Y Combinator

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pages: 216 words: 61,061

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

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Airbnb, barriers to entry, carbon-based life, cloud computing, crowdsourcing, en.wikipedia.org, Hans Rosling, hiring and firing, Internet Archive, Kickstarter, 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.


pages: 559 words: 155,372

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

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Airbnb, airport security, Amazon Web Services, Burning Man, Celtic Tiger, centralized clearinghouse, cognitive dissonance, collective bargaining, corporate governance, Credit Default Swap, crowdsourcing, death of newspapers, El Camino Real, Elon Musk, Emanuel Derman, financial independence, global supply chain, Goldman Sachs: Vampire Squid, hive mind, income inequality, interest rate swap, intermodal, Jeff Bezos, Malcom McLean invented shipping containers, Mark Zuckerberg, Maui Hawaii, means of production, Menlo Park, minimum viable product, move fast and break things, Network effects, Paul Graham, performance metric, Peter Thiel, Ponzi scheme, pre–internet, Ralph Waldo Emerson, random walk, Sand Hill Road, Scientific racism, second-price auction, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, social web, Socratic dialogue, Steve Jobs, telemarketer, urban renewal, Y Combinator, 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

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8-hour work day, affirmative action, AltaVista, Apple II, Brewster Kahle, business process, Byte Shop, Danny Hillis, don't be evil, fear of failure, financial independence, Firefox, full text search, game design, Googley, HyperCard, illegal immigration, Internet Archive, Jeff Bezos, Maui Hawaii, Menlo Park, nuclear winter, Paul Buchheit, Paul Graham, Peter Thiel, Richard Feynman, Richard Feynman, 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: 294 words: 82,438

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

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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, 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.


pages: 94 words: 26,453

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

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3D printing, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, fear of failure, Filter Bubble, future of work, Google Glasses, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, Lean Startup, low skilled workers, Mark Zuckerberg, move fast and break things, Paul Erdős, Paul Graham, recommendation engine, rising living standards, Robert Shiller, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, 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: 317 words: 84,400

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

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

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: 468 words: 124,573

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

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Airbnb, Amazon Web Services, barriers to entry, Black Swan, business intelligence, call centre, crowdsourcing, 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, Mark Zuckerberg, minimum viable product, move fast and break things, Network effects, Oculus Rift, Paul Graham, 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, 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.


pages: 56 words: 16,788

The New Kingmakers by Stephen O'Grady

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

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.


pages: 353 words: 104,146

European Founders at Work by Pedro Gairifo Santos

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

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

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3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, clean water, collapse of Lehman Brothers, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, 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, Joseph Schumpeter, Kickstarter, lone genius, manufacturing employment, Mark Zuckerberg, Martin Wolf, new economy, Paul Graham, Peter Thiel, 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: 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

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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: 211 words: 77

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

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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: 91,520

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

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affirmative action, Airbnb, Albert Einstein, Bernie Sanders, Clayton Christensen, David Brooks, en.wikipedia.org, Frederick Winslow Taylor, future of work, immigration reform, income inequality, index card, Jeff Bezos, jimmy wales, 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, 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

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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, conceptual framework, continuous integration, crowdsourcing, disintermediation, 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, 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, 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, The Spirit Level, total factor productivity, transaction costs, Uber and 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.


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

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

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: 274 words: 75,846

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

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

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: 270 words: 79,180

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

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Affordable Care Act / Obamacare, Airbnb, Al Roth, Black Swan, buy low sell high, Credit Default Swap, cross-subsidies, crowdsourcing, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, Jean Tirole, Lean Startup, Lyft, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, ride hailing / ride sharing, 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, 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

The Economic Singularity: Artificial intelligence and the death of capitalism by Calum Chace

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3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, 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, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, lump of labour, Lyft, 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, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, 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, Thomas Malthus, transaction costs, Tyler Cowen: Great Stagnation, Uber for X, 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: 169 words: 56,250

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

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barriers to entry, cleantech, cloud computing, corporate social responsibility, Grace Hopper, job satisfaction, Kickstarter, labour mobility, Lean Startup, minimum viable product, Network effects, Peter Thiel, place-making, pre–internet, Richard Florida, Silicon Valley, Silicon Valley startup, smart cities, software as a service, Steve Jobs, text mining, Y Combinator, 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: 238 words: 73,824

Makers by Chris Anderson

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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, crowdsourcing, dark matter, David Ricardo: comparative advantage, death of newspapers, dematerialisation, Elon Musk, factory automation, Firefox, future of work, global supply chain, global village, 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, profit maximization, race to the bottom, Richard Feynman, Richard Feynman, Ronald Coase, 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: 268 words: 75,850

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

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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, computer age, death of newspapers, deferred acceptance, 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, Kevin Kelly, Kodak vs Instagram, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, 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: 310 words: 34,482

Makers at Work: Folks Reinventing the World One Object or Idea at a Time by Steven Osborn

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3D printing, A Pattern Language, additive manufacturing, air freight, Airbnb, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, c2.com, computer vision, crowdsourcing, dumpster diving, en.wikipedia.org, Firefox, future of work, Google Chrome, Google Glasses, Google Hangouts, Hacker Ethic, Internet of things, Iridium satellite, Khan Academy, Kickstarter, Mason jar, means of production, Minecraft, minimum viable product, Network effects, Oculus Rift, patent troll, popular electronics, Rodney Brooks, Shenzhen was a fishing village, side project, Silicon Valley, Skype, slashdot, social software, software as a service, special economic zone, speech recognition, subscription business, telerobotics, urban planning, web application, Y Combinator

We joined a program called Y Combinator, which is an incubator in Silicon Valley. That was our first connection to the Valley. In Canada, we were initially trying to raise money from angel or seed investors, and it was nearly impossible. The only funding sources that I found in Canada were my parents and the government. We were unable to convince any private investors. It was tough because as a hardware company, we had to physically make things. We finally got the chance to go down to Silicon Valley to join the Y Combinator program in early 2011.3 We thought it would be a massive change in our ability to raise money. Silicon Valley and is where people dream big and they believe in random, crazy, and potentially difficult ideas. After going through three months of Y Combinator, we went into the demo day and tried again to raise money.


pages: 624 words: 127,987

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

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Albert Einstein, Atul Gawande, Black Swan, 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 Ricardo: comparative advantage, Dean Kamen, delayed gratification, discounted cash flows, double entry bookkeeping, Douglas Hofstadter, en.wikipedia.org, Frederick Winslow Taylor, Gödel, Escher, Bach, high net worth, hindsight bias, index card, inventory management, iterative process, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, loose coupling, loss aversion, 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, 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: 669 words: 210,153

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

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Airbnb, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Black Swan, blue-collar work, Buckminster Fuller, business process, Cal Newport, call centre, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, 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, Kevin Kelly, Kickstarter, Lao Tzu, life extension, Mahatma Gandhi, Mark Zuckerberg, Mason jar, Menlo Park, Mikhail Gorbachev, Nicholas Carr, optical character recognition, PageRank, passive income, pattern recognition, Paul Graham, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, post scarcity, premature optimization, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, Richard Feynman, risk tolerance, Ronald Reagan, 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

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

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23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, barriers to entry, Berlin Wall, business process, call centre, cashless society, citizen journalism, clean water, connected car, credit crunch, crowdsourcing, death of newspapers, disintermediation, diversified portfolio, don't be evil, fear of failure, Firefox, future of journalism, 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, 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, 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: 368 words: 96,825

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

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

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: 397 words: 102,910

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

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4chan, Any sufficiently advanced technology is indistinguishable from magic, Brewster Kahle, buy low sell high, corporate governance, 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, Lean Startup, Paul Buchheit, Paul Graham, profit motive, RAND corporation, Republic of Letters, Richard Stallman, 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

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

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: 374 words: 89,725

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

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3D printing, Airbnb, carbon footprint, Clayton Christensen, clean water, fear of failure, Google X / Alphabet X, Isaac Newton, Jeff Bezos, jimmy wales, 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, 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: 102 words: 27,769

Rework by Jason Fried, David Heinemeier Hansson

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call centre, Clayton Christensen, Dean Kamen, Exxon Valdez, fault tolerance, James Dyson, Jeff Bezos, Ralph Nader, risk tolerance, 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: 647 words: 43,757

Types and Programming Languages by Benjamin C. Pierce

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Albert Einstein, combinatorial explosion, experimental subject, finite state, Henri Poincaré, recommendation engine, sorting algorithm, Turing complete, Turing machine, type inference, Y Combinator

The omega combinator has a useful generalization called the fixed-point combinator,6 which can be used to help define recursive functions such as factorial.7 fix = λf. (λx. f (λy. x x y)) (λx. f (λy. x x y)); Like omega, the fix combinator has an intricate, repetitive structure; it is difficult to understand just by reading its definition. Probably the best way of getting some intuition about its behavior is to watch how it works on a specific example. 8 Suppose we want to write a recursive function definition 6. It is often called the call-by-value Y-combinator. Plotkin (1975) called it Z. 7. 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. 8. 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. 66 5 The Untyped Lambda-Calculus of the form h = hbody containing hi—i.e., we want to write a definition where the term on the right-hand side of the = uses the very function that we are defining, as in the definition of factorial on page 52.

—Albert Einstein Index ∈ alternate notation for type membership, 92 ⇒ arrow kind, 441 ⇓ big-step evaluation, 42 Π dependent function type, 463 :: derivation of, 203 ↑ divergence, 16 dom(Γ ) domain of Γ , 101 « “quick check” exercise, xviii «« easy exercise, xviii ««« moderate exercise, xviii «««« challenging exercise, xviii 3 exercise without solution, xviii → function type, 100 :: kind membership, 449 ∗ -→ multi-step evaluation, 39 -→ one-step evaluation, 36 l parallel reduction of types, 454 L record labels, 129 R + transitive closure of R, 17 R ∗ reflexive, transitive closure, 17 ñ 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 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, 381–387 606 Index 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 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 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 Index 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, 204–206 607 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, 465 608 Index Curry-Howard correspondence, 2, 108– 109, 341, 429 Curry-style presentation, 111 currying, 58, 73 of type operators, 440 cut elimination, 109 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 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 Index 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 (terminology), 24 extended calculus of constructions, 11 Extended Static Checking, 3 extensible records, see row variables extensible variant type, 177 extensions of the simply typed lambdacalculus, 117–146 external language, 53, 120 F, see System F Fω , see System Fω ω Fω <: , see System F<: F<: , see System F<: F-bounded quantification, 393, 408 F-closed set, 282 F-consistent set, 282 F1 , F2 , F3 , etc., 461 609 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– 245 610 Index 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 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 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 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 Index 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 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<: , 432–435 611 joinsub implementation, 218–220 judgment, 36 KEA, 226 kernel F<: , 391 kinding, 439–447, 459 kinds dependent, 445 power, 445 row, 445 singleton, 445 Knaster-Tarski fixed point theorem, 283 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 lambdacalculus 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, 81 612 Index 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 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 Index ν, 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 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, 475–489 613 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 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, 204 614 Index 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, 409 615 Index 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 qualified types, 338 quantification, see polymorphism Quest, 11, 409 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, 198 616 Index 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 Index 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, 42 617 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, 454 618 Index 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 Index 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 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, 55 619 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, 76 620 Index 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 Index ML implementation, 381–387 System Fω , 449–466 and higher-order logic, 109 fragments, 461 System Fω <: , 467–473 System F<: , 389–409 kernel and full variants, 391 System λω , 445–447 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, 289 621 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 622 Index 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 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 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 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 Index well-founded order, 18 set, 18 well-typed term, 93 width subtyping, 183 wildcard bindings, 119–121 witness type, 364 wrong, 42, 73 XML, 9, 207, 313 Y combinator, 65 Year 2000 problem, 9 Z combinator, 65 623

., 461 609 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– 245 610 Index 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 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 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 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 Index 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 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<: , 432–435 611 joinsub implementation, 218–220 judgment, 36 KEA, 226 kernel F<: , 391 kinding, 439–447, 459 kinds dependent, 445 power, 445 row, 445 singleton, 445 Knaster-Tarski fixed point theorem, 283 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 lambdacalculus 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, 81 612 Index 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 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 Index ν, 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 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, 475–489 613 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 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, 204 614 Index 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, 409 615 Index 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 qualified types, 338 quantification, see polymorphism Quest, 11, 409 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, 198 616 Index 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 Index 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, 42 617 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, 454 618 Index 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 Index 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 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, 55 619 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, 76 620 Index 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 Index ML implementation, 381–387 System Fω , 449–466 and higher-order logic, 109 fragments, 461 System Fω <: , 467–473 System F<: , 389–409 kernel and full variants, 391 System λω , 445–447 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, 289 621 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 622 Index 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 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 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 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 Index well-founded order, 18 set, 18 well-typed term, 93 width subtyping, 183 wildcard bindings, 119–121 witness type, 364 wrong, 42, 73 XML, 9, 207, 313 Y combinator, 65 Year 2000 problem, 9 Z combinator, 65 623


pages: 455 words: 133,322

The Facebook Effect by David Kirkpatrick

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Andy Kessler, Burning Man, delayed gratification, demand response, don't be evil, global village, happiness index / gross national happiness, Howard Rheingold, Jeff Bezos, 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.


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

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3D printing, Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, 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 blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, Internet of things, inventory management, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, 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, underbanked, WikiLeaks, Y Combinator, Y2K, 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.


pages: 527 words: 147,690

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

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

.* 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: 163 words: 46,523

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

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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

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Airbnb, AltaVista, Cass Sunstein, choice architecture, cognitive bias, cognitive dissonance, en.wikipedia.org, framing effect, game design, Google Glasses, 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, Silicon Valley, Silicon Valley startup, Snapchat, TaskRabbit, telemarketer, 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 startup products and services designed around mobile user needs and behaviors. To uncover where interfaces are changing, Paul Buchheit, Partner at Y-Combinator, encourages entrepreneurs to “live in the future.” [cxxxix] 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 watch 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. *** Remember and Share - The Hook Model helps the product designer generate an initial prototype for a habit-forming technology.


pages: 138 words: 40,787

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

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3D printing, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, business intelligence, call centre, Clayton Christensen, cloud computing, connected car, crowdsourcing, data acquisition, 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, Network effects, Paul Graham, Ray Kurzweil, RFID, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

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: 270 words: 64,235

Effective Programming: More Than Writing Code by Jeff Atwood

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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, 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

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

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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, Mark Zuckerberg, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, 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, Uber and Lyft, Uber for X, 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: 666 words: 181,495

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

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

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: 1,065 words: 229,099

Real World Haskell by Bryan O'Sullivan, John Goerzen, Donald Stewart, Donald Bruce Stewart

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bash_history, database schema, Debian, distributed revision control, domain-specific language, en.wikipedia.org, Firefox, general-purpose programming language, job automation, p-value, Plutocrats, plutocrats, revision control, sorting algorithm, transfer pricing, type inference, web application, Y Combinator

Horizontal concatenation of documents, for example, is easy to specify by writing a reference implementation on lists: -- file: ch11/QC.hs prop_hcat xs = hcat xs == glue xs where glue [] = empty glue (d:ds) = d <> glue ds It is a similar story for punctuate, where we can model inserting punctuation with list interspersion (from Data.List, intersperse is a function that takes an element and interleaves it between other elements of a list): -- file: ch11/QC.hs prop_punctuate s xs = punctuate s xs == intersperse s xs While this looks fine, running it reveals a flaw in our reasoning: ghci> quickCheck prop_punctuate Falsifiable, after 6 tests: Empty [Line,Text "",Line] The pretty-printing library optimizes away redundant empty documents, something the model implementation doesn’t do, so we’ll need to augment our model to match reality. First, we can intersperse the punctuation text throughout the document list, and then a little loop to clean up the Empty documents scattered through, like so: -- file: ch11/QC.hs prop_punctuate' s xs = punctuate s xs == combine (intersperse s xs) where combine [] = [] combine [x] = [x] combine (x:Empty:ys) = x : combine ys combine (Empty:y:ys) = y : combine ys combine (x:y:ys) = x `Concat` y : combine ys Running this in GHCi, we can confirm the result. It is reassuring to have the test framework spot the flaws in our reasoning about the code—exactly what we’re looking for: ghci> quickCheck prop_punctuate' passed 100 tests. Putting It All Together We can put all these tests together in a single file and run them simply using one of QuickCheck’s driver functions.


pages: 292 words: 81,699

More Joel on Software by Joel Spolsky

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barriers to entry, Black Swan, Build a better mousetrap, business process, call centre, Danny Hillis, failed state, Firefox, George Gilder, low cost carrier, Mars Rover, Network effects, Paul Graham, performance metric, place-making, price discrimination, prisoner's dilemma, Ray Oldenburg, 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: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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

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: 232

A Discipline of Programming by E. Dijkstra

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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: 290 words: 119,172

Beginning Backbone.js by James Sugrue

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Airbnb, continuous integration, 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: 284 words: 92,688

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

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

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: 364 words: 99,897

The Industries of the Future by Alec Ross

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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, knowledge economy, knowledge worker, litecoin, M-Pesa, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, new economy, offshore financial centre, open economy, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

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: 366 words: 94,209

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

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3D printing, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, 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, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, 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, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, 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, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, unpaid internship, Y Combinator, young professional, 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.


pages: 1,076 words: 67,364

Haskell Programming from first principles by Christopher Allen, Julie Moronuki

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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: 648 words: 108,814

Solr 1.4 Enterprise Search Server by David Smiley, Eric Pugh

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Amazon Web Services, bioinformatics, cloud computing, continuous integration, database schema, domain-specific language, en.wikipedia.org, fault tolerance, Firefox, information retrieval, Internet Archive, 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: 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

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

4chan, Affordable Care Act / Obamacare, Airbnb, Bernie Sanders, Burning Man, call centre, Cass Sunstein, collective bargaining, crony capitalism, crowdsourcing, don't be evil, facts on the ground, Firefox, hive mind, immigration reform, informal economy, jimmy wales, Kickstarter, liquidity trap, Mark Zuckerberg, obamacare, Occupy movement, offshore financial centre, 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: 523 words: 143,139

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

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4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, algorithmic trading, anthropic principle, asset allocation, autonomous vehicles, Berlin Wall, Bill Duvall, bitcoin, Community Supported Agriculture, complexity theory, constrained optimization, cosmological principle, cryptocurrency, Danny Hillis, delayed gratification, dematerialisation, diversification, 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, John Nash: game theory, John von Neumann, knapsack problem, Lao Tzu, linear programming, martingale, Nash equilibrium, natural language processing, NP-complete, P = NP, packet switching, prediction markets, race to the bottom, RAND corporation, RFC: Request For Comment, Robert X Cringely, sealed-bid auction, second-price auction, self-driving car, Silicon Valley, Skype, sorting algorithm, spectrum auction, Steve Jobs, stochastic process, Thomas Malthus, traveling salesman, Turing machine, urban planning, Vickrey auction, Walter Mischel, Y Combinator

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.


pages: 598 words: 183,531

Hackers: Heroes of the Computer Revolution - 25th Anniversary Edition by Steven Levy

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air freight, Apple II, Bill Gates: Altair 8800, Buckminster Fuller, Byte Shop, computer age, computer vision, corporate governance, El Camino Real, game design, Hacker Ethic, hacker house, Haight Ashbury, John Conway, Mark Zuckerberg, Menlo Park, non-fiction novel, Paul Graham, popular electronics, RAND corporation, reversible computing, Richard Stallman, Silicon Valley, software patent, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Ted Nelson, Whole Earth Catalog, Y Combinator

It’s one outpost in a growing number of "Hacker Spaces" across the country devoted to empowering formerly isolated and underequipped gearheads. “I am a sensei of the dojo, which as you may know is a grand revered master,” he says, a wide grin on his face. “Felsenstein sensei.” • • • • • • • • Greenblatt, Stallman, and Felsenstein see hacking as a set of ideals. But Paul Graham sees it as a humming economic engine. The forty-five-year-old Internet guru, himself a fanatic engineer in his day, is a cofounder of Y Combinator, an incubator for Internet startups. Twice a year, his company runs American Idol-style contests to select twenty to thirty budding companies to participate in a three-month boot camp, culminating in a demo day packed with Angel investors, VCs, and acquisition-hungry companies like Google and Yahoo. How does Graham pick the most promising candidates? Easy. He looks for the hackers. “We’re pretty hackerly so it’s easy to recognize a kindred spirit,” says Graham, who in 1995 co-created Viaweb, the first web-based application.


pages: 677 words: 206,548

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

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

Krieger, “Biological Computer Created at Stanford,” San Jose Mercury News, March 29, 2013; Tim Requarth and Greg Wayne, “Tiny Biocomputers Move Closer to Reality,” Scientific American, Nov. 2, 2011; Adam Baer, “Why Living Cells Are the Future of Data Processing,” Popular Science, Nov. 5, 2012. 42 The emerging field: Clay Dillow, “Bio-storage Scheme Turns E. coli Bacteria into Hard Drives,” Popular Science, Jan. 10, 2011. 43 The legendary geneticist: Wyss Institute, “Writing the Book in DNA,” Aug. 16, 2012, http://​wyss.​harvard.​edu/​viewpressrelease/​93/. 44 Not only do such storage techniques: Ibid. 45 Indeed, a whole host: Chiropractic Resource Organization, “NIH Heads Foresee the Future,” http://​www.​chiro.​org/; Helen Thomson, “Deaf People Get Gene Tweak to Restore Natural Hearing,” New Scientist, April 23, 2014. 46 The died-out mammoth: George M. Church, Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves (New York: Basic Books, 2012); J. Craig Venter, Life at the Speed of Light: From the Double Helix to the Dawn of Digital Life (New York: Viking Adult, 2013). 47 In another example: Kim-Mai Cutler, “Glowing Plant Is One of Y Combinator’s Very First Biotech Startups,” TechCrunch, Aug. 11, 2014. 48 Her estate eventually: Rebecca Skloot, The Immortal Life of Henrietta Lacks (New York: Broadway Books, 2011); Moore v. Regents of University of California (1990) 51 Cal. 3d 120 (271 Cal. Rptr. 146, 793 P.2d 479), Justia Law, accessed Sept. 12, 2014, http://​law.​justia.​com/. 49 Why did they: A case of Moore v. Regents of the University of California.


pages: 903 words: 235,753

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

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

Martin Lukacs, “Detroit's Water War: A Tap Shut-Off That Could Impact 300,000 People,” Guardian, June 25, 2014, http://www.theguardian.com/environment/true-north/2014/jun/25/detroits-water-war-a-tap-shut-off-that-could-impact-300000-people. 31.  See http://www.crimethinc.com/texts/ex/digital-utopia.html, https://www.youtube.com/watch?v=cOubCHLXT6A, and http://www.ftc.gov/sites/default/files/documents/public_statements/promoting-internet-inclusion-more-things-more-people/140107ces-iot.pdf. 32.  Balaji Srinivasa, “Silicon Valley's Ultimate Exit,” speech at the Y Combinator Startup School, De Anza College, Cupertino, CA, October 25, 2013, https://www.youtube.com/watch?v=cOubCHLXT6A. “Peacefully start an international (1) company, (2) community, (3) currency, (4) country. We are now at step 3.” (@balajis, January 3, 2014. 33.  Albert O. Hirschman, Exit, Voice, and Loyalty; Responses to Decline in Firms, Organizations, and States (Cambridge, MA: Harvard University Press, 1970). 34.