Wikipedia Willard, Rik William III, King Williams, Mark T. Wilson, Cody Wilson, Fred Winklevoss, Cameron and Tyler Wise, Josh Women’s Annex Wood, Gavin work World Bank Wright, Frank Lloyd Wuille, Pieter Xapo XIPH Foundation Xpert Financial XRP Y2K threat Yahoo Yang, Jerry Yap Y Combinator Yellen, Janet Yermack, David YouTube YTCracker Yunus, Muhammad ZeroBlock Zhang, Ng Zimbabwe Zimmerman, Phil Zobro, Jonathan Zoosk Zuckerberg, Mark Zug Also by Michael J. Casey The Unfair Trade Che’s Afterlife ABOUT THE AUTHORS Paul Vigna is a markets reporter for The Wall Street Journal, covering equities and the economy. He writes for the Journal’s MoneyBeat blog, coauthoring the daily “BitBeat” column with Michael Casey, and anchors the daily MoneyBeat show.


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The Facebook Effect by David Kirkpatrick

Andy Kessler, Burning Man, delayed gratification, demand response, don't be evil, global village, happiness index / gross national happiness, Howard Rheingold, Jeff Bezos, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Network effects, Peter Thiel, rolodex, Sand Hill Road, sharing economy, Silicon Valley, Silicon Valley startup, Skype, social graph, social software, social web, Startup school, Steve Ballmer, Steve Jobs, Stewart Brand, the payments system, The Wealth of Nations by Adam Smith, Whole Earth Review, winner-take-all economy, Y Combinator

Fall 2005 Page 149 As the school year resumed in the fall of 2005: Michael Arrington, “85% of College Students Use Facebook,” TechCrunch, September 7, 2005, www.techcrunch.com/2005/09/07/85-of-college-students-use-facebook/ (accessed November 15, 2009). 151 One new group was called “You’re Still in High School … ”: John Cassidy, “Me Media: How Hanging Out On The Internet Became Big Business,” New Yorker, May 15, 2006, http://www.newyorker.com/archive/2006/05/15/060515fa_fact_cassidy (accessed December 11, 2009). 151 At the beginning of the school year, Facebook had nearly doubled: Owen Van Natta, interview with author, May 15, 2007. 152 Ever vigilant about competitors: Angwin, Stealing MySpace, 140, 177. 153 Zuckerberg was dismissive: Ibid., 177. 156 By early 2010 Facebook was hosting: email from Brandee Barker, Facebook public relations, February 24, 2010. 8. The CEO Page 166 “I want to stress the importance of being young”: Mark Coker, “Start-Up Advice For Entrepreneurs, From Y Combinator Startup School,” Venturebeat, March 26, 2007, http://venturebeat.com/2007/03/26/start-up-advice-for-entrepreneurs-from-y-combinator-start-up-school/ (accessed November 28, 2009). 169 But at the end of March, BusinessWeek’s online edition: Steve Rosenbush, “Facebook’s on the Block,” BusinessWeek, March 28, 2006, http://www.businessweek.com/technology/content/mar2006/tc20060327_215976.htm (accessed November 15, 2009). 170 But to Zuckerberg, what was more significant: Ibid. 171 Another imitator, which launched around the same time in China: Baloun, Inside Facebook, 95. 173 He also quoted a sociologist who speculated: Cassidy, “Me Media.” 174 who he had met while: Lacy, 162. 174 After some negotiation, Zuckerberg: Lacy, 162. 176 A week after the program launched: Rob Walker, “A For-Credit Course,” New York Times, September 30, 2007, http://www.nytimes.com/2007/09/30/magazine/30wwInconsumed-t.html (accessed December 27, 2009). 177 As part of the deal the ad giant: email from Brandee Barker, Facebook public relations, December 11, 2009. 9. 2006 Page 184 Peter Thiel, older but very sympathetic: Lacy, 165. 186 Some nights, unable to sleep: David Kushner, “The Baby Billionaires of Silicon Valley,” Rolling Stone, November 16, 2006, http://rollingstone.com/news/story/12286036/the_baby_billionaires_of_silicon_valley (accessed November 28, 2009). 186 “I hope he doesn’t sell it”: Kevin Colleran, interview with the author. 190 Within about three hours the group’s membership: Tracy Samantha Schmidt, “Inside the Backlash Against Facebook,” Time, September 6, 2006, www.time.com/time/nation/article/0,8599,1532225,00.html (accessed December 11, 2009). 190 And there were about five hundred other protest groups: Brandon Moore, “Student users say new Facebook feed borders on stalking,” Arizona Daily Wildcat, September 8, 2006, http://wildcat.arizona.edu/2.2257/student-users-say-new-facebook-feed-borders-on-stalking-1.177273 (accessed December 11, 2009). 190 “Chuck Norris come save us”: Layla Aslani, “Users Rebel Against Facebook Feature,” Michigan Daily, September 7, 2006, http://www.michigandaily.com/content/users-rebel-against-facebook-feature (accessed December 11, 2009). 190 “You shouldn’t be forced to have a Web log”: Moore, “Student Users.” 190 “I’m really creeped out”: Aslani, “Users Rebel.” 191 But Zuckerberg, in New York on a promotional trip: Andrew Kessler, “Weekend Interview with Facebook’s Mark Zuckerberg,” Wall Street Journal, March 24, 2007, http://www.andykessler.com/andy_kessler/2007/03/wsj_weekend_int.html (accessed December 11, 2009). 10.


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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, basic income, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, commoditize, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, drone strike, 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, lifelogging, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta analysis, meta-analysis, Minecraft, move fast and break things, 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 intelligence, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

.* Given that Mark Zuckerberg has said that connectivity is a human right, does requiring patrons to log into Facebook to get free WiFi impinge on their rights, or does it merely place Facebook access on the same level of humanitarianism? All of the world’s information, every opportunity, every fact, every business on earth. Such widely shared self-regard has made it seem embarrassing to claim more modest goals for one’s business. A document sent out to members of Y Combinator, the industry’s most sought-after start-up incubator, instructed would-be founders: “If it doesn’t augment the human condition for a huge number of people in a meaningful way, it’s not worth doing.” As long as we have the informational appetite, more data will always seem axiomatic—why wouldn’t one collect more, compute more? It’s the same absolutism found in the mantra “information wants to be free.”

(Lanier), 328 WiFi, 323–24 Wikipedia, 198 Winnebago Man (documentary), 72 Winogrand, Garry, 48 women and abusive labor practices in Asia, 266n and revenge porn, 210 and shadow work, 271 targeting ads by gender in the physical world, 298–99 tracking feelings of unattractiveness, 304 warning other women about deadbeat men, 191 Wonkblog (Washington Post), 105–7, 123, 124 Wood, Graeme, 213 World Economic Forum (WEF), 281–82, 328–29, 330–31 World Wide Web. See Internet Wu, Tim, 2, 67 Yahoo, 28, 96 Yang, Zoe, 78–80, 81, 82 Y Combinator, 324 YouTube, 13, 15, 70–71, 84, 361 Zakas, Laimonas, 353–54 Zengotita, Thomas de, 120, 346 Zipcar, 236 Zuckerberg, Mark claims for Facebook, 6 on companies over countries, 6 on Facebook’s supply of data, vii on frictionless sharing, 12 on human beings as cells of a single organism, 12, 376n on maintaining two identities, 159 on privacy, 287–88, 292 Shreateh’s post on Zuckerberg’s Facebook page, 354–55 Zuckerberg, Randi, 159 Zuckerberg’s Law, 288 About the Author JACOB SILVERMAN’S work has been published in the New York Times, the Los Angeles Times, Slate, the Atlantic, the New Republic, and many other publications.


pages: 229 words: 61,482

The Gig Economy: The Complete Guide to Getting Better Work, Taking More Time Off, and Financing the Life You Want by Diane Mulcahy

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, Clayton Christensen, cognitive bias, collective bargaining, creative destruction, David Brooks, deliberate practice, diversification, diversified portfolio, fear of failure, financial independence, future of work, gig economy, helicopter parent, Home mortgage interest deduction, housing crisis, job satisfaction, Kickstarter, loss aversion, low skilled workers, Lyft, mass immigration, mental accounting, minimum wage unemployment, mortgage tax deduction, negative equity, passive income, Paul Graham, remote working, risk tolerance, Robert Shiller, Robert Shiller, Silicon Valley, Snapchat, TaskRabbit, Uber and Lyft, uber lyft, universal basic income, wage slave, Y Combinator, Zipcar

We can’t deepen our connections with others and devote significant attention to our important relationships if we’re also checking email or watching the clock because we’re scheduled for something else in 10 minutes. To be our most effective and efficient selves and to create the time to invest in our priorities, we need reasonably sized blocks of time. One way to create that time is to apply the framework of Maker vs. Manager schedules to our calendars. Paul Graham of Y Combinator introduced the concept in his 2009 blog post “Maker’s Schedule, Manager’s Schedule.”7 I’ll summarize the concepts he introduces, but it’s worth reading it in its entirety. The Manager’s Schedule The Manager’s Schedule is the one most familiar to us, as it’s common for traditional employees and management (as the name implies) in corporations. The day is structured around half-hour to one-hour blocks of time, in which meetings and phone calls take place throughout the day.


pages: 270 words: 64,235

Effective Programming: More Than Writing Code by Jeff Atwood

AltaVista, Amazon Web Services, barriers to entry, cloud computing, endowment effect, Firefox, future of work, game design, Google Chrome, gravity well, job satisfaction, Khan Academy, Kickstarter, loss aversion, Marc Andreessen, Mark Zuckerberg, Merlin Mann, Minecraft, Paul Buchheit, Paul Graham, price anchoring, race to the bottom, recommendation engine, science of happiness, Skype, social software, Steve Jobs, web application, Y Combinator, zero-sum game

Heck, it’s a huge win if we read one hundred posts and learn one new valuable thing. If you’re looking for good programming blogs to sharpen your saw (or at least pique your intellectual curiosity), I know of two excellent programming specific link aggregation sites that can help you find them. The first is Hacker News, which I recommend highly. Hacker News is the brainchild of Paul Graham, so it partially reflects his interests in Y Combinator and entrepreneurial stuff like startups. Paul is serious about moderation on the site, so in addition to the typical Digg-style voting, there’s a secret cabal (I like to think of it as The Octagon, “no one will admit they still exist!”) of hand-picked editors who remove flagged posts. More importantly, the conversation on the site about the articles is quite rational, with very little noise and trolling.


pages: 265 words: 69,310

What's Yours Is Mine: Against the Sharing Economy by Tom Slee

4chan, Airbnb, Amazon Mechanical Turk, asset-backed security, barriers to entry, Berlin Wall, big-box store, bitcoin, blockchain, citizen journalism, collaborative consumption, congestion charging, Credit Default Swap, crowdsourcing, data acquisition, David Brooks, don't be evil, gig economy, Hacker Ethic, income inequality, informal economy, invisible hand, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, Khan Academy, Kibera, Kickstarter, license plate recognition, Lyft, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, peer-to-peer, peer-to-peer lending, Peter Thiel, pre–internet, principal–agent problem, profit motive, race to the bottom, Ray Kurzweil, recommendation engine, rent control, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, software is eating the world, South of Market, San Francisco, TaskRabbit, The Nature of the Firm, Thomas L Friedman, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ultimatum game, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Zipcar

They bought some inflatable airbeds and offered accommodations to attendees who would be interested in a cheap place to stay. They were inundated with requests and realized there may be a market for this kind of thing, and so “Airbed and Breakfast” was born. Since then, the story has been one of hard work and growth. Running up the limit on multiple credit cards to finance the very beginnings, they got an early investment from Paul Graham’s Y-Combinator fund. Struggling to get the site to take off, they went out to their biggest city (New York) and got the hosts to have professional photos taken of their rooms to make them more appealing; the bookings increased, and professional photography continues to be the most effective way for a host to attract guests. Other maneuvers included a breakfast-cereal pitch around the Democratic convention in Chicago and a widely criticized email campaign via Craigslist.


pages: 222 words: 70,132

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

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

As Ben Tarnoff, writing in the Guardian noted, one of the reasons Peter Thiel was drawn to Donald Trump’s authoritarian candidacy was that “he would discipline what Thiel calls ‘the unthinking demos’: the democratic public that constrains capitalism.” But for now there are few constraints on Tech capitalism. The monopoly profits of this new era have been very, very good to a few men. The Forbes 400 list, which ranks American wealth, places Bill Gates, Larry Ellison, Larry Page, Jeff Bezos, Sergey Brin, and Mark Zuckerberg in the top ten. The Silicon Valley venture capitalist Paul Graham (CEO of Y Combinator), in a 2016 blog post, was quite open about celebrating income inequality. He wrote, “I’ve become an expert on how to increase economic inequality, and I’ve spent the past decade working hard to do it. Not just by helping the 2500 founders YC has funded. I’ve also written essays encouraging people to increase economic inequality and giving them detailed instructions showing how.” If tech billionaires have achieved political and economic power unseen since the Gilded Age, they have also achieved cultural power.


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, Donald Knuth, Douglas Engelbart, Douglas Engelbart, El Camino Real, fault tolerance, Firefox, Gerard Salton, Gerard Salton, Google bus, Google Chrome, Google Earth, Googley, HyperCard, hypertext link, IBM and the Holocaust, informal economy, information retrieval, Internet Archive, Jeff Bezos, John Markoff, Kevin Kelly, Kickstarter, Mark Zuckerberg, Menlo Park, one-China policy, optical character recognition, PageRank, Paul Buchheit, Potemkin village, prediction markets, recommendation engine, risk tolerance, Rubik’s Cube, Sand Hill Road, Saturday Night Live, search inside the book, second-price auction, selection bias, 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, turn-by-turn navigation, undersea cable, Vannevar Bush, web application, WikiLeaks, Y Combinator

To round out its suite of web applications, Google began developing a cloud-based alternative to Microsoft’s PowerPoint. In early 2007, it heard about an innovative start-up that was working on a web-based presentation program that had some even niftier features than the one Google was developing internally. Wayne Crosby and Robby Walker had begun a company called Zenter. Funded by $15,000 from a start-up incubator called Y Combinator, they set out to create their web-based program in four months. They were working out of a small apartment in Mountain View with almost no furniture: their dining room table was a large Styrofoam box that had once held a case of Lean Cuisine meals that Walker’s father had sent them so they wouldn’t starve. Back in his home state of Arizona, Crosby’s wife was about to give birth to their first child.

., The Organization Man, 162 Wi-Fi networks, 343, 383, 384 Wikipedia, 240, 241 Wilkin, John, 352 Williams, Evan, 374, 376 Williams, Robin, 246–47 Winograd, Terry, 14, 16, 17, 28, 31 wireless communication, 214–16, 384 Wissman, Adam, 103 Wittgenstein, Ludwig, 48 Wojcicki, Anne, 126, 253 Wojcicki, Susan, 128, 235, 356 and advertising, 78, 79, 95, 98, 101, 102, 104, 115, 119, 174, 335 house of, 34, 125–26, 133, 139 Wong, Nicole, 175–76, 178, 309, 338–39, 379–80 Wooki, 240–41 word processing, 201, 202 words, defined by content, 48 word stuffing, 25 World Economic Forum, 283–84 World Wide Web, see Internet; web Wright, Johanna, 58, 59, 68 Writely, 201 Writers Guild of America, 361 Wu, Dandan, 288 Wu, Qing, 119–20 Xerox PARC (Palo Alto Research Center), 37 Xue, Rohnsin, 289 Yahoo: and China, 273, 284, 285, 286 and competition, 98, 99, 220, 332, 380 and eGroups, 30 and email, 168, 172, 180 and Flickr, 239 founding of, 31 funding of, 73 and Google, 44–45, 57, 151 meetings with, 28 and Microsoft, 343–44, 346, 380 and Overture, 98–99 and YouTube, 247, 248 Yang, Jerry, 28, 71, 344 Y Combinator, 203 Yeo, Boon-Lock, 301–2 Yoshka (dog), 36 YouTube, 242–52, 328, 372 and China, 298, 305 and copyrights, 244, 245, 251, 261 formation of, 243 Google acquisition of, 199, 247–52 and Google management, 251, 260–65 and Google Video, 242–47, 249, 263 Insight project, 264 profitability of, 264, 383 and U.S. politics, 317–18 Yuanchao, Li, 306 Zenter, 203 Zenzu Consulting, 195 Zhu, Julie, 303, 312 Zuckerberg, Mark, 369–70, 374, 381, 382


pages: 1,007 words: 181,911

The 4-Hour Chef: The Simple Path to Cooking Like a Pro, Learning Anything, and Living the Good Life by Timothy Ferriss

Airbnb, Atul Gawande, Buckminster Fuller, Burning Man, correlation does not imply causation, crowdsourcing, deliberate practice, en.wikipedia.org, Golden Gate Park, happiness index / gross national happiness, haute cuisine, Hugh Fearnley-Whittingstall, Isaac Newton, Johann Wolfgang von Goethe, Kevin Kelly, Kickstarter, Loma Prieta earthquake, loss aversion, Louis Pasteur, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, microbiome, Parkinson's law, Paul Buchheit, Paul Graham, Pepto Bismol, Ponzi scheme, Ralph Waldo Emerson, Silicon Valley, Skype, spaced repetition, Stephen Hawking, Steve Jobs, the High Line, Y Combinator

CULINARY CRAM SCHOOL—THE BLUEPRINT We’ll work on the most central techniques throughout this book, but if you want to replicate our madness, here’s the blueprint. Find a chef coach to lead the way. CULINARY CRAM SCHOOL—LESSON PLAN TECHNIQUE: BUTCHERY TECHNIQUE: COOKING TECHNIQUE: CUTTING TECHNIQUE: EGG COOKERY TECHNIQUE: GARDE MANGER TECHNIQUE: SAUCE MAKING LONGER-TERM LEARNING SUGGESTIONS Y Combinator, quietly tucked away off highway 101 just miles from Google headquarters, is named after one of the coolest ideas in computer science: a program that runs programs. Cofounded in 2005 by Paul Graham, Robert Morris, Trevor Blackwell, and Jessica Livingston, YC offers small amounts of capital ($14,000–$20,000) to founders in exchange for, on average, 6% of each company. Thousands of applications flow in for dozens of spots in each “class,” leading to an acceptance rate of 2.5–3.5%.

Brian Chesky, cofounder of Airbnb, says of Paul Graham, the godfather of YC: “Just as [legendary music producer John] Hammond found Bob Dylan when he was a bad singer no one knew, Graham can spot potential.” If Graham can spot potential, the question I had was: how does he do it? The answer: YC has funded more than 450 start-ups since 2005. They have a far better sample size than most venture capitalists. I vividly remember my first visit to Y Combinator Demo Day. The only photograph I took was of a graph labeled “The Process” on a whiteboard, reflective of a good data set, which follows. For many reasons, it fascinated and amused me. First and foremost, I’d sketched out an eerily similar graph for language learning in 2005, which follows. This sketch, covering roughly eight months, represented my Japanese learning curve from 1992. Why did I draw it in 2005?


pages: 276 words: 78,094

Design for Hackers: Reverse Engineering Beauty by David Kadavy

Airbnb, complexity theory, en.wikipedia.org, Firefox, Isaac Newton, John Gruber, Paul Graham, Ruby on Rails, semantic web, Silicon Valley, Silicon Valley startup, Steve Jobs, TaskRabbit, web application, wikimedia commons, Y Combinator

In today’s world, that often means learning at least a little coding, but the hacker attitude can be applied to problem solving of all kinds. People who live by the hacker attitude are curious. They do whatever it takes to achieve their visions. They’re entrepreneurial. They value skills and knowledge over titles and experience. At the forefront of the hacker movement is the Hacker News community (http://news.ycombinator.com), a news aggregation site contributed to by followers of Paul Graham’s Y Combinator entrepreneurial incubator program. The program tends to fund small teams of hackers who have used their skills and hacker attitude to build cool products that solve problems: UserVoice (www.uservoice.com) democratizes customer support; Reddit (www.reddit.com) democratizes news; Dropbox (www.dropbox.com) provides an easy, automatic backup solution; and AirBNB (www.airbnb.com) turns extra bedrooms into places for travelers to stay.


pages: 302 words: 73,946

People Powered: How Communities Can Supercharge Your Business, Brand, and Teams by Jono Bacon

Airbnb, barriers to entry, blockchain, bounce rate, Cass Sunstein, Charles Lindbergh, Debian, Firefox, if you build it, they will come, IKEA effect, Internet Archive, Jono Bacon, Kickstarter, Kubernetes, lateral thinking, Mark Shuttleworth, Minecraft, minimum viable product, more computing power than Apollo, planetary scale, pull request, Richard Stallman, Richard Thaler, sexual politics, Silicon Valley, Travis Kalanick, Y Combinator

People Powered provides a clear and thoughtful blueprint for others looking to tap into this potential and unlock benefits for their own organizations. —Jim Whitehurst, President and CEO, Red Hat; Author, The Open Organization In my profession, building networks is all about nurturing relationships for the long term. Jono Bacon has authored the recipe on how to do this, and you should follow it. —Gia Scinto, Head of Talent, Y Combinator Continuity Communities are the future of business, technology, and collaboration. Jono Bacon’s experience, approach, and candor is critical reading for harnessing this future. —Jim Zemlin, Executive Director, The Linux Foundation If you want to harness the power of your customers, People Powered should be the first book you open. Highly recommended. —Whitney Bouck, COO, HelloSign Jono Bacon has spent years perfecting the craft of building productive communities.


Buy Then Build: How Acquisition Entrepreneurs Outsmart the Startup Game by Walker Deibel

barriers to entry, Clayton Christensen, commoditize, deliberate practice, discounted cash flows, diversification, Elon Musk, family office, financial independence, high net worth, intangible asset, inventory management, Jeff Bezos, knowledge worker, Lean Startup, Mark Zuckerberg, meta analysis, meta-analysis, Network effects, new economy, Peter Thiel, risk tolerance, risk/return, rolodex, software as a service, Steve Jobs, supply-chain management, Y Combinator

Hal Clifford for confirming and fine tuning my outline, Brooke White for getting me to a final first draft (finally), Erin Tyler for the perfect cover, and Tucker Max for the tough love at all the right times. If there is a single word in this book that shouldn’t be there, trust me that Tucker told me with conviction to remove it. My Publishing Manager Katherine Sears could not have been a better partner. She started Booktrope, a disruptive market network for selfpublished authors. After raising over seven figures of capital and going through Y-Combinator, the # 1 accelerator program in the world, she met early success. After almost two years of running a successful, aggressively growing company she was faced with a change in product-market fit, and the startup capitulated through no fault of her team. She understands first-hand how a great product, all-star team, world class training, and amazing idea can fail in execution from external sources.


The Code: Silicon Valley and the Remaking of America by Margaret O'Mara

"side hustle", A Declaration of the Independence of Cyberspace, accounting loophole / creative accounting, affirmative action, Airbnb, AltaVista, Amazon Web Services, Apple II, Apple's 1984 Super Bowl advert, autonomous vehicles, back-to-the-land, barriers to entry, Ben Horowitz, Berlin Wall, Bob Noyce, Buckminster Fuller, Burning Man, business climate, Byte Shop, California gold rush, carried interest, clean water, cleantech, cloud computing, cognitive dissonance, commoditize, computer age, continuous integration, cuban missile crisis, Danny Hillis, DARPA: Urban Challenge, deindustrialization, different worldview, don't be evil, Donald Trump, Doomsday Clock, Douglas Engelbart, Dynabook, Edward Snowden, El Camino Real, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Frank Gehry, George Gilder, gig economy, Googley, Hacker Ethic, high net worth, Hush-A-Phone, immigration reform, income inequality, informal economy, information retrieval, invention of movable type, invisible hand, Isaac Newton, Jeff Bezos, Joan Didion, job automation, job-hopping, John Markoff, Julian Assange, Kitchen Debate, knowledge economy, knowledge worker, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, mass immigration, means of production, mega-rich, Menlo Park, Mikhail Gorbachev, millennium bug, Mitch Kapor, Mother of all demos, move fast and break things, move fast and break things, mutually assured destruction, new economy, Norbert Wiener, old-boy network, pattern recognition, Paul Graham, Paul Terrell, paypal mafia, Peter Thiel, pets.com, pirate software, popular electronics, pre–internet, Ralph Nader, RAND corporation, Richard Florida, ride hailing / ride sharing, risk tolerance, Robert Metcalfe, Ronald Reagan, Sand Hill Road, Second Machine Age, self-driving car, shareholder value, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, skunkworks, Snapchat, social graph, software is eating the world, speech recognition, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supercomputer in your pocket, technoutopianism, Ted Nelson, the market place, the new new thing, There's no reason for any individual to have a computer in his home - Ken Olsen, Thomas L Friedman, Tim Cook: Apple, transcontinental railway, Uber and Lyft, uber lyft, Unsafe at Any Speed, upwardly mobile, Vannevar Bush, War on Poverty, We wanted flying cars, instead we got 140 characters, Whole Earth Catalog, WikiLeaks, William Shockley: the traitorous eight, Y Combinator, Y2K

It was about that “pattern recognition” so fatefully identified by John Doerr, looking for the next Stanford or Harvard dropout with a wild but brilliant idea. Of all those assertions, Doerr’s slip-up came closest to the heart of the Valley’s secret. “West Coast investors aren’t bolder because they’re irresponsible cowboys, or because the good weather makes them optimistic,” wrote Paul Graham, founder of the Valley’s most influential tech incubator, Y Combinator, in 2007. “They’re bolder because they know what they’re doing.” The Valley power players knew the tech, knew the people, and knew the formula that worked. They looked for “grade-A men” (who very occasionally were women) from the nation’s best engineering and computer science programs, or from the most promising young companies, and who had validation from someone else they already knew.

., 36 Wayne, Ron, 148 Web 2.0, 361, 373 Weinberger, Caspar, 245 WELL, The, 258, 286, 287, 369 Wells, Katherine, 319 West Coast Computer Faire, 140, 150–51, 157, 186 West Coast Electronics Manufacturers Association (WEMA), 34, 35, 164, 166, 168 Westinghouse, 25, 26 White, Mark, 265 Whitney, Dick, 160 Whole Earth Catalog, 118, 128, 150, 257 Wick, Charles, 196 Widlar, Bob, 97, 112 Wiener, Norbert, 56, 119 Wikipedia, 368–69 Wilson, Charlie, 25 Wilson, John, 78 Wilson, Rand, 264 Wilson Sonsini Goodrich & Rosati, 79, 164, 305, 342, 344–45, 354–55 Winamp, 357 Winblad, Ann, 274, 345 Winograd, Terry, 248, 254, 352, 353, 355, 369 Wired, 303, 327, 333 Wirth, Tim, 192–94, 215, 216, 222, 304 Wojcicki, Susan, 354 Wordsworth, William, 148 World Altair Computer Convention, 139–40 World’s Fair, 48, 49, 153 World War II, 7, 11, 18, 20–24, 26, 28, 34, 37, 54, 70, 78, 81, 352 World Wide Web, 20, 258, 287, 289, 303, 305, 307–10, 332, 341, 342, 353, 363, 371 Wozniak, Steve, 138, 139, 146–51, 154, 157, 178, 181, 189, 224, 232, 285, 304, 404 Wyly, Sam, 58 Xerox, 76, 128–31, 133, 147, 231, 234, 248 Xerox PARC, see Palo Alto Research Center Y2K, 347–48 Yahoo!, 309, 352–54, 361, 362, 366, 368–70 Yammer, 395 Yang, Jerry, 283, 284, 308–9, 316, 377 Y Combinator, 399 Young, John, 213, 215, 223, 237–38, 295–97 YouTube, 365, 369, 403 Yu, Albert, 141–42 Zschau, Ed, 95–96, 166, 168, 170, 171, 197, 221–22, 224, 225, 250, 261–62, 331, 334–36 Zuckerberg, Mark, 367, 368, 370–74, 392, 393, 402–4 ABCDEFGHIJKLMNOPQRSTUVWXYZ ABOUT THE AUTHOR Margaret O'Mara is Professor of History at the University of Washington. She writes and teaches about the history of U.S. politics, the growth of the high-tech economy, and the connections between the two, and is the author of Cities of Knowledge and Pivotal Tuesdays.


pages: 290 words: 119,172

Beginning Backbone.js by James Sugrue

Airbnb, continuous integration, don't repeat yourself, Firefox, Google Chrome, loose coupling, MVC pattern, node package manager, single page application, web application, Y Combinator

This section of the book lists some highprofile examples and gives five good reasons to use Backbone, along with another list that describes where it might not be suitable. Companies Using Backbone Some of the brightest companies in the world use Backbone to power their latest applications. Let’s take a look at three of these companies and find out why they have chosen Backbone. You’ll find many more case studies listed at the official Backbone web site. 11 Chapter 1 ■ An Introduction to Backbone.js Airbnb Airbnb is one of Y Combinator’s greatest success stories, providing a collaborative sharing service for people to rent living space across 192 countries. Airbnb has used Backbone in a number of its products, from its mobile web application to web site features including wish lists and matching and in its own internal applications. An example of how Backbone is used in the mobile website can be seen in Figure 1-8. Figure 1-8.


pages: 232

A Discipline of Programming by E. Dijkstra

finite state, Turing machine, Y Combinator

To give the example for Euclid's cardboard game: we can guarantee a final state satisfying the postcondition (1) for any initial state satisfying GCD(x, y) == GCD(X, Y) and 0 < x < 500 and 0 < y < 500 (2) (The upper limits have been added to do justice to the limited size of the cardboard. If we start with a pair (X, Y) such that GCD(X, Y) == 713, then there exists no pair (x, y) satisfying condition (2), i.e. for those values of X and Y condition (2) reduces to F; and that means that the machine in question cannot be used to compute the GCD(X, Y) for that pair of values of X and Y.) For many (X, Y) combinations, many states satisfy (2). In the case that o < X < 500 and 0 < Y < 500, the trivial choice is x == X and y == Y. It is a choice that can be made without any evaluation of the GCD-function, even without appealing to the fact that the GCD-function is a symmetric function of its arguments. The condition that characterizes the set of all initial states such that activation will certainly result in a properly terminating happening leaving the system in a final state satisfying a given post-condition is called "the weakest pre-condition corresponding to that post-condition".


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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

Having bought a $37.5 million, 89-acre property in Half Moon Bay, a coastal town just south of San Francisco, Khosla unilaterally declared independence and blocked all public access to a much-loved local beach beside his property.74 Balaji Srinivasan, a Stanford University lecturer and startup entrepreneur, has taken the secession fantasy one crazy step further. At one of Paul Graham’s “Failure Central” Y Combinator startup events, Srinivasan pitched the concept of what he called “Silicon Valley’s Ultimate Exit,” a complete withdrawal of Silicon Valley from the United States. “We need to build opt-in society, outside the US, run by technology,” is how he described a ridiculous fantasy that would turn Silicon Valley into a kind of free-floating island that Wired’s Bill Wasik satirizes as the “offshore plutocracy of Libertaristan.”75 And one group of “Libertaristanians” at the Peter Thiel–funded, Silicon Valley–based Seasteading Institute, founded by Patri Friedman, a former Google engineer and the grandson of the granddaddy of free-market economics, Milton Friedman, has even begun to plan floating utopias that would drift off the Pacific coast.76 Behind all these secession fantasies is the very concrete reality of the secession of the rich from everyone else in Silicon Valley.


pages: 297 words: 84,009

Big Business: A Love Letter to an American Anti-Hero by Tyler Cowen

23andMe, Affordable Care Act / Obamacare, augmented reality, barriers to entry, Bernie Sanders, bitcoin, blockchain, Bretton Woods, cloud computing, cognitive dissonance, corporate governance, corporate social responsibility, correlation coefficient, creative destruction, crony capitalism, cryptocurrency, dark matter, David Brooks, David Graeber, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, experimental economics, Filter Bubble, financial innovation, financial intermediation, global reserve currency, global supply chain, Google Glasses, income inequality, Internet of things, invisible hand, Jeff Bezos, late fees, Mark Zuckerberg, mobile money, money market fund, mortgage debt, Network effects, new economy, Nicholas Carr, obamacare, offshore financial centre, passive investing, payday loans, peer-to-peer lending, Peter Thiel, pre–internet, price discrimination, profit maximization, profit motive, RAND corporation, rent-seeking, reserve currency, ride hailing / ride sharing, risk tolerance, Ronald Coase, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, The Nature of the Firm, Tim Cook: Apple, too big to fail, transaction costs, Tyler Cowen: Great Stagnation, ultimatum game, WikiLeaks, women in the workforce, World Values Survey, Y Combinator

In 2017, some of the critics pointed to Juicero, a $400 Wi-Fi–enabled juicer that has been called “the absurd avatar of Silicon Valley hubris.” (The company later went under.) Scott Alexander, one of my favorite bloggers (on the internet, of course), set out to rebut this charge. Here is what he found: I looked at the latest batch of 52 startups from legendary Silicon Valley startup incubator Y Combinator. Thirteen of them had an altruistic or international development focus, including Neema, an app to help poor people without access to banks gain financial services; Kangpe, online health services for people in Africa without access to doctors; Credy, a peer-to-peer lending service in India; Clear Genetics, an automated genetic counseling tool for at-risk parents; and Dost Education, helping to teach literacy skills in India via a $1/month course.


pages: 352 words: 87,930

Space 2.0 by Rod Pyle

additive manufacturing, air freight, barriers to entry, Colonization of Mars, commoditize, crony capitalism, crowdsourcing, Donald Trump, Elon Musk, experimental subject, Intergovernmental Panel on Climate Change (IPCC), Jeff Bezos, low earth orbit, Mars Rover, mouse model, risk-adjusted returns, Search for Extraterrestrial Intelligence, Silicon Valley, Silicon Valley startup, stealth mode startup, Stephen Hawking, telerobotics, trade route, wikimedia commons, X Prize, Y Combinator

“How big is the market for small launch vehicles?” Space News, April 11, 2016. 49Howell, Elizabeth. “How to Poop in Space: NASA Unveils Winners of the Space Poop Challenge.” Space.com, February 15, 2017. CHAPTER 8: SPACE EXPLORATION TECHNOLOGIES COR P. 50Masunaga, Samantha. “SpaceX track record ‘right in the ballpark’ with 93% success rate.” Los Angeles Times, September 1, 2016. 51Sam Altman interview with Elon Musk for Y Combinator, September 2016. 52Dillow, Clay. “The Great Rocket Race.” Fortune, October 2016. 53Brown, Alex. “Why Elon Musk Is Suing the U.S. Air Force.” The Atlantic, June 5, 2014. 54De Selding, Peter. “SpaceX’s reusable Falcon 9: What are the real cost savings for customers?” SpaceNews, April 25, 2016. 55This figure is quoted across a wide range. Lowest estimates fall at about $1,200 per pound via SpaceX, and go up to about $7,500 per pound for other launch providers.


pages: 403 words: 87,035

The New Geography of Jobs by Enrico Moretti

assortative mating, Bill Gates: Altair 8800, business climate, call centre, cleantech, cloud computing, corporate raider, creative destruction, desegregation, Edward Glaeser, financial innovation, global village, hiring and firing, income inequality, industrial cluster, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, knowledge economy, labor-force participation, low skilled workers, manufacturing employment, Mark Zuckerberg, mass immigration, medical residency, Menlo Park, new economy, peer-to-peer lending, Peter Thiel, Productivity paradox, Richard Florida, Sand Hill Road, Silicon Valley, Skype, special economic zone, Startup school, Steve Jobs, Steve Wozniak, thinkpad, Tyler Cowen: Great Stagnation, Wall-E, Y Combinator, zero-sum game

.” [>] “The speed at which things move”: Kane, “Overseas Start-Ups Move In.” [>] For example, studies have shown: Baumgardner, “Physicians’ Services and the Division of Labor Across Local Markets.” [>] Think about the history of Facebook: In a recent interview, Zuckerberg criticized several aspects of Silicon Valley’s culture that he does not like but admitted that “Facebook would not have worked if I had stayed in Boston.” Interview at Y Combinator’s Startup School, October 29, 2011. [>] The size of labor markets: Wheeler, “Local Market Scale and the Pattern of Job Changes Among Young Men”; Bleakley and Lin, “Thick-Market Effects and Churning in the Labor Market.” [>] In a recent study of changing family structure: Costa and Kahn, “Power Couples.” [>] “where Ericsson has more than 1,200 employees”: Clark, “Overseas Tech Firms Ramp Up Hiring in Silicon Valley.” [>] One study finds that the likelihood: Sorenson and Stuart, “Syndication Networks and the Spatial Distribution of Venture Capital Investment.” [>] “to be closer”: Delo, “When the Car-Rental Fleet Is Parked in Your Driveway.” [>] “it is tough to get funding”: Gelles, “All Roads Lead to the Valley.” [>] “There’s a lot of support”: Interview, “The Changing Role of the Venture Capitalist,” Marketplace, NPR, January 18, 2011. [>] “to be close to the action”: Kissack, “Electric Vehicle Companies Tap Silicon Valley Cash.” [>] “Knowledge flows are invisible”: Quoted in Jaffe, Trajtenberg, and Henderson, “Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations.” [>] In 1993 three economists: Ibid. [>] Excluding citations that come from the same company: Thompson, “Patent Citations and the Geography of Knowledge Spillovers.” [>] “cricket spills over”: Lohr, “Silicon Valley Shaped by Technology and Traffic.” [>] Citations are highest: Belenzon and Schankerman, “Spreading the Word.” [>] Geographical distance seems to impede: Adams and Jaffe, “Bounding the Effects of R&D.” [>] Pierre Azoulay, Joshua Graff Zivin, and Jialan Wang: Azoulay, Graff Zivin, and Wang, “Superstar Extinction.” [>] When a team of Harvard Medical School doctors: Lee, Brownstein, Mills, and Kohane, “Does Collocation Inform the Impact of Collaboration?”


pages: 292 words: 81,699

More Joel on Software by Joel Spolsky

a long time ago in a galaxy far, far away, barriers to entry, Black Swan, Build a better mousetrap, business process, call centre, Danny Hillis, David Heinemeier Hansson, failed state, Firefox, fixed income, George Gilder, Larry Wall, low cost airline, low cost carrier, Mars Rover, Network effects, Paul Graham, performance metric, place-making, price discrimination, prisoner's dilemma, Ray Oldenburg, Ruby on Rails, Sand Hill Road, Silicon Valley, slashdot, social software, Steve Ballmer, Steve Jobs, Superbowl ad, The Great Good Place, type inference, unpaid internship, wage slave, web application, Y Combinator

If you’re a web app developer and you don’t want to support the SDK everybody else is supporting, you’ll increasingly find that people won’t use your web app, because it doesn’t, you know, support cut and paste and address book synchronization and whatever weird new interop features we’ll want in 2010. Imagine, for example, that you’re Google with Gmail, and you’re feeling rather smug. But then somebody you’ve never heard of, some bratty Y Combinator startup, maybe, is gaining ridiculous traction selling NewSDK, which combines a great portable programming language 176 More from Joel on Software that compiles to JavaScript, and even better, a huge Ajaxy library that includes all kinds of clever interop features. Not just cut and paste: cool mashup features like synchronization and single-point identity management (so you don’t have to tell Facebook and Twitter what you’re doing, you can just enter it in one place).


pages: 294 words: 96,661

The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity by Byron Reese

agricultural Revolution, AI winter, artificial general intelligence, basic income, Buckminster Fuller, business cycle, business process, Claude Shannon: information theory, clean water, cognitive bias, computer age, crowdsourcing, dark matter, Elon Musk, Eratosthenes, estate planning, financial independence, first square of the chessboard, first square of the chessboard / second half of the chessboard, full employment, Hans Rosling, income inequality, invention of agriculture, invention of movable type, invention of the printing press, invention of writing, Isaac Newton, Islamic Golden Age, James Hargreaves, job automation, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, lateral thinking, life extension, Louis Pasteur, low skilled workers, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Mary Lou Jepsen, Moravec's paradox, On the Revolutions of the Heavenly Spheres, pattern recognition, profit motive, Ray Kurzweil, recommendation engine, Rodney Brooks, Sam Altman, self-driving car, Silicon Valley, Skype, spinning jenny, Stephen Hawking, Steve Wozniak, Steven Pinker, strong AI, technological singularity, telepresence, telepresence robot, The Future of Employment, the scientific method, Turing machine, Turing test, universal basic income, Von Neumann architecture, Wall-E, Watson beat the top human players on Jeopardy!, women in the workforce, working poor, Works Progress Administration, Y Combinator

In that regard, they may be like the pantheon of Greek gods, all both powerful and idiosyncratic, relegating us to the role of pawns in their dramas. All of these are more than abstract worries. There are people working on these concerns right now. Since we probably couldn’t defeat a malicious AGI given that we couldn’t ever outsmart it, our best plan is to never make a malicious AGI. To that end, Elon Musk along with Sam Altman, the president of the start-up incubator Y Combinator, cochair a nonprofit called OpenAI that has as its purpose to help usher in the era of safe and beneficial AI. The initial blog post announcing its formation states, “Because of AI’s surprising history, it’s hard to predict when human-level AI might come within reach. When it does, it’ll be important to have a leading research institution which can prioritize a good outcome for all over its own self-interest.”


pages: 284 words: 92,688

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

activist fund / activist shareholder / activist investor, Airbnb, Ben Horowitz, Bernie Madoff, bitcoin, call centre, cleantech, cloud computing, corporate governance, disruptive innovation, dumpster diving, fear of failure, Filter Bubble, Golden Gate Park, Google Glasses, Googley, Gordon Gekko, hiring and firing, Jeff Bezos, Lean Startup, Lyft, Marc Andreessen, 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, Stanford prison experiment, Steve Ballmer, Steve Jobs, Steve Wozniak, telemarketer, tulip mania, uber lyft, Y Combinator, éminence grise

It’s wrapped up in the mythology that has sprung up around start-ups. Almost by definition these companies are founded and run by young people. Young people are the ones who change the world. They’re filled with passion. They have new ideas. Venture capitalists openly admit they prefer to invest in twenty-something founders. “The cut-off in investors’ heads is thirty-two,” Paul Graham, who runs an incubator called Y Combinator, once said, adding that, “I can be tricked by anyone who looks like Mark Zuckerberg.” John Doerr, a legendary venture capitalist and partner at Kleiner Perkins, once said he liked to invest in “white male nerds who have dropped out of Harvard or Stanford and they have absolutely no social life. When I see that pattern coming in, it [is] very easy to decide to invest.” Companies prefer the same thing.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy and hold, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, corporate raider, creative destruction, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Mitch Kapor, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

Everyone from Marc Andreessen (Netscape) to Sean Parker (Napster) to Peter Thiel (PayPal) to Jack Dorsey (Twitter) now runs venture funds of his own. Facebook and Google, once startups themselves, now acquire more businesses than they incubate internally. With each new generation, firms and investors leverage the startup economy more deliberately, or even cynically. After all, a win is a win. Take OMGPop, a gaming Web site startup that won a spot in the Y Combinator incubator to build social games. It soon enjoyed moderate success with a Facebook game but then couldn’t seem to get any traction. With good advice from its venture-savvy mentors—all former startup founders themselves—the company pivoted from one sector to another, looking for a sweet spot. It picked up another cohort of mentors, including the famed startup studio Betaworks, who helped steer the company toward a trending yet underserved market segment: mobile social gaming.


Rockonomics: A Backstage Tour of What the Music Industry Can Teach Us About Economics and Life by Alan B. Krueger

accounting loophole / creative accounting, Affordable Care Act / Obamacare, Airbnb, autonomous vehicles, bank run, Berlin Wall, bitcoin, Bob Geldof, butterfly effect, buy and hold, creative destruction, crowdsourcing, disintermediation, diversified portfolio, Donald Trump, endogenous growth, George Akerlof, gig economy, income inequality, index fund, invisible hand, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kickstarter, Live Aid, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, moral hazard, Network effects, obamacare, offshore financial centre, Paul Samuelson, personalized medicine, pre–internet, price discrimination, profit maximization, random walk, recommendation engine, rent-seeking, Richard Thaler, ride hailing / ride sharing, Saturday Night Live, Skype, Steve Jobs, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, ultimatum game, winner-take-all economy, women in the workforce, Y Combinator, zero-sum game

Their first album went triple platinum. Thinking that the good times would continue, Smith spent extravagantly. His second album, however, was a flop. Smith jokes that it went “double plastic.” He neglected to pay his income taxes, and the Internal Revenue Service repossessed Smith’s car and motorcycle, assessed him with a $2.8 million tax debt, and garnished his income. “Being famous and broke,” Smith recalled, “is a s****y combination, because you’re still famous and people recognize you, but they recognize you while you’re sitting on the bus.”30 On the verge of bankruptcy, Smith caught a break. A chance meeting led to an impromptu audition at Quincy Jones’s mansion in Bel Air, and the rest is history, as Smith went on to become one of Hollywood’s biggest stars. Musicians are not so different from many Americans when it comes to making financial decisions, but the unpredictable nature of their income, the high rate of self-employment, and the laser-like focus on their art often makes their financial situation more perilous.


pages: 343 words: 101,563

The Uninhabitable Earth: Life After Warming by David Wallace-Wells

"Robert Solow", agricultural Revolution, Albert Einstein, anthropic principle, Asian financial crisis, augmented reality, basic income, Berlin Wall, bitcoin, British Empire, Buckminster Fuller, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon-based life, cognitive bias, computer age, correlation does not imply causation, cryptocurrency, cuban missile crisis, decarbonisation, Donald Trump, effective altruism, Elon Musk, endowment effect, energy transition, everywhere but in the productivity statistics, failed state, fiat currency, global pandemic, global supply chain, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, Joan Didion, John Maynard Keynes: Economic Possibilities for our Grandchildren, labor-force participation, life extension, longitudinal study, Mark Zuckerberg, mass immigration, megacity, megastructure, mutually assured destruction, Naomi Klein, nuclear winter, Pearl River Delta, Peter Thiel, plutocrats, Plutocrats, postindustrial economy, quantitative easing, Ray Kurzweil, rent-seeking, ride hailing / ride sharing, Sam Altman, Silicon Valley, Skype, South China Sea, South Sea Bubble, Steven Pinker, Stewart Brand, the built environment, the scientific method, Thomas Malthus, too big to fail, universal basic income, University of East Anglia, Whole Earth Catalog, William Langewiesche, Y Combinator

It is hard to know just how seriously to take these visions, though they are close to universal among the Bay Area’s futurist vanguard, who have succeeded the NASAs and the Bell Labs of the last century as architects of our imagined future—and who differ among themselves primarily in their assessments of just how long it will take for all this to come to pass. Peter Thiel may complain about the pace of technological change, but maybe he’s doing so because he’s worried it won’t outpace ecological and political devastation. He’s still investing in dubious eternal-youth programs and buying up land in New Zealand (where he might ride out social collapse on the civilization scale). Y Combinator’s Sam Altman, who has distinguished himself as a kind of tech philanthropist with a small universal-basic-income pilot project and recently announced a call for geoengineering proposals he might invest in, has reportedly made a down payment on a brain-upload program that would extract his mind from this world. It’s a project in which he is also an investor, naturally. For Bostrom, the very purpose of “humanity” is so transparently to engineer a “posthumanity” that he can use the second term as a synonym for the first.


pages: 335 words: 96,002

WEconomy: You Can Find Meaning, Make a Living, and Change the World by Craig Kielburger, Holly Branson, Marc Kielburger, Sir Richard Branson, Sheryl Sandberg

Airbnb, Albert Einstein, barriers to entry, blood diamonds, business intelligence, business process, carbon footprint, clean water, cleantech, Colonization of Mars, corporate social responsibility, Downton Abbey, Elon Musk, energy transition, family office, future of work, global village, inventory management, James Dyson, job satisfaction, Kickstarter, market design, meta analysis, meta-analysis, microcredit, Nelson Mandela, Occupy movement, pre–internet, shareholder value, sharing economy, Silicon Valley, Snapchat, Steve Jobs, telemarketer, The Fortune at the Bottom of the Pyramid, working poor, Y Combinator

Frontline is an amazing example that if you invest boldly at the right moment, you can have extraordinary impact. Essie North, current Big Change M.D., sums up exactly how elated we felt when we heard the news: “Today, the most satisfying feedback we get from our project partners is that by supporting them, when and how we did, we've influenced other organizations to do the same. An example of a similar model, but in the high-tech sector, would be the Y Combinator in Silicon Valley, which takes some of the best tech ideas and incubates them in those early stages with mentors. They can then access funding because they've proved their impact. Taking bold bets does mean you have to roll your sleeves up and get down and dirty sometimes.” You'll experience some trepidation because you are leading the way and approaching charity from a different angle—but you will encourage others to follow and therefore bring about real change.


pages: 572 words: 94,002

Reset: How to Restart Your Life and Get F.U. Money: The Unconventional Early Retirement Plan for Midlife Careerists Who Want to Be Happy by David Sawyer

Airbnb, Albert Einstein, asset allocation, beat the dealer, bitcoin, Cal Newport, cloud computing, cognitive dissonance, crowdsourcing, cryptocurrency, David Attenborough, David Heinemeier Hansson, Desert Island Discs, diversification, diversified portfolio, Edward Thorp, Elon Musk, financial independence, follow your passion, gig economy, hiring and firing, index card, index fund, invention of the wheel, knowledge worker, loadsamoney, low skilled workers, Mahatma Gandhi, Mark Zuckerberg, meta analysis, meta-analysis, mortgage debt, passive income, passive investing, Paul Samuelson, pension reform, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Silicon Valley, Skype, smart meter, Snapchat, stakhanovite, Steve Jobs, Tim Cook: Apple, Vanguard fund, Y Combinator

[471] “A Renaissance man”: “Renaissance Man – Wikipedia.” toreset.me/471. [472] “use the income from that to pay for everything else”: “Early Retirement Extreme: A Philosophical and Practical... – Amazon UK.” toreset.me/472, (Kindle version) Location 1,151. [473] “Character is destiny”: “Character is Destiny – Thoughts And Ideas – Medium.” 31 Jan. 2017, toreset.me/473. [474] Charlie Munger…gave a talk to USC Business School in 1994: “Y Combinator: Elementary Worldly Wisdom.” toreset.me/474. [475] “The future belongs to those who learn more skills and combine them in creative ways”: “Quote by Robert Greene: “The future belongs to those who learn more...” toreset.me/475. [476] “It is this stamp of personality, of individual view, which is known as individuality”: “Jack London’s Wisdom on Living a Life of Thumos – The Art of Manliness.” 11 Dec. 2017, toreset.me/476.


pages: 1,076 words: 67,364

Haskell Programming: From First Principles by Christopher Allen, Julie Moronuki

c2.com, en.wikipedia.org, natural language processing, spaced repetition, Turing complete, Turing machine, type inference, web application, Y Combinator

Recursion is a means of expressing code that must take an indefinite number of steps to return a result. But the lambda calculus does not appear on the surface to have any means of recursion, because of the anonymity of expressions. How do you call something without a name? Being able to write recursive functions, though, is essential to Turing completeness. We use a combinator – known as the Y combinator or fixed-point combinator – to write recursive functions in the lambda calculus. Haskell has native recursion ability based on the same principle as the Y combinator. It is important to have a solid understanding of the behavior of recursive functions. In later chapters, we will see that, in fact, it is not often necessary to write our own recursive functions, as many standard higher-order functions have built-in recursion. But without understanding the systematic behavior of recursion itself, it can be difficult to reason about those HOFs.


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

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

He points to the example of his technology-savvy son, Luukas, who works in government: “He’s never going to invent a billion-dollar app, but he’s in policy, and he understands the policy implications, and that is, I think, one of our problems right now: we don’t have, in Europe at least, people at the policymaking level who understand what IT is about.” * * * But what about the many children born around the world who will not have access to college? There are several resources that have arisen lately that democratize access to important programming skills. One is Codeacademy, a Y Combinator project cofounded by two 23-year-olds that teaches people how to code for free online. Codeacademy counts more than 24 million people around the globe who have used its resources. A second incredible resource is Scratch, a project of the Lifelong Kindergarten Group at the MIT Media Lab. It’s a nonprofit endeavor that teaches programming. It is free and doesn’t require a download. It is well-suited to low-bandwidth environments and available in more than 40 languages.


pages: 419 words: 109,241

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, blue-collar work, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Khan Academy, Kickstarter, low skilled workers, lump of labour, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Network effects, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator

An early edition of the laws, from 1552, stated, rather dramatically, that “if any man or woman, able to work, should refuse to labor and live idly for three days, he or she should be branded with a red hot iron on the breast with the letter V and should be judged the slave for two years of any person who should inform against such idler.”13 The resentment runs both ways. While those in work rail against the unemployed, those without work also feel aggrieved toward those with it. This, in part, explains the curious reaction to Silicon Valley’s recent enthusiasm about the UBI. Mark Zuckerberg and Elon Musk have made supportive noises about the idea of a UBI; Pierre Omidyar, founder of eBay, and Sam Altman, founder of Y Combinator, have funded trials of it in Kenya and the United States.14 But their interest has been met with widespread hostility. If work were simply a means to an income, that response might seem odd: these entrepreneurs were essentially proposing that people like them should do all the hard work and give everyone else money for free. For many people, though, work means more than securing a wage—and so, in their eyes, the offer of a UBI from those in fantastically well-paid jobs might have felt more like hush money, or a bribe, perhaps even an attempt to monopolize a source of life’s meaning and deny it to others.


pages: 648 words: 108,814

Solr 1.4 Enterprise Search Server by David Smiley, Eric Pugh

Amazon Web Services, bioinformatics, cloud computing, continuous integration, database schema, domain-specific language, en.wikipedia.org, fault tolerance, Firefox, information retrieval, Ruby on Rails, web application, Y Combinator

NW, , Atlanta, , 30327 About the Reviewers James Brady is an entrepreneur and software developer living in San Francisco, CA. Originally from England, James discovered his passion for computer science and programming while at Cambridge University. Upon graduation, James worked as a software engineer at IBM's Hursley Park laboratory—a role which taught him many things, most importantly, his desire to work in a small company. In January 2008, James founded WebMynd Corp., which received angel funding from the Y Combinator fund, and he relocated to San Francisco. WebMynd is one of the largest installations of Solr, indexing up to two million HTML documents per day, and making heavy use of Solr's multicore features to enable a partially active index. Jerome Eteve holds a BSC in physics, maths and computing and an MSC in IT and bioinformatics from the University of Lille (France). After starting his career in the field of bioinformatics, where he worked as a biological data management and analysis consultant, he's now a senior web developer with interests ranging from database level issues to user experience online.


pages: 402 words: 126,835

The Job: The Future of Work in the Modern Era by Ellen Ruppel Shell

3D printing, affirmative action, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, Amazon Mechanical Turk, basic income, Baxter: Rethink Robotics, big-box store, blue-collar work, Buckminster Fuller, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, cloud computing, collective bargaining, computer vision, corporate governance, corporate social responsibility, creative destruction, crowdsourcing, deskilling, disruptive innovation, Donald Trump, Downton Abbey, Elon Musk, Erik Brynjolfsson, factory automation, follow your passion, Frederick Winslow Taylor, future of work, game design, glass ceiling, hiring and firing, immigration reform, income inequality, industrial robot, invisible hand, Jeff Bezos, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, low skilled workers, Lyft, manufacturing employment, Marc Andreessen, Mark Zuckerberg, means of production, move fast and break things, move fast and break things, new economy, Norbert Wiener, obamacare, offshore financial centre, Paul Samuelson, precariat, Ralph Waldo Emerson, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, Steve Jobs, The Chicago School, Thomas L Friedman, Thorstein Veblen, Tim Cook: Apple, Uber and Lyft, uber lyft, universal basic income, urban renewal, white picket fence, working poor, Y Combinator, young professional, zero-sum game

the “social vaccine of the 21st century” Critics point to a conflict of interest: rather than promote technology that contributes to general human flourishing, Silicon Valley elites favor UBI as a publicly supported solution that does not impede their profit-making activities. See, for example, Jathan Sadowski, “Why Silicon Valley Is Embracing Universal Basic Income,” Guardian, July 14, 2017, https://www.thegu­ardian.com/​technology/​2016/​jun/​22/​silicon-valley-universal-basic-income-y-combinator. an addictive public handout Predictions that a BIG (basic income guarantee) would result in many people laying around lazily are not supported by the evidence. In particular, Brazil’s subsistence-level BIG program has resulted in very little change in workforce participation. Given a choice, most people choose to work, and the World Bank has determined that such supports even increase individual efforts to find work, as they allow people to take risks.


pages: 452 words: 134,502

Hacking Politics: How Geeks, Progressives, the Tea Party, Gamers, Anarchists and Suits Teamed Up to Defeat SOPA and Save the Internet by David Moon, Patrick Ruffini, David Segal, Aaron Swartz, Lawrence Lessig, Cory Doctorow, Zoe Lofgren, Jamie Laurie, Ron Paul, Mike Masnick, Kim Dotcom, Tiffiniy Cheng, Alexis Ohanian, Nicole Powers, Josh Levy

4chan, Affordable Care Act / Obamacare, Airbnb, Bernie Sanders, Burning Man, call centre, Cass Sunstein, Chelsea Manning, collective bargaining, creative destruction, crony capitalism, crowdsourcing, don't be evil, facts on the ground, Firefox, hive mind, immigration reform, informal economy, jimmy wales, Julian Assange, Kickstarter, liquidity trap, Mark Zuckerberg, obamacare, Occupy movement, offshore financial centre, peer-to-peer, plutocrats, Plutocrats, prisoner's dilemma, rent-seeking, Silicon Valley, Skype, technoutopianism, WikiLeaks, Y Combinator

The magic of reddit comes from an appreciation Steve and I had from the day we launched—nothing would work without a truly empowered community. So we’d guide people to a common subreddit (r/SOPA) and see what bubbled up. I posted a quick YouTube video explaining why I was publicly in opposition: “The story of reddit, where Steve Huffman and I started it from an apartment in Medford, MA with 12k in funding from Y Combinator simply could not have happened in a world with this bill … and it’s not just reddit, it’s every single other social media site out there that would be threatened by this bill. And that is devastating. It’s something we simply cannot afford to do from an economic standpoint.” An unprecedented display of democracy in action culminated on January 18, with simultaneously offline and online protests.


pages: 444 words: 127,259

Super Pumped: The Battle for Uber by Mike Isaac

"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, always be closing, Amazon Web Services, Andy Kessler, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Bay Area Rapid Transit, Burning Man, call centre, Chris Urmson, Chuck Templeton: OpenTable:, citizen journalism, Clayton Christensen, cloud computing, corporate governance, creative destruction, don't be evil, Donald Trump, Elon Musk, family office, gig economy, Google Glasses, Google X / Alphabet X, high net worth, Jeff Bezos, John Markoff, Kickstarter, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Menlo Park, Mitch Kapor, money market fund, moral hazard, move fast and break things, move fast and break things, Network effects, new economy, off grid, peer-to-peer, pets.com, Richard Florida, ride hailing / ride sharing, Sand Hill Road, self-driving car, shareholder value, side project, Silicon Valley, Silicon Valley startup, skunkworks, Snapchat, software as a service, software is eating the world, South China Sea, South of Market, San Francisco, sovereign wealth fund, special economic zone, Steve Jobs, TaskRabbit, the payments system, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ubercab, union organizing, upwardly mobile, Y Combinator

Chapter 16: THE APPLE PROBLEM 156 BuzzFeed ran its story: Ben Smith, “Uber Executive Suggests Digging Up Dirt on Journalists,” BuzzFeedNews, November 17, 2014, https://www.buzzfeednews.com/article/bensmith/uber-executive-suggests-digging-up-dirt-on-journalists. 156 an enterprising young hacker: Average Joe, “What the Hell Uber? Uncool Bro.,” Gironsec (blog), November 25, 2014, https://www.gironsec.com/blog/2014/11/what-the-hell-uber-uncool-bro/. 156 it landed on Hacker News: “Permissions Asked for by Uber Android App,” Y Combinator, November 25, 2014, https://news.ycombinator.com/item?id=8660336. Chapter 17: “THE BEST DEFENSE . . .” 165 Kalanick also held court over “Hell”: Amir Efrati, “Uber’s Top Secret ‘Hell’ Program Exploited Lyft’s Vulnerability,” The Information, April 12, 2017, https://www.theinformation.com/articles/ubers-top-secret-hell-program-exploited-lyfts-vulnerability. 166 Those programs fell under: Kate Conger, “Uber’s Massive Scraping Program Collected Data About Competitors Around The World.”


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Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, algorithmic trading, anthropic principle, asset allocation, autonomous vehicles, Bayesian statistics, Berlin Wall, Bill Duvall, bitcoin, Community Supported Agriculture, complexity theory, constrained optimization, cosmological principle, cryptocurrency, Danny Hillis, David Heinemeier Hansson, delayed gratification, dematerialisation, diversification, Donald Knuth, double helix, Elon Musk, fault tolerance, Fellow of the Royal Society, Firefox, first-price auction, Flash crash, Frederick Winslow Taylor, George Akerlof, global supply chain, Google Chrome, Henri Poincaré, information retrieval, Internet Archive, Jeff Bezos, Johannes Kepler, John Nash: game theory, John von Neumann, Kickstarter, knapsack problem, Lao Tzu, Leonard Kleinrock, linear programming, martingale, Nash equilibrium, natural language processing, NP-complete, P = NP, packet switching, Pierre-Simon Laplace, prediction markets, race to the bottom, RAND corporation, RFC: Request For Comment, Robert X Cringely, Sam Altman, sealed-bid auction, second-price auction, self-driving car, Silicon Valley, Skype, sorting algorithm, spectrum auction, Stanford marshmallow experiment, Steve Jobs, stochastic process, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, urban planning, Vickrey auction, Vilfredo Pareto, Walter Mischel, Y Combinator, zero-sum game

It’s as exciting a sport as ever, but as athletes overfit their tactics to the quirks of scorekeeping, it becomes less useful in instilling the skills of real-world swordsmanship. Perhaps nowhere, however, is overfitting as powerful and troublesome as in the world of business. “Incentive structures work,” as Steve Jobs put it. “So you have to be very careful of what you incent people to do, because various incentive structures create all sorts of consequences that you can’t anticipate.” Sam Altman, president of the startup incubator Y Combinator, echoes Jobs’s words of caution: “It really is true that the company will build whatever the CEO decides to measure.” In fact, it’s incredibly difficult to come up with incentives or measurements that do not have some kind of perverse effect. In the 1950s, Cornell management professor V. F. Ridgway cataloged a host of such “Dysfunctional Consequences of Performance Measurements.” At a job-placement firm, staffers were evaluated on the number of interviews they conducted, which motivated them to run through the meetings as quickly as possible, without spending much time actually helping their clients find jobs.


Convergence Culture: Where Old and New Media Collide by Henry Jenkins

barriers to entry, Cass Sunstein, citizen journalism, collective bargaining, Columbine, deskilling, Donald Trump, game design, George Gilder,