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Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers by John MacCormick, Chris Bishop
Ada Lovelace, AltaVista, Claude Shannon: information theory, fault tolerance, information retrieval, Menlo Park, PageRank, pattern recognition, Richard Feynman, Richard Feynman, Silicon Valley, Simon Singh, sorting algorithm, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, traveling salesman, Turing machine, Turing test, Vannevar Bush
However, the word-location trick and the metaword trick certainly convey the flavor of how real search engines construct and use indexes. The metaword trick did help AltaVista succeed—where others had failed—in finding efficient matches to the entire web. We know this because the metaword trick is described in a 1999 U.S. patent filing by AltaVista, entitled “Constrained Searching of an Index.” However, AltaVista's superbly crafted matching algorithm was not enough to keep it afloat in the turbulent early days of the search industry. As we already know, efficient matching is only half the story for an effective search engine: the other grand challenge is to rank the matching pages. And as we will see in the next chapter, the emergence of a new type of ranking algorithm was enough to eclipse AltaVista, vaulting Google into the forefront of the world of web search. 3 PageRank: The Technology That Launched Google The Star Trek computer doesn't seem that interesting.
Less than 10 years later, their company had become the greatest digital giant to rise in the internet age. But the idea of web search had already been around for several years. Among the earliest commercial offerings were Infoseek and Lycos (both launched in 1994), and AltaVista, which launched its search engine in 1995. For a few years in the mid-1990s, AltaVista was the king of the search engines. I was a graduate student in computer science during this period, and I have clear memories of being wowed by the comprehensiveness of AltaVista's results. For the first time, a search engine had fully indexed all of the text on every page of the web—and, even better, results were returned in the blink of an eye. Our journey toward understanding this sensational technological breakthrough begins with a (literally) age-old concept: indexing.
But the reasoning for page 3 is similar: we see that “cat” appears at location 2, and “sat” occurs at location 7, so they cannot possibly occur next to each other—because 7 is not immediately after 2. So we know that page 3 is not a hit for the phrase query “cat sat”, even though it /s a hit for the multiword query cat sat. By the way, the word-location trick is important for more than just phrase queries. As one example, consider the problem of finding words that are near to each other. On some search engines, you can do this with the NEAR keyword in the query. In fact, the AltaVista search engine offered this facility from its early days and still does at the time of writing. As a specific example, suppose that on some particular search engine, the query cat NEAR dog finds pages in which the word “cat” occurs within five words of the word “dog.” How can we perform this query efficiently on our data set? Using word locations, it's easy. The index entry for “cat” is 1-2, 3-2, and the index entry for “dog” is 2-2, 3-6.
In the Plex: How Google Thinks, Works, and Shapes Our Lives by Steven Levy
23andMe, AltaVista, Anne Wojcicki, Apple's 1984 Super Bowl advert, autonomous vehicles, book scanning, Brewster Kahle, Burning Man, business process, clean water, cloud computing, crowdsourcing, Dean Kamen, discounted cash flows, don't be evil, Donald Knuth, Douglas Engelbart, Douglas Engelbart, El Camino Real, fault tolerance, Firefox, Gerard Salton, Gerard Salton, Google bus, Google Chrome, Google Earth, Googley, HyperCard, hypertext link, IBM and the Holocaust, informal economy, information retrieval, Internet Archive, Jeff Bezos, John Markoff, Kevin Kelly, Mark Zuckerberg, Menlo Park, one-China policy, optical character recognition, PageRank, Paul Buchheit, Potemkin village, prediction markets, recommendation engine, risk tolerance, Rubik’s Cube, Sand Hill Road, Saturday Night Live, search inside the book, second-price auction, selection bias, Silicon Valley, skunkworks, Skype, slashdot, social graph, social software, social web, spectrum auction, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, Ted Nelson, telemarketer, trade route, traveling salesman, turn-by-turn navigation, Vannevar Bush, web application, WikiLeaks, Y Combinator
Since he didn’t have the assistance, the resources, the time, or the inclination, he didn’t attempt to index the entire web for his link analysis. Instead he did a kind of prewash. He typed a query into AltaVista, took the first two hundred results, and then used that subset for his own search. Interestingly, the best results for the query were often not included in those AltaVista solutions. For instance, if you typed in “newspaper,” Alta-Vista would not give you links for The New York Times or The Washington Post. “That’s not surprising, because AltaVista is about matching strings, and unless The New York Times happened to say, ‘I’m a newspaper!’ AltaVista is not going to find it,” Kleinberg explains. But, he suspected, he’d have more luck if he checked out what those 200 sites pointed to. “Among those 200 people who were saying ‘newspapers,’ someone was going to point to The New York Times,” he says.
He had a tough time convincing his bosses to open up the engine to the public. They argued that there was no way to make money from a search engine but relented when Monier sold them on the public relations aspect. (The system would be a testament to DEC’s powerful new Alpha processing chip.) On launch day, AltaVista had 16 million documents in its indexes, easily besting anything else on the net. “The big ones then had maybe a million pages,” says Monier. That was the power of AltaVista: its breadth. When DEC opened it to outsiders on December 15, 1995, nearly 300,000 people tried it out. They were dazzled. AltaVista’s actual search quality techniques—what determined the ranking of results—were based on traditional information retrieval (IR) algorithms. Many of those algorithms arose from the work of one man, a refugee from Nazi Germany named Gerard Salton, who had come to America, got a PhD at Harvard, and moved to Cornell University, where he cofounded its computer science department.
“For thirty years,” wrote one academic in tribute a year later, “Gerry Salton was information retrieval.” The World Wide Web was about to change that, but the academics didn’t know it—and neither did AltaVista. While its creators had the insight to gather all of the web, they missed the opportunity to take advantage of the link structure. “The innovation was that I was not afraid to fetch as much of the web as I could, store it in one place, and have a really fast response time. That was the novelty,” says Monier. Meanwhile, AltaVista analyzed what was on each individual page—using metrics like how many times each word appeared—to see if a page was a relevant match to a given keyword in a query. Even though there was no clear way to make money from search, AltaVista had a number of competitors. By 1996, when I wrote about search for Newsweek, executives from several companies were all boasting the most useful service.
The Invisible Web: Uncovering Information Sources Search Engines Can't See by Gary Price, Chris Sherman, Danny Sullivan
AltaVista, American Society of Civil Engineers: Report Card, bioinformatics, Brewster Kahle, business intelligence, dark matter, Donald Davies, Douglas Engelbart, Douglas Engelbart, full text search, HyperCard, hypertext link, information retrieval, Internet Archive, joint-stock company, knowledge worker, natural language processing, pre–internet, profit motive, publish or perish, search engine result page, side project, Silicon Valley, speech recognition, stealth mode startup, Ted Nelson, Vannevar Bush, web application
Table 1.1 A Timeline of Internet Search Technologies Year 1945 1965 1972 1986 1990 1991 1993 1994 1995 1996 1997 1998 1999 2000+ Search Service Vannevar Bush Proposes “MEMEX” Hypertext Coined by Ted Nelson Dialog—First Commercial Proprietary System OWL Guide Hypermedia Browser Archie for FTP Search, Tim Berners-Lee creates the Web Gopher: WAIS Distributed Search ALIWEB (Archie Linking), WWWWander, JumpStation, WWWWorm EINet Galaxy, WebCrawler, Lycos, Yahoo! Infoseek, SavvySearch, AltaVista, MetCrawler, Excite HotBot, LookSmart NorthernLight Google, InvisibleWeb.com FAST Hundreds of search tools 16 The Invisible Web In 1995 Infoseek, AltaVista, and Excite made their debuts, each offering different capabilities for the searcher. Metasearch engines—programs that searched several search engines simultaneously—also made an appearance this year (see Chapter 3 for more information about metasearch engines). SavvySearch, created by Daniel Dreilinger at Colorado State University, was the first metasearch engine, and MetaCrawler, from the University of Washington, soon followed.
LawCrawler provides the ability to limit your search to certain types of law related resources. These resources include a legal dictionary, legal NewsLaw reviews, U.S. government sites, the U.S. Constitution, the U.S. Legal Code, U.S. Supreme Court opinions, and information published by all federal circuit courts—even worldwide sites with legal information. Because LawCrawler is powered by the AltaVista search engine software, the searcher can also employ any of the advanced search capabilities provided by AltaVista, but the search is usefully restricted to the specific legal information domains indexed by LawCrawler. LawCrawler is part of the FedLaw service, which has numerous other legal resources, including a targeted directory. 42 The Invisible Web PsychCrawler http://www.psychcrawler.com This site is sponsored by an organization with knowledge of the topic, the American Psychological Association, which has a vested interest in making sure that high-quality material is crawled.
Yet you also hate them, because all too often they fail miserably at answering even the most basic questions or satisfying the simplest queries. They waste your time, they exasperate and frustrate, even provoking an extreme reaction, known as “Web rage,” in some people. It’s fair to ask, “What’s the problem here? Why is it so difficult to find the information I’m looking for?” The problem is that vast expanses of the Web are completely invisible to general-purpose search engines like AltaVista, HotBot, and Google. Even worse, this “Invisible Web” is in all likelihood growing significantly faster than the visible Web that you’re familiar with. It’s not that the search engines and Web directories are “stupid” or even badly engineered. Rather, they simply can’t “see” millions of high-quality resources that are available exclusively on the Invisible Web. So what is this Invisible Web and why aren’t search engines doing anything about making it visible?
Digital Wars: Apple, Google, Microsoft and the Battle for the Internet by Charles Arthur
activist fund / activist shareholder / activist investor, AltaVista, Build a better mousetrap, Burning Man, cloud computing, commoditize, credit crunch, crowdsourcing, disintermediation, don't be evil, en.wikipedia.org, Firefox, gravity well, Jeff Bezos, John Gruber, Mark Zuckerberg, Menlo Park, Network effects, PageRank, pre–internet, Robert X Cringely, Silicon Valley, Silicon Valley startup, skunkworks, Skype, slashdot, Snapchat, software patent, speech recognition, stealth mode startup, Steve Ballmer, Steve Jobs, the new new thing, the scientific method, Tim Cook: Apple, turn-by-turn navigation, upwardly mobile
The race at first looked as though it would go to the swift and the large. Compaq took a lead with AltaVista, a search engine set up essentially to show off the power of the 64-bit Alpha chip it had acquired along with Digital Equipment Corporation. The chips could chomp through huge indexes; all AltaVista needed then was to crawl the web and index it, and it would dominate; and it could make money by selling advertisements on its opening search page. That worked. But, as the web grew, the results it served up became polluted. Spam and porn sites began using ‘invisible’ text – white on a white background, or sized so small humans could not see it, but AltaVista’s crawler could. The problems with spam became increasingly annoying for users. But AltaVista’s revenues kept rising as more people came online. It wasn’t because it had significantly improved the user experience or its search results; it was because advertisers were buying more and more advertising slots.
If you couldn’t turn business that came your way from Google into sales, that wasn’t Google’s fault; it was your own. And nobody else seemed as good at driving traffic to sites. It was as Page and Brin had wanted: people came to the site and left it quickly. More and more, they exited via an advertisement. According to Jupiter Media Metrix data, in January 2001 AltaVista had more than 10 million visitors, and Google just under 9 million. AltaVista’s revenue however was collapsing, from $63 million in the quarter ending April 2000 to around $28 million in the three months to July 2001 (and at a thumping loss). A quarter of AltaVista’s staff had been laid off in September 2000. As revenue plummeted, so did the visitors essential to attract advertising revenue, to below 8 million in June 2001. In the same month, according to Media Metrix, Google had 13.4 million visitors. During the first half of 2001, it had become the busiest standalone search engine on the world wide web – a position it has held ever since.
(Page and Brin left it in a drawer in Stanford while they tried to get some more funding and figure out the mechanics of setting up the company that would be able to accept it. Bechtolsheim got about 1 per cent of the business.) At the time the site was answering about 10,000 queries a day; in September, around the time Gates and Stephens met, Page and Brin were just about to hire the company’s first employee, Craig Silverstein. Like Apple, Google was a minnow compared to the leader in its field – the search engine AltaVista, which had earned $50 million in sponsorship revenue in 1997 and was receiving 80 million hits per day. Even so, at the end of the year, Google was named one of the top 100 websites by PC Magazine. Given how few queries it was answering, that was a harbinger of things to come. Internet search At the time, despite its 1997 press release about MSN, internet search was not a high priority for Microsoft (or Apple, whose executives have never thought of it as a ‘web’ company).
I'm Feeling Lucky: The Confessions of Google Employee Number 59 by Douglas Edwards
Albert Einstein, AltaVista, Any sufficiently advanced technology is indistinguishable from magic, barriers to entry, book scanning, Build a better mousetrap, Burning Man, business intelligence, call centre, commoditize, crowdsourcing, don't be evil, Elon Musk, fault tolerance, Googley, gravity well, invisible hand, Jeff Bezos, job-hopping, John Markoff, Marc Andreessen, Menlo Park, microcredit, music of the spheres, Network effects, P = NP, PageRank, performance metric, pets.com, Ralph Nader, risk tolerance, second-price auction, side project, Silicon Valley, Silicon Valley startup, slashdot, stem cell, Superbowl ad, Y2K
By 2001 we felt we were clearly better than Inktomi results-wise, clearly better than AltaVista, clearly better than FAST. We had the best search engine." And what about Google's comparative quality the year before, when Netscape had become a partner? "Netscape was kind of crazy to switch their search to us," Urs confessed. He believed they made the change "in part because they didn't care about search that much ... It was a cost center." Not to mention that Omid Kordestani happened to be an excellent salesperson. "Omid could type in 'IBM' on Google and type in 'IBM' on AltaVista," Urs recalls, "and say 'Hey look, aren't our results better?' That was the level of sophistication. Our search was good, but our coverage was bad. You had all kinds of queries where we didn't have the page and AltaVista or Inktomi had it. People's expectations were just low."
It was likely a waste of buff-colored stationery and a thirty-three-cent stamp, because I was looking for the next big thing and I was pretty sure they weren't it. Search was so 1997. Still, since I'd sent Google a résumé, I figured I should give their product a try. I went to their site and entered the name of a girl I'd known in high school but hadn't heard from in twenty years. Even AltaVista, which I viewed as the best search engine available, had never found a trace of her, so my expectations were low when I hit the enter key. And there she was. Google listed her current contact information as the first result. I tried more searches. They all worked better than they had on AltaVista. I no longer begrudged Google the stationery and the stamp. Other signs pointed to something out of the ordinary. Sequoia Capital and Kleiner Perkins were the Montagues and Capulets of Silicon Valley venture capital (VC) firms. They had enviable success records individually—Yahoo, Amazon, Apple, Cisco Systems, Sun Microsystems—and an intense rivalry that usually kept them from investing in the same startup.
My life balance was about to get knocked on its inner ear. In less than a year I would be working sixteen-hour days and Jay would depart Google to pursue personal goals that were at odds with those of the company. What were Google's goals in late 1999? Hell if I knew. We were a search engine. What did search engines do? They searched. I assumed that we wanted to be the best damn search engine on the planet. Even better than AltaVista. It seemed unlikely we'd ever be a giant like Yahoo, given their head start, but maybe someday we'd be big enough to make Inktomi share the market for supplying portals with technology. There were no mouse pads imprinted with our mission statement or motivational posters on the walls urging us to surpass our sales targets as there had been at the Merc. If Googlers, or anyone else, had a clear vision of the company's future, they kept it hidden.
The Googlization of Everything: by Siva Vaidhyanathan
1960s counterculture, activist fund / activist shareholder / activist investor, AltaVista, barriers to entry, Berlin Wall, borderless world, Burning Man, Cass Sunstein, choice architecture, cloud computing, computer age, corporate social responsibility, correlation does not imply causation, creative destruction, data acquisition, death of newspapers, don't be evil, Firefox, Francis Fukuyama: the end of history, full text search, global village, Google Earth, Howard Rheingold, informal economy, information retrieval, John Markoff, Joseph Schumpeter, Kevin Kelly, knowledge worker, libertarian paternalism, market fundamentalism, Marshall McLuhan, means of production, Mikhail Gorbachev, moral panic, Naomi Klein, Network effects, new economy, Nicholas Carr, PageRank, pirate software, Ray Kurzweil, Richard Thaler, Ronald Reagan, side project, Silicon Valley, Silicon Valley ideology, single-payer health, Skype, social web, Steven Levy, Stewart Brand, technoutopianism, The Nature of the Firm, The Structural Transformation of the Public Sphere, Thorstein Veblen, urban decay, web application, zero-sum game
The New York Times apparently did not consider Google important enough to write about until its columnist Max Frankel mentioned Google among a list of search engines in November 1999.10 GOOGL E ’S WAYS A ND ME A N S 57 The ﬁrst serious consideration of Google by the New York Times, the leading American newspaper, was a de facto endorsement by the technology writer Peter Lewis in September 1999. “Until recently my favorite search engines were Hotbot (www.hotbot.com) and Alta Vista (www .altavista.com),” Lewis wrote. “Hotbot is useful for ﬁnding popular Web sites, and AltaVista is good at ferreting out obscure information. Alta Vista in particular returns a bazillion potential hits when it is asked to scour the Net for a word or phrase. But the larger the World Wide Web becomes, the more important it becomes for search engines to return fewer results, not more. Few people have time to click through 70,482 query matches hoping that the one they want, the most relevant one, is in there somewhere.
Many of Google’s positions correspond roughly with the public interest (such as giving empty support to a network neutrality policy and “safe-harbor” exemptions from copyright liability). Others, such as ﬁghting against stronger privacy laws in the United States, do not.13 REN D E R UNTO CA ESA R 19 When confronted with questions about its dominance in certain markets, Google ofﬁcials always protest that, on the Internet, barriers to entry are low, and thus any young ﬁrm with innovative services could displace Google the way Google displaced Yahoo and AltaVista in the early days of the twenty-ﬁrst century. With Google unable or unwilling to leverage its advantages though some sort of lockdown, such as holding users’ content and data hostage with technology or exclusive contracts so that they must continue to use Google services, they point out that users could easily migrate to the next Google-like company. As Google’s lawyer Dana Wagner says, “Competition is a click away.”14 Of course, that argument relies on the myth that Internet companies are weightless and virtual.
Because most of my research drew on sources available on microﬁlm, search engines had not yet become an integral part of my professional life. I was aware of the techno-utopian conversations about electronic archives and the global delivery of knowledge, but I didn’t think very hard about them. I had a book to write and sell. The Web, for me, was a platform for self-promotion. And existing search engines, like Yahoo, were not helping in that effort. Since about 1995 I had been using Yahoo and AltaVista for my Web navigation. I had a brief and passionate involvement with a much better and faster Web search service, Northern Light, until, facing a revenue shortage, it became a specialized portal for corporate clients (and remains so today). I ﬁrst learned 234 NOTES TO PAGE 81 about Google from an e-mail list called Red Rock Eater, written and edited by Phil Agre, a professor of information studies at UCLA.
Designing Great Data Products by Jeremy Howard, Mike Loukides, Margit Zwemer
We don’t claim that the Drivetrain Approach is the best or only method; our goal is to start a dialog within the data science and business communities to advance our collective vision. Objective-based data products We are entering the era of data as drivetrain, where we use data not just to generate more data (in the form of predictions), but use data to produce actionable outcomes. That is the goal of the Drivetrain Approach. The best way to illustrate this process is with a familiar data product: search engines. Back in 1997, AltaVista was king of the algorithmic search world. While their models were good at finding relevant websites, the answer the user was most interested in was often buried on page 100 of the search results. Then, Google came along and transformed online search by beginning with a simple question: What is the user’s main objective in typing in a search query? The four steps in the Drivetrain Approach. Google realized that the objective was to show the most relevant search result; for other companies, it might be increasing profit, improving the customer experience, finding the best path for a robot, or balancing the load in a data center.
This is not to say that Amazon’s recommendation engine could not have made the same connection; the problem is that this helpful recommendation will be buried far down in the recommendation feed, beneath books that have more obvious similarities to “Beloved.” The objective is to escape a recommendation filter bubble, a term which was originally coined by Eli Pariser to describe the tendency of personalized news feeds to only display articles that are blandly popular or further confirm the readers’ existing biases. As with the AltaVista-Google example, the lever a bookseller can control is the ranking of the recommendations. New data must also be collected to generate recommendations that will cause new sales. This will require conducting many randomized experiments in order to collect data about a wide range of recommendations for a wide range of customers. The final step in the drivetrain process is to build the Model Assembly Line.
Googled: The End of the World as We Know It by Ken Auletta
23andMe, AltaVista, Anne Wojcicki, Apple's 1984 Super Bowl advert, bioinformatics, Burning Man, carbon footprint, citizen journalism, Clayton Christensen, cloud computing, Colonization of Mars, commoditize, corporate social responsibility, creative destruction, death of newspapers, disintermediation, don't be evil, facts on the ground, Firefox, Frank Gehry, Google Earth, hypertext link, Innovator's Dilemma, Internet Archive, invention of the telephone, Jeff Bezos, jimmy wales, John Markoff, Kevin Kelly, knowledge worker, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Network effects, new economy, Nicholas Carr, PageRank, Paul Buchheit, Peter Thiel, Ralph Waldo Emerson, Richard Feynman, Richard Feynman, Sand Hill Road, Saturday Night Live, semantic web, sharing economy, Silicon Valley, Skype, slashdot, social graph, spectrum auction, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, strikebreaker, telemarketer, the scientific method, The Wisdom of Crowds, Upton Sinclair, X Prize, yield management, zero-sum game
Years later, he called it a “seminal” book, and remembered being amazed when he first read it “that people are so focused on outside things and are not focused on the functionality of things.” (It still drives him mad to stay in a hotel and not be able to figure out how to turn the lights off “in less than three minutes.”) The book, he said, strengthened the attitude he brought to designing the Google search engine, which was the opposite approach from existing search engines like Alta Vista. If you did a search for university on Alta Vista, it heaved at you every text that contained the word university, without ranking value or assessing whether people were actually using the links. Doing the same search, Google relied on the collective intelligence of its users and returned with the top ten universities. Thinking that “your customer or users are always right, and your goal is to build systems that work for them in a natural way, is a good attitude to have,” Page said.
They believed few of their customers would read a newspaper, magazine, or book online or on a handheld device. It was too hard on the eyes, screens were too small, desktop computers were not portable. They believed consumers would gravitate toward their bundled services, pleased to receive a single bill for a variety of offerings. They knew Google had bested many of the search firm pioneers—Excite, Alta Vista, Inktomi, Infoseek, GoTo, Lycos. But to most old media executives, Google was an exotic search service with puny text ads and a cute corporate motto. They were wrong about how a new generation interacted with their electronic devices. And they were wrong about Google. Technology moved fast, and was no friend to entrenched media companies. Only a dozen years before Karmazin’s 2003 visit, there was no World Wide Web, no DVDs, no satellite TV, no mobile phones or PDAs, no Tivos or DVRs, no digital cameras, no iPods, no PlayStation or Wii games, no blogs.
Brin and Page were unknowns and Conway remembers them approaching Fanning and saying, “What does it feel like to be on the cover of all those magazines?” “You guys have a really cool search product,” responded Fanning. “You’ll be more famous than I am!” Danny Sullivan, a former reporter who left newspapers in 1996 to publish a Web newsletter called Search Engine Watch (now called Search Engine Land), and who is the closest approximation to an umpire in the search world, remembers the early buzz about Google. The initial search engines—AltaVista, Highbot, Lycos, Excite, Infoseek, GoTo, Yahoo—were more interested in becoming “sticky portals” that trapped users on their sites, which diluted their focus on search. And when they performed a search, they were not impartial, allowing advertisers to buy their way to the top of the search results. Google, by contrast, “was really dedicated to search,” and refused to allow advertisers to distort the “science” of their search results.
AltaVista, barriers to entry, Black Swan, bounce rate, business intelligence, butterfly effect, call centre, Claude Shannon: information theory, complexity theory, correlation does not imply causation, en.wikipedia.org, first-price auction, information asymmetry, information retrieval, intangible asset, inventory management, life extension, linear programming, megacity, Nash equilibrium, Network effects, PageRank, place-making, price mechanism, psychological pricing, random walk, Schrödinger's Cat, sealed-bid auction, search engine result page, second-price auction, second-price sealed-bid, sentiment analysis, social web, software as a service, stochastic process, telemarketer, the market place, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Vickrey auction, Vilfredo Pareto, yield management
So in a way, each search engine’s sponsored-search platform is both cooperating with its own organic search service and in competition with that same organic search service! It was that way in the beginning and is still the same today. To get traffic, Overture entered into agreements with large Web portals of the time (e.g., CNN, Yahoo!, Microsoft) to serve advertisements on their Web sites (i.e., monetizing their existing traffic). Overture also purchased existing Web search engines, AltaVista and AlltheWeb.com. Potpourri: Yahoo! acquired Overture in 2003 and was later subsumed with Microsoft’s Bing sponsored-search platform in 2010, effectively taking Overture out of the sponsored-search business. Personally, I find it sad. But, the world moves on. 14 Understanding Sponsored Search In 2000, Google launched its first advertising effort, Google AdWords, although the pricing was at first based on number of impressions .
A SERP is the entire page and all content shown by a search engine in response to a searcher clicking a search or submit button or, if the search engine provides automated searching, by typing in the query. The space on the SERP is known as the screen real estate. To see the entire SERP, a searcher may have to scroll on the browser to the bottom portion of the SERP. Potpourri: Why do search engines list the advertisements in a separate listing? One of the major reasons was a complaint to the Federal Trade Commission (FTC) filed by Commercial Alert in July 2001 against AltaVista, AOL Time Warner, Direct Hit Technologies, iWon, LookSmart, Microsoft, and Lycos . The complaint alleged that the confusion caused in consumers who saw mixed paid and unpaid results in a combined listing constituted fraud in advertising by the search engines. After that, by convention, the sponsored results are listed separately, or at least labeled as sponsored if they are integrated with organic results.
Human Information behaviors are the conduits for human information processing, which is the methods of making sense of the information that we gather. Figure 3.3.â•‡ Framework of human information behavior, information-seeking behavior, and Â�information-searching behavior. Potpourri: Interestingly, the first academic studies of Web information searching using query logs from search engines (Excite, Infoseek, and AltaVista) all came out within a few months of each other (late 1998 and early 1999) and in the same outlet (SIGIR Forum). The three journal articles are: Jansen, B.J., Spink, A., Bateman, J., & Saracevic, T. (1998). Real life information retrieval: A study of user queries on the Web. SIGIR Forum, 32(1), 5–17. Kirsch, S. (1998). Infoseek’s experiences searching the Internet. SIGIR Forum, 32(2), 3–7. Silverstein, C., Henzinger, M., Marais, H., & Moricz, M. (1999).
Women Leaders at Work: Untold Tales of Women Achieving Their Ambitions by Elizabeth Ghaffari
Albert Einstein, AltaVista, business process, cloud computing, Columbine, corporate governance, corporate social responsibility, dark matter, family office, Fellow of the Royal Society, financial independence, follow your passion, glass ceiling, Grace Hopper, high net worth, knowledge worker, Long Term Capital Management, performance metric, pink-collar, profit maximization, profit motive, recommendation engine, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley startup, Steve Ballmer, Steve Jobs, thinkpad, trickle-down economics, urban planning, women in the workforce, young professional
So, I took him up on his offer to arrange an introduction to Digital. I stayed at Digital from April 1994 to May 1998, four years during which I had three different jobs and seven different bosses. I was a vice president in charge of the Software Group Strategy and then development for the AltaVista business unit. Those were the very early days of the internet. Digital had an e-mail product, a firewall product, and several other products related to the internet, including the search engine, all in the AltaVista business unit. The search engine became most closely linked to the AltaVista name. It was a very tumultuous period in Digital's history, which culminated in the sale of the company to Compaq Computer Company in 1998. Ghaffari: Did you observe that there were many women along the way in your career in technology? Horan: Now, that's a really interesting question.
She was in charge of development of the Lotus brand (1998–2002), followed by strategy for the Software Group (2003–2004), and then information management (2004–2006). She became vice president of Business Process and Architecture Integration (2006–2007) and then headed Enterprise Business Transformation (through April 2011). Before coming to IBM, Ms. Horan was vice president of the Software Group and the AltaVista business unit at Digital Equipment Corporation (DEC; 1994–1998). She was also vice president of Development and Engineering at the Open Software Foundation (1989–1994). Ms. Horan has been a member of the board of directors of MicroVision in Redmond, Washington, since July 2006 and serves on the Audit and Compensation Committees. She is also in great demand as a keynote speaker and expert on corporate IT, CIO strategies and responsibilities, and women in leadership topics.
. _______________ 2 Iris Associates was a software development company founded in late 1984 by Ray Ozzie to build the collaborative “groupware” and e-mail software product known as Lotus Notes. IBM purchased Lotus in 1995. Ghaffari: You made quite a progression from nuts-and-bolts software engineering to strategic software development. How did that transformation happen? Horan: Yes, it's interesting that I started out truly working on the bits and bytes of computers. Then I moved into operating systems and device drivers, which still were close to the hardware. AltaVista and Lotus Notes were more collaborative tools—information resources that allowed for searching and sharing across departments and, ultimately, companies. I definitely started to see possibilities—I think it was the advent of the internet that started me thinking, “Wait a minute. There's a whole new proposition here and some interesting opportunities to explore new areas.” Ghaffari: Tell me how your people management responsibilities grew.
Hacking Exposed: Network Security Secrets and Solutions by Stuart McClure, Joel Scambray, George Kurtz
He said this switch was new to him, and he didn’t know how to turn off the default accounts and passwords. We’d hate to guess how many phone phreaks were salivating over the prospect of making free calls at that organization. Needless to say, you can gain additional insight into the organization and the technical prowess of its staff just by reviewing their postings. Lastly, you can use the advanced searching capabilities of some of the major search engines like AltaVista or Hotbot. These search engines provide a handy facility that allows you to search for all sites that have links back to the target organization’s domain. This may not seem significant at first, but let’s explore the implications. Suppose someone in an organization decides to put up a rogue web site at home or on the target network’s site. This web server may not be secure or sanctioned by the organization.
Sometimes the most outlandish search yields the most productive results. P:\010Comp\Hacking\381-6\ch01.vp Friday, September 07, 2001 10:37:32 AM 7 ProLib8 / Hacking Network Security Color profile: GenericExposed: CMYK printer profile Composite Default screen 8 Secrets and Solutions, Third Edition / McClure, Scambray & Kurtz / 9381-6 / Chapter 1 Hacking Exposed: Network Security Secrets and Solutions Figure 1-1. With the AltaVista search engine, use the link:www.example.com directive to query all sites with links back to the target domain. EDGAR Search For targets that are publicly traded companies, you can consult the Securities and Exchange Commission (SEC) EDGAR database at http://www.sec.gov, as shown in Figure 1-3. One of the biggest problems organizations have is managing their Internet connections, especially when they are actively acquiring or merging with other entities.
Often organizations will scramble to connect the acquired entities to their corporate network with little regard for security. So it is likely that you may be able to find security weaknesses P:\010Comp\Hacking\381-6\ch01.vp Friday, September 07, 2001 10:37:32 AM ProLib8 / Hacking Network Security Color profile: GenericExposed: CMYK printer profile Composite Default screen Secrets and Solutions, Third Edition / McClure, Scambray & Kurtz / 9381-6 / Chapter 1 Chapter 1: Figure 1-2. Footprinting With AltaVista, use the host:example.com directive to query the site for the specified string (for example, “mudge”). in the acquired entity that would allow you to leapfrog into the parent company. Attackers are opportunistic and are likely to take advantage of the chaos that normally comes with combining networks. With an EDGAR search, keep in mind that you are looking for entity names that are different from the parent company.
AltaVista, Ayatollah Khomeini, barriers to entry, bitcoin, Chelsea Manning, Chuck Templeton: OpenTable, clean water, crowdsourcing, cuban missile crisis, data is the new oil, David Graeber, Debian, Edward Snowden, Filter Bubble, Firefox, GnuPG, Google Chrome, Google Glasses, informal economy, Jacob Appelbaum, John Markoff, Julian Assange, Marc Andreessen, market bubble, market design, medical residency, meta analysis, meta-analysis, mutually assured destruction, prediction markets, price discrimination, randomized controlled trial, RFID, Robert Shiller, Ronald Reagan, security theater, Silicon Valley, Silicon Valley startup, Skype, smart meter, Steven Levy, Upton Sinclair, WikiLeaks, Y2K, zero-sum game, Zimmermann PGP
Somehow, with the polka-dot couch, the ducks, the castle, and Weinberg’s auburn hair, I had allowed myself to be lulled into thinking that it was more of a hobby than an actual company. But they appeared to be dead serious. It reminded me of when I was a reporter at the San Francisco Chronicle in the late 1990s. I was dismissive of this newfangled search engine Google. I remember thinking: How could its reliance on machine-based page ranking be better than the hand-curated results on my favorite search engine, AltaVista? Now I was sitting on a polka-dot couch in suburban Philadelphia wondering how a few guys working in a castle could pose a threat to a search engine that pulls in nearly $30 billion a year. And yet, in the technology industry, some of the best ideas sound crazy at first. * * * I really didn’t want to quit using Gmail. Most of my hacker friends used it—even the ones who were paranoid about privacy.
The Internet was brand-new, and the few advertisers buying ads were not worried about targeting—anonymous or not. Most Internet ad buyers were other dot-coms trying to generate buzz for their initial public offerings. Meanwhile, Engage Technologies was at the center of the dot-com hurricane that was about to make landfall. Engage was part of a conglomerate of Internet companies—ranging from search engines AltaVista and Lycos to websites Shopping.com and Furniture.com—that resulted from a buying spree by the entrepreneur David Wetherell. In the fall of 1999, Wetherell appeared on the cover of BusinessWeek under the headline “Internet Evangelist.” His conglomerate, CMGI, was a poster child for the dot-com boom, with a massive stock market value of $10 billion, despite the fact that it was losing $127 million a year on revenues of just $176 million.
Aaronson, Trevor Abdulla, Husain Abdulmutallab, Umar Farouk Abine Abrams, Martin accountability Accurint Acquisti, Alessandro Acxiom Adblock Plus ADFGVX cipher Adium Adler, Jim Adobe Reader AdThis adversary, identifying advertisers and ad-tracking blocking Afghanistan Afifi, Yasir AgileBits Ahmed, Bilal airlines. See also travel airport body scanners Alcoholics Anonymous (AA) Alexander, Keith al-Qaeda AltaVista Al-Wefaq party Amazon American Academy of Pediatrics American Business Information American Civil Liberties Union (ACLU) American Express American Revolution Americans for Democracy and Human Rights Ancestry.com Anderson, Nate Anderson, Ross Andreessen, Marc Android phones AnnualCreditReport.com anonymizing software Anti-Ballistic Missile Treaty (1972) anti-tracking software antivirus software antiwar protests “anxious awareness” AOL Appelbaum, Jacob Apple.
Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins by Garry Kasparov
3D printing, Ada Lovelace, AI winter, Albert Einstein, AltaVista, barriers to entry, Berlin Wall, business process, call centre, clean water, computer age, Daniel Kahneman / Amos Tversky, David Brooks, Donald Trump, Douglas Hofstadter, Drosophila, Elon Musk, Erik Brynjolfsson, factory automation, Freestyle chess, Gödel, Escher, Bach, job automation, Leonard Kleinrock, Mikhail Gorbachev, Nate Silver, Norbert Wiener, packet switching, pattern recognition, Ray Kurzweil, Richard Feynman, Richard Feynman, rising living standards, rolodex, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, Skype, speech recognition, stem cell, Stephen Hawking, Steven Pinker, technological singularity, The Coming Technological Singularity, The Signal and the Noise by Nate Silver, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero-sum game
If I recall correctly, the shouting was being done by Stepan Pachikov, a computer scientist who shared the direction of the computer club with me. His contributions to handwriting recognition software at the Soviet company ParaGraph were used in the Apple Newton. He later moved to Silicon Valley and founded Evernote, the ubiquitous note-taking app. I once made a television commercial for the search engine company AltaVista. If you want to know what happened to AltaVista, you can google it! This fits the axiom of Bill Gates. Bill Gates, The Road Ahead (New York: Viking Penguin, 1995). CHAPTER 4. WHAT MATTERS TO A MACHINE? “I checked it very thoroughly,” said the computer. Douglas Adams, The Hitchhiker’s Guide to the Galaxy (New York: Del Rey, 1995), Kindle edition, locations 2606–14. In my lectures on the human-machine relationship, I’m fond of citing Pablo Picasso.
Far-fetched? Certainly, but I don’t think you have to have my suspicious mind to wonder if lightbulb companies would sell an indestructible and everlasting bulb if they could make one. But resisting change and delaying it to squeeze a few more dollars out of an existing business model usually just makes the inevitable fall all the worse. I once made a television commercial for the search engine company AltaVista in 1999, but that didn’t mean I wanted to follow it to oblivion when the chess equivalent of Google came along. I was in my twenties when the digital information wave rolled over the chess world, and it was a fairly gradual one, not a tsunami. Flicking through games on a screen was far more efficient than on printed materials, a real competitive advantage but not a nuclear bomb. The impact of the Internet a few years later was just as great, dramatically accelerating the information warfare that Grandmasters wage against each other over the board.
Distrust That Particular Flavor by William Gibson
AltaVista, British Empire, cognitive dissonance, cuban missile crisis, edge city, informal economy, means of production, megastructure, pattern recognition, proxy bid, telepresence, Vannevar Bush, Whole Earth Catalog
Is this leisure—this browsing, randomly linking my way through these small patches of virtual real-estate—or do I somehow imagine that I am performing some more dynamic function? The content of the Web aspires to absolute variety. One might find anything there. It is like rummaging in the forefront of the collective global mind. Somewhere, surely, there is a site that contains . . . everything we have lost? The finest and most secret pleasure afforded new users of the Web rests in submitting to the search engine of AltaVista the names of people we may not have spoken aloud in years. Will she be here? Has he survived unto this age? (She isn’t there. Someone with his name has recently posted to a news group concerned with gossip about soap stars.) What is this casting of the nets of identity? Do we engage here in something of a tragic seriousness? In the age of wooden television, media were there to entertain, to sell an advertiser’s product, perhaps to inform.
Today, in its clumsy, larval, curiously innocent way, it offers us the opportunity to waste time, to wander aimlessly, to daydream about the countless other lives, the other people, on the far sides of however many monitors in that postgeographical meta-country we increasingly call home. It will probably evolve into something considerably less random, and less fun—we seem to have a knack for that—but in the meantime, in its gloriously unsorted Global Ham Television Postcard Universes phase, surfing the Web is a procrastinator’s dream. And people who see you doing it might even imagine you’re working. “…the search engine of AltaVista”? Blimey. Spoken from a pre-Google universe. A tender and unformed time indeed. For all of that, though, when I read this now I think that what I should more accurately have called the Web did become what I expected it to. Though in the way of these things, it became so much else as well. I LEARNED OF SCIENCE FICTION and history in a single season. History I found in the basement of an old brick house I happened to pass each day, on my way to elementary school, in a small town in Virginia.
Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier
23andMe, Affordable Care Act / Obamacare, airport security, AltaVista, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, lifelogging, Louis Pasteur, Mark Zuckerberg, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, performance metric, Peter Thiel, Post-materialism, post-materialism, random walk, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, speech recognition, Steve Jobs, Steven Levy, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Watson beat the top human players on Jeopardy!
(This is more important than it may seem: As Google’s spell check continually improved, people stopped bothering to type their searches correctly, since Google could process them well regardless.) Google’s spell-checking system shows that “bad,” “incorrect,” or “defective” data can still be very useful. Interestingly, Google wasn’t the first to have this idea. Around 2000 Yahoo saw the possibility of creating a spell checker from users’ mistyped queries. But the idea never went anywhere. Old search-query data was treated largely as rubbish. Likewise, Infoseek and Alta Vista, earlier popular search engines, each had the world’s most comprehensive database of misspelled words in its day, but they didn’t appreciate the value. Their systems, in a process that was invisible to users, treated typos as “related terms” and performed a search. But it was based on dictionaries that explicitly told the system what was correct, not on the living, breathing sum of user interactions.
VIKTOR MAYER-SCHÖNBERGER KENNETH CUKIER Oxford/London, August 2012 Index abacuses, [>] Accenture, [>], [>] accountability, individual: big data and, [>]–[>], [>] Acxiom, [>], [>] airlines Etzioni analyzes fare pricing patterns, [>]–[>], [>], [>], [>], [>], [>], [>], [>], [>] flight delay predictions, [>]–[>], [>]–[>] AirSage, [>], [>] “algorithmists,” [>]–[>] algorithms, computer, [>]–[>], [>] improvements in, [>]–[>] transparency of, [>] Alta Vista, [>] Amazon, [>], [>], [>], [>], [>], [>], [>] as big-data company, [>] book reviews at, [>]–[>], [>] collaborative filtering at, [>]–[>], [>] data-reuse by, [>], [>] and e-books, [>]–[>] Amazonia (Marcus), [>] ancient world: record-keeping in, [>]–[>] Anderson, Chris: on “end of theory,” [>]–[>] anonymization: big data defeats, [>]–[>], [>] of data, [>], [>]–[>] privacy and, [>]–[>] antitrust regulation: big data and, [>]–[>] AOL: fails to understand data-reuse, [>] releases personal data, [>]–[>] Apple, [>], [>] and cell phone data, [>] Arabic numerals, [>]–[>] Arnold, Thelma, [>]–[>] artificial intelligence: big data and, [>]–[>] at Google, [>] Asthmapolis, [>] astronomy: big data in, [>] automobiles: anti-theft systems, [>] data-gathering by, [>]–[>], [>]–[>], [>], [>], [>]–[>] automobiles, electric: big data and, [>]–[>] IBM and, [>]–[>] automobiles, self-driving, [>], [>], [>], [>] Aviva, [>]–[>] Ayres, Ian: Super Crunchers, [>] Bacon, Francis, [>] Banko, Michele, [>], [>] Barabási, Albert-László, [>]–[>] Barnes & Noble, [>]–[>] Basis, [>] Beane, Billy, [>]–[>] Being Digital (Negroponte), [>] Bell Labs, [>] Berners-Lee, Tim, [>] Bezos, Jeff, [>], [>], [>], [>] big data.
Different: Escaping the Competitive Herd by Youngme Moon
It started innocently enough; I had just purchased a new laptop and a friend of mine told me I needed to download a program cal ed Netscape and use it to get on the internet. “Start by typing in Yahoo!” she told me. Back then we stil used awkward terms like “cyberspace,” “the infobahn,” and “the information superhighway” to refer to the web, and the only way most people knew to get onboard was by using Yahoo! or one of the other portals—AOL, Excite, AltaVista. The funny thing was, none of us were exactly clear on what we were supposed to be doing online; al we knew was that there were swirling currents of information out there and if you wanted to tap into them, you needed a guide, a virtual shepherd if you wil . This is what the search portals provided; they promised to hold our hands as we ventured into this unregulated ocean of content. For me, everything began and ended with Yahoo!
Then weather. Personals. Email. Auctions. And with each new addition to its homepage, a new piece of the internet opened up to me. Games. Online classifieds. A calendar service. Travel information. Every day, a new feature, a new benefit to explore. Job listings. Horoscopes. Entertainment news. This was augmentation-by-addition at the rate of hyperspeed, and because al of the major search portals—Excite, AltaVista, AOL—were caught in the wave, within a few years al of them had evolved into online smorgasbords offering a swol en buffet of information and services: These companies were not just setting the competitive pace for the industry, they were setting the consumption standard for how people accessed information on the web. And if ever there was a time when it would’ve seemed easy to be a prognosticator—that is, easy to predict what the Portal of the Future would look like—this reckoned to be the time, because the evolutionary trajectory of the category couldn’t have appeared more clear.
Founders at Work: Stories of Startups' Early Days by Jessica Livingston
8-hour work day, affirmative action, AltaVista, Apple II, Brewster Kahle, business process, Byte Shop, Danny Hillis, David Heinemeier Hansson, don't be evil, fear of failure, financial independence, Firefox, full text search, game design, Googley, HyperCard, illegal immigration, Internet Archive, Jeff Bezos, Justin.tv, Larry Wall, Maui Hawaii, Menlo Park, nuclear winter, Paul Buchheit, Paul Graham, Peter Thiel, Richard Feynman, Richard Feynman, Robert Metcalfe, Ruby on Rails, 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
Brady: Yes. Strategically, it was spot-on until Google showed up. Because we always thought it was going to be a leapfrogging game. No one is ever going to be able to get so far ahead that we’d ever be in strategic risk of kingmaking a full-text search engine, because you just can’t do that. Google ended up doing exactly that. At the time, until 2000/2001, we had Open Text first, then I think we had AltaVista, then Inktomi. So we just switched off as better technologies became available. We just switched out the old partners with the new ones and always had the best-of-breed search as our falloff. Livingston: Was this invisible to the users? Brady: Yes, it was largely invisible to our users. Even though their brands were there, you came to the front page of Yahoo; you searched; the search result had a Yahoo brand on the upper-left and the technology provider had a smaller brand.
But, as I say, for these people, it depends on their situation if they can take that risk of joining a startup or moving to a new city if they don’t live in the right place. For me, I was actually single at the time, I didn’t have a mortgage, so the idea of joining a little startup that may well be destroyed was just like, “That will be fun.” Because I kind of thought, “Even if Google doesn’t make it, it will be educational and I’ll learn something.” Honestly, I was pretty sure AltaVista was going to destroy Google. Repairing the disk electronics on an early Gmail prototype. C H A P T E 13 R Steve Perlman Cofounder,WebTV One weekend in 1995, Steve Perlman tested his theory that the Web could look as good on a TV screen as it did on a computer monitor. In 3 days of roundthe-clock effort, he built a thin client for surfing the Web, using a television as a display. He invited his friend Bruce Leak over to see what he’d built, and they knew right away it was a big enough idea for a startup.
That required all my spin abilities. Livingston: What did you tell them? Graham: I said that this was part of his graduate student career and that it was a common thing for people in graduate school to take jobs working in research labs during the summer and, yes, this was another company, but it was really more of a research lab than a company. That part was certainly true. When they tried to turn AltaVista into a company, it was disaster. Livingston: What was the next turning point after Robert left for his summer job? Graham: Our main angel investor, the metals trader, was encouraged that the big company had wanted to buy us, so that spring he’d put more money in—still angel-scale money. We weren’t desperately running out of money, but we were going to run out sometime in the fall. The angel investor decided that we needed to have a business guy as CEO and that he wasn’t going to give us any more money unless we got someone.
Utopia Is Creepy: And Other Provocations by Nicholas Carr
Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, Donald Trump, Electric Kool-Aid Acid Test, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator
The impetus, again, seems to be a mix of frustration with Bloglines’s glitches and the availability of a decent and convenient alternative operated by the giant Google. During the 1990s, when the World Wide Web was new, it exerted a strong centrifugal force. It pulled us out of the orbit of big media outlets and sent us skittering to the outskirts of the info-universe. Early web directories like Yahoo and early search engines like AltaVista, whatever their shortcomings (perhaps because of their shortcomings), led us to personal web pages and other small, obscure, and often oddball sources of information. The earliest web loggers, too, took pride in ferreting out and publicizing far-flung sites. And, of course, the big media outlets were slow to move to the web, so their gravitational fields remained weak or nonexistent online. For a time, to bring my metaphor down to earth, the web had no mainstream; there were just brooks and creeks and rills, and the occasional beaver pond.
Abbas ibn Firnas, 329, 341 Abedin, Huma, 315 Abercrombie & Fitch, 244–45 accessibility, 99–100, 199–200, 268 instantaneous, 57, 232, 241, 264, 267 of music, 293 Adams, John, 325 Adderall, 304 Addiction by Design (Schüll), 218–19 Adorno, Theodor, 153–54 advertising, 15, 31, 168, 255, 258, 264 edginess in, 10–11 as pervasive, 64 search-linked, 279–80 in social media, 53–54 in virtual world, 27 see also marketing Advisory Council on the Right to Be Forgotten, 194 AdWords, 279 aesthetic emotions, 249–50 Against Intellectual Monopoly (Levine), 276 Agar, Nicholas, 339 Agarwal, Anant, 133 air disasters, 322–23 Air France Flight 447, 322 Akamai Technologies, 205 “Alastor” (Shelley), 88 Alfred P. Sloan Foundation, 272 algorithms, 113, 136, 145, 167, 174, 190–94, 237, 238, 242, 257, 258 allusion, cultural nuances of, 86–89 alphabet, ideograms vs., 234 Altamont concert, 42 AltaVista, 67 amateurs, 33 creativity of, 49 internet hegemony of, 4–8 media production by, 81 Amazon, 31, 37–38, 92, 142, 256, 277, 288 ambient overload, 90–92 America Online, 279–80 “Amorality of Web 2.0, The” (Carr), xxi–xii Amtrak derailment, 323 analog resources, 148–50 Anders, Günther, 321 Anderson, Chris, 68 Andreessen, Marc, xvii Andrews, James, 134 Android phones, 156, 283 anticonsumerism, 83–85 anxiety, 186, 304 Apple, 125 Apple Corps, 71 Apple II, 76–77 archiving, cultural memory and, 325–28 Arendt, Hannah, 310–11 Aristotle, 174, 307–9 art: allusion in, 89 bundling of musical tracks as, 42–43 by-number, 71–72 digitalization of, 223 emotional response to, 249–50 “free” vs.
3D printing, AltaVista, altcoin, bitcoin, blockchain, buy low sell high, capital controls, cloud computing, corporate governance, crowdsourcing, cryptocurrency, distributed ledger, Edward Snowden, Elon Musk, ethereum blockchain, fiat currency, Firefox, forensic accounting, global village, GnuPG, Google Earth, Haight Ashbury, Jacob Appelbaum, Kevin Kelly, Kickstarter, litecoin, M-Pesa, Marc Andreessen, Marshall McLuhan, Oculus Rift, peer-to-peer, peer-to-peer lending, Ponzi scheme, prediction markets, QR code, ransomware, Satoshi Nakamoto, self-driving car, Skype, smart contracts, Steven Levy, the medium is the message, underbanked, WikiLeaks, Zimmermann PGP
Two years seems like an almost unfathomable amount of time for the people entrenched in it. I preach a bit more patience but the point remains: a lot will be determined by then. Predicting anything is tough with a new technology, because the changes are amplified drastically when the in-hindsight obvious uses are in place. Imagine trying to predict AltaVista, Geocities, and ICQ before web browsers existed, then imagine trying to predict Facebook, Reddit, and Google Earth in 2000 when AltaVista, Geocities, and ICQ were still Internet mainstays. Given that I will likely be wrong at least as often as I am right, what kind of services do I see evolving in a cryptocurrency wonderland? Amazing ones. Altcoins are currently plagued by speculative investing. This drives everything in the space. If the price goes down, the community demands that the developers announce something.
The Industries of the Future by Alec Ross
23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, new economy, offshore financial centre, open economy, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional
Former CEO John Donahoe of eBay, one of the first companies to establish a trust-based commerce network online, said, “I don’t know what Bitcoin will look like ten years from now, but I do think cryptocurrency and digital currency are growing technologies with tremendous potential. There is no reason why you shouldn’t have almost perfectly secure transfer of money with traceability. Cryptocurrency and digital currency are here to stay. And it will get more powerful, not less.” So what will be the future digital currency landscape? When I think of cryptocurrencies, I think of the search engines of the 1990s—WebCrawler, AltaVista, Lycos, Infoseek, Ask Jeeves, MSN Search, Yahoo!—and wonder if there is a Google among them. I think the vast majority of the cryptocurrencies in circulation today will disappear to nothing, but the category will endure. I think that the cryptocurrency that breaks out (whether it is Bitcoin or another) will shed its cryptolibertarian roots and embrace the responsibilities that come with being economically significant.
See also cancer African Robotics Network (AFRON), 21 aging, 19, 26, 63, 214 agriculture: American Civil War and, 7 Argentina and, 223 Belarus and, 208 data and, 178, 181–82 land and, 152, 178, 185 precision agriculture, 161–66, 181, 191–93 Rwanda and, 238 Soviet Union and, 68 Tanzania and, 235 technology and, 3, 5, 160–62 universal machine translation and, 160 Airbnb, 91–97 AIST, 17 Alexander, Keith, 129 Alibaba, 82, 228 AltaVista, 119 Amazon, 4, 31, 48, 90, 93, 98, 157 Andela, 234–35, 239, 248 Andreessen Horowitz, 105, 116, 119, 123, 149, 164 Andreessen, Marc, 103–5, 113–14, 116, 119, 186–87, 195, 204 antidepressants, 53–55. See also mental illnesses Apple, 36, 79, 87 application programming interfaces (APIs), 168 Apps4Africa, 236 Aramco, 122–23, 138, 224 Argentina, 104, 223 ASIMO (Advanced Step in Innovative Mobility robot), 16–17.
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz
affirmative action, AltaVista, Amazon Mechanical Turk, Asian financial crisis, Bernie Sanders, big data - Walmart - Pop Tarts, Cass Sunstein, computer vision, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, desegregation, Donald Trump, Edward Glaeser, Filter Bubble, game design, happiness index / gross national happiness, income inequality, Jeff Bezos, John Snow's cholera map, Mark Zuckerberg, Nate Silver, peer-to-peer lending, Peter Thiel, price discrimination, quantitative hedge fund, Ronald Reagan, Rosa Parks, sentiment analysis, Silicon Valley, statistical model, Steve Jobs, Steven Levy, Steven Pinker, TaskRabbit, The Signal and the Noise by Nate Silver, working poor
Google harnessed Big Data in a way that no other company ever has to build an automated money stream. The company plays a crucial role in this book since Google searches are by far the dominant source of Big Data. But it is important to remember that Google’s success is itself built on the collection of a new kind of data. If you are old enough to have used the internet in the twentieth century, you might remember the various search engines that existed back then—MetaCrawler, Lycos, AltaVista, to name a few. And you might remember that these search engines were, at best, mildly reliable. Sometimes, if you were lucky, they managed to find what you wanted. Often, they would not. If you typed “Bill Clinton” into the most popular search engines in the late 1990s, the top results included a random site that just proclaimed “Bill Clinton Sucks” or a site that featured a bad Clinton joke.
A/B testing ABCs of, 209–21 and addictions, 219–20 and Boston Globe headlines, 214–17 in digital world, 210–19 downside to, 219–21 and education/learning, 276 and Facebook, 211 future uses of, 276, 277, 278 and gaming industry, 220–21 and Google advertising, 217–19 importance of, 214, 217 and Jawbone, 277 and politics, 211–14 and television, 222 Abdulkadiroglu, Atila, 235–36 abortion, truth about, 147–50 Adamic, Lada, 144 Adams, John, 78 addictions and A/B testing, 219–20 See also specific addiction advertising and A/B testing, 217–19 causal effects of, 221–25, 273 and examples of Big Data searches, 22 Google, 217–19 and Levitt-electronics company, 222, 225, 226 and movies, 224–25 and science, 273 and Super Bowl games, 221–26 TV, 221–26 African Americans and Harvard Crimson editorial about Zuckerberg, 155 income and, 175 and origins of notable Americans, 182–83 and truth about hate and prejudice, 129, 134 See also “nigger”; race/racism age and baseball fans, 165–69, 165–66n and lying, 108n and origins of political preferences, 169–71 and predicting future of baseball players, 198–99 of Stormfront members, 137–38 and words as data, 85–86 See also children; teenagers Aiden, Erez, 76–77, 78–79 alcohol as addiction, 219 and health, 207–8 AltaVista (search engine), 60 Alter, Adam, 219–20 Amatriain, Xavier, 157 Amazon, 20, 203, 283 American Pharoah (Horse No. 85), 22, 64, 65, 70–71, 256 Angrist, Joshua, 235–36 anti-Semitism. See Jews anxiety data about, 18 and truth about sex, 123 AOL, and truth about sex, 117–18 AOL News, 143 art, real life as imitating, 190–97 Ashenfelter, Orley, 72–74 Asher, Sam, 202 Asians, and truth about hate and prejudice, 129 asking the right questions, 21–22 assassinations, 227–28 Atlantic magazine, 150–51, 152, 202 Australia, pregnancy in, 189 auto-complete, 110–11, 116 Avatar (movie), 221–22 Bakshy, Eytan, 144 Baltimore Ravens-New England Patriots games, 221, 222–24 baseball and influence of childhood experiences, 165–69, 165–66n, 171, 206 and overemphasis on measurability, 254–55 predicting a player’s future in, 197–200, 200n, 203 and science, 273 scouting for, 254–55 zooming in on, 165–69, 165–66n, 171, 197–200, 200n, 203 basketball pedigrees and, 67 predicting success in, 33–41, 67 and socioeconomic background, 34–41 Beane, Billy, 255 Beethoven, Ludwig von, zooming in on, 190–91 behavioral science, and digital revolution, 276, 279 Belushi, John, 185 Benson, Clark, 217 Berger, Jonah, 91–92 Bezos, Jeff, 203 bias implicit, 134 language as key to understanding, 74–76 omitted-variable, 208 subconscious, 132 See also hate; prejudice; race/racism Big Data and amount of information, 15, 21, 59, 171 and asking the right questions, 21–22 and causality experiments, 54, 240 definition of, 14, 15 and dimensionality, 246–52 and examples of searches, 15–16 and expansion of research methodology, 275–76 and finishing books, 283–84 future of, 279 Google searches as dominant source of, 60 honesty of, 53–54 importance/value of, 17–18, 29–33, 59, 240, 265, 283 limitations of, 20, 245, 254–55, 256 powers of, 15, 17, 22, 53–54, 59, 109, 171, 211, 257 and predicting what people will do in future, 198–200 as revolutionary, 17, 18–22, 30, 62, 76, 256, 274 as right data, 62 skeptics of, 17 and small data, 255–56 subsets in, 54 understanding of, 27–28 See also specific topic Bill & Melinda Gates Foundation, 255 Billings (Montana) Gazette, and words as data, 95 Bing (search engine), and Columbia University-Microsoft pancreatic cancer study, 28, 30 Black, Don, 137 Black Lives Matter, 12 Blink (Gladwell), 29–30 Bloodstock, Incardo, 64 bodies, as data, 62–74 Boehner, John, 160 Booking.com, 265 books conclusions to, 271–72, 279, 280–84 digitalizing, 77, 79 number of people who finish, 283–84 borrowing money, 257–61 Bosh, Chris, 37 Boston Globe, and A/B testing, 214–17 Boston Marathon (2013), 19 Boston Red Sox, 197–200 brain, Minsky study of, 273 Brazil, pregnancy in, 190 breasts, and truth about sex, 125, 126 Brin, Sergey, 60, 61, 62, 103 Britain, pregnancy in, 189 Bronx Science High School (New York City), 232, 237 Buffett, Warren, 239 Bullock, Sandra, 185 Bundy, Ted, 181 Bush, George W., 67 business and comparison shopping, 265 reviews of, 265 See also corporations butt, and truth about sex, 125–26 Calhoun, Jim, 39 Cambridge University, and Microsoft study about IQ of Facebook users, 261 cancer, predicting pancreatic, 28–29, 30 Capital in the 21st Century (Piketty), 283 casinos, and price discrimination, 263–65 causality A/B testing and, 209–21 and advertising, 221–25 and Big Data experiments, 54, 240 college and, 237–39 correlation distinguished from, 221–25 and ethics, 226 and monetary windfalls, 229 natural experiments and, 226–28 and power of Big Data, 54, 211 and randomized controlled experiments, 208–9 reverse, 208 and Stuyvesant High School study, 231–37, 240 Centers for Disease Control and Prevention, 57 Chabris, Christopher, 250 Chance, Zoë, 252–53 Chaplin, Charlie, 19 charitable giving, 106, 109 Chen, M.
Look Evelyn, Duck Dynasty Wiper Blades. We Should Get Them.: A Collection of New Essays by David Thorne
“It wouldn’t cost much,” Geoffrey argued, “we could drive there.” “You mean I could drive there.” Geoffrey didn’t own a car and caught the bus most places. “They have a boat that ferries cars across. It costs... fifty-five dollars per vehicle under two tons. That’s a bargain. How much does your car weigh?” “Why would I know how much my car weighs?” “Right. Hang on,” he typed something into Alta Vista and waited patiently. This was before Google was a thing. Or wi-fi. We had to plug a box into the telephone, run a cable to the computer, edit scripts so they would work with the box, try several different ppp settings, unplug the cables, plug them back in... “We’ve got two flashing green lights on the modem now, what did you do?” “I changed 255.255.182.4 to 255.255.182.5, hang on, I’ll try 255.255.182.6” “Three flashing green lights!”
Frommer's Los Angeles 2010 by Matthew Richard Poole
AltaVista, call centre, car-free, carbon footprint, clean water, Donald Trump, El Camino Real, Frank Gehry, Guggenheim Bilbao, Haight Ashbury, Maui Hawaii, Saturday Night Live, sustainable-tourism, upwardly mobile
Van Ness Ave. Days Inn Hollywood 1 PARK Western Ave. Best Western Hollywood Hills Hotel 5 (HOLLYWOOD FOREVER) Rosewood Ave. The Wilshire Country Club Rossmore Ave. Blvd. CBS Beverly PAN Television PACIFIC City PARK HOLLYWOOD CEMETERY St. Highland Ave. Oakwood Ave. 101 Gower Melrose Ave. Vine St. Rosewood Ave. Romaine St. Willoughby Ave. Wilcox Ave. Sycamore Ave. La Brea Ave. Alta Vista Blvd. Gardner St. Martell Ave. Fairfax Ave. Crescent Heights Blvd. Vine St. Fountain Ave. Sunset Blvd. Gower St. El Centro Ave. DeLongpre Ave. Hollywood Blvd. wy. 1 nset Blvd. Su Cahuenga Blvd. 2 Hol l yw oo dF i 4 Hollywood Blvd. 5 Franklin Ave. 3 Franklin Ave. Western Ave. Information 93 94 renovated with extra-large bathr ooms, dar k-wood platform beds with luxurious F rette linens, and all the latest high-tech accessories.
PARK LA BREA HOLLYWOOD CEMETERY St. Larchmont Blvd. 18 19 101 Rosewood Ave. The Wilshire 9 Sunset Blvd. Gower 17 12 Rossmore Ave. 3rd St. Vine St. 14 Martell Ave. Beverly Blvd. CBS Television PAN PACIFIC City PARK 15 11 Melrose Ave. Gower St. El Centro Ave. Oakwood Ave. Wilcox Ave. Gardner St. Martell Ave. Fairfax Ave. 10 Romaine St. Willoughby Ave. Highland Ave. Sycamore Ave. La Brea Ave. Alta Vista Blvd. Santa Monica Blvd. Rosewood Ave. 16 Vine St. Crescent Heights Blvd. H O L LY W O O D 2 8 7 Fountain Ave. 13 Fw Sunset Blvd. DeLongpre Ave. Franklin Ave. w o Hollywood Blvd. 6 4 lly od i 5 Blvd. 3 Franklin Ave. Western Ave. Rd. Franklin Ave. Hollywood Blvd. 1 2 nset Blvd. Su To Griffith Park 101 uenga Cah on any Blvd. yon Can rel au RUNYON CANYON PARK Highl and Ave.
Freeman House 1 Museum of Television & Radio 17 Grauman’s Chinese Theatre 7 Museum of the American West 5 Griffith Park & Observatory 4 Pacific Design Center 19 Hollywood & Highland 8 Petersen Automotive Museum 22 Hollywood Guinness World of Records 15 Paramount Pictures Studios 25 Hollywood Museum 13 Schindler House 18 HOLLYWOOD Sign 3 Sunset Ranch Hollywood Stables 2 Hollywood Walk of Fame 11 Visitor Information Center Hollywood 9 Ripley’s “Believe It Or Not” Museum 12 7 MUSEUMS & GALLERIES Sa n HANCOCK PARK Blvd. 21 24 22 23 1st St. 1/2 mi 0 Club i Information Beverly Blvd. Country Van Ness Ave. Wilshire Rosewood Ave. The Wilshire 3rd St. PARK LA BREA Western Ave. CBS Beverly Blvd. Television PAN City PACIFIC 20 PARK (HOLLYWOOD FOREVER) 25 Melrose Ave. Highland Ave. Oakwood Ave. HOLLYWOOD CEMETERY Vine St. Rosewood Ave. Romaine St. Willoughby Ave. Wilcox Ave. Gardner St. Martell Ave. 19 Santa Monica Blvd. Sycamore Ave. La Brea Ave. Alta Vista Blvd. 2 101 Gower St. El Centro Ave. H O L LY W O O D Fairfax Ave. 18 Crescent Heights Blvd. 17 Vine St. Fountain Ave. W H AT TO S E E & D O I N LO S A N G E L E S y. Sunset Blvd. lly Fw 11 12 14 15 13 16 od 7 8 10 Hollywood Blvd. nset Blvd. Su 9 6 Cahuenga Blvd. Rd. Franklin Ave. 5 4 2 3 101 Western Ave. on any Blvd. yon Can rel au RUNYON CANYON PARK Hig h L 169 170 Fun Facts L.A.
Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations by Thomas L. Friedman
3D printing, additive manufacturing, affirmative action, Airbnb, AltaVista, Amazon Web Services, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Bob Noyce, business process, call centre, centre right, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, corporate social responsibility, creative destruction, crowdsourcing, David Brooks, demand response, demographic dividend, demographic transition, Deng Xiaoping, Donald Trump, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Ferguson, Missouri, first square of the chessboard / second half of the chessboard, Flash crash, game design, gig economy, global supply chain, illegal immigration, immigration reform, income inequality, indoor plumbing, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the steam engine, inventory management, Irwin Jacobs: Qualcomm, Jeff Bezos, job automation, John Markoff, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, Live Aid, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, mass immigration, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, pattern recognition, planetary scale, pull request, Ralph Waldo Emerson, ransomware, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, South China Sea, Steve Jobs, supercomputer in your pocket, TaskRabbit, Thomas L Friedman, transaction costs, Transnistria, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra, zero-sum game
This is before the Web happened.” When the Web emerged, companies, led by Yahoo, started to organize it for consumers. Yahoo began as a directory of directories. Anytime someone put up a new website, Yahoo would add it to its directory, and then it started breaking websites down into groups—finance, news, sports, business, entertainment, et cetera. “And then search came along,” said Cutting, “and Web search engines, like AltaVista, started cropping up. It had cataloged twenty million Web pages. That was a lot—and for a while it leapfrogged everyone. That was happening around 1995 to ’96. Google showed up shortly thereafter [in 1997] with a small search engine, but claiming much better methods. And gradually it proved itself.” As Google took off, Cutting explained, he wrote an open-source search program in his spare time to compete with Google’s proprietary system.
It was the first phone designed not just to relay text messages, but to combine digital wireless mobile broadband connectivity to the Internet with a touchscreen and an open operating system that eventually ran downloadable apps. Qualcomm later created the first mobile telephone–based app store, called Brew, which was marketed by Verizon in 2001. Paul Jacobs recalls the exact moment when he knew a revolution was about to happen. It was Christmas 1998 and he was sitting on the beach in Maui. “I took out a prototype of the pdQ 1900 they had sent me and I typed in ‘Maui sushi’ into the AltaVista search engine. I was wirelessly connected using Sprint. Up came a sushi restaurant in Maui. I don’t remember the name of the restaurant, but it was good sushi! I knew viscerally right then that what I had theorized—having a phone with the connectivity of a Palm organizer connected to the Internet—would change everything. The day of the disconnected PDA was over. I searched for something I cared about that had nothing to do with technology.
Louis Park Agadez, Niger age of accelerations; dislocation and; education and; human adaptability as challenged by; as inflection point; innovation as response to; leadership and; the Machine and; Moore’s law and; social technologies and agriculture: in Africa and Middle East; climate change and; monocultures vs. polycultures in Airbnb; trust and air-conditioning Aita, Samir algorithms; human oversight and; self-improving Alivio Capital Allen, Paul Allisam, Graham Almaniq, Mati Al Qaeda Al-Shabab AltaVista Amazon (company) Amazon rain forest Amazon Web Services American Civil Liberties Union American Dream American Interest American University of Iraq “America’s New Immigrant Entrepreneurs: Then and Now” (Kauffman Foundation) Amman, Jordan amplifying, as geopolitical policy Andersen, Jeanne Anderson, Chris Anderson, Ross Anderson, Wendell Andreessen, Marc Andrews, Garrett Android AngularJS Annan, Kofi Anthropocene epoch Anthropocene Review anti-Semitism APIs (application programming interfaces) Apple; see also Jobs, Steve Applebaum, Anne Apple Newton Apple Pay apps revolution Arab Awakening Arabic, author’s study of Arab-Muslim world, golden age of Arafat, Yasser architects, software for Armstrong, Neil artificial intelligence (AI); intelligent algorithms and; intelligent assistance and Artnet.com Ashe, Neil Ashraf, Quamrul Assad, Bashar al- Associated Press Astren, Fred AT&T; intelligent assistance and; iPhone gamble of; lifelong learning and; as software company Atkinson, Karen atmosphere: aerosol loading in; CO2 in; ozone layer of ATMs Auguste, Byron Austria Austro-Hungarian Empire Autodesk automation, see computers, computing autonomous systems; see also cars, self-driving Autor, David Avaaz.org Azmar Mountain Bajpai, Aloke Baker, James A., III balance of power Bandar Mahshahr, Iran bandwidth Bangladesh bankruptcy laws bank tellers Barbut, Monique baseball, class-mixing and BASIC Bass, Carl Batman, Turkey BBCNews.com Bee, Samantha Beinhocker, Eric Beirut: civil war in; 1982 Israeli-Palestinian war in Bell, Alexander Graham Bell Labs Bennis, Warren Benyus, Janine Berenberg, Morrie Berenberg, Tess Berkus, Nate Berlin, Isaiah Berlin Wall, fall of Bessen, James Betsiboka River “Better Outcomes Through Radical Inclusion” (Wells) Between Debt and the Devil (Turner) Beykpour, Kayvon Bible Bigbelly garbage cans big data; consumers and; financial services and; software innovation and; supernova and Big Shift Big World, Small Planet (Rockström) “Big Yellow Taxi” (song) Bingham, Marjorie bin Laden, Osama bin Yehia, Abdullah biodiversity: environmental niches and; resilience and biodiversity loss; climate change and biofuels biogeochemical flows biomass fuels biotechnology bioweapons birth control, opposition to Bitcoin black elephants Blase, Bill blockchain technology Bloomberg.com Blumenfeld, Isadore “Kid Cann” Bobby Z (Bobby Rivkin) Bodin, Wes Bohr, Mark Bojia, Ayele Z.
Website Optimization by Andrew B. King
AltaVista, bounce rate, don't be evil, en.wikipedia.org, Firefox, In Cold Blood by Truman Capote, information retrieval, iterative process, medical malpractice, Network effects, performance metric, search engine result page, second-price auction, second-price sealed-bid, semantic web, Silicon Valley, slashdot, social graph, Steve Jobs, web application
. --> </style></head><body> <MTIf name="main_index"> <div class="widget-cloud widget"> <h3 class="widget-header">Tag Cloud</h3> <div class="widget-content"> <ul class="widget-list"> <MTTags limit="20" sort_by="rank"> <li class="rank-<$MTTagRank max="10"$> widget-list-item"><a href="<$MTTagSearchLink$>"><$MTTagName$></a></li> </MTTags> </ul> </div> </div> </MTIf> For more details on using Movable Type, see the documentation at http://www.movabletype.org. Deploy strange attractors A general rule of thumb is that the home page of a website gets the most traffic. There are exceptions, however. You can buck the trend by creating "strange attractors" to generate buzz and, thus, get links. Free online tools can garner a large number of links quickly. Babel Fish, a translator from AltaVista that is available at http://babelfish.altavista.com/, is a good example of a useful free online tool (see Figure 1-19). Figure 1-19. Babel Fish, a free language-translator tool Free web-based tools, Flash configurators (such as a clothes colorizer, or a hotel reservation system/calendar), and Ajax mashups all are elements that wow your audience and provide compelling and useful services that are bound to help.
One Day in December: Celia Sánchez and the Cuban Revolution by Nancy Stout
The owner, Cruz Alonso, was a Spanish refugee who had created a hangout for Latin American revolutionaries and political activists living in exile. This year, she probably returned to Pilón, then took the bus to Santiago, and after she paid for her purchases at two or three factories, arranged to have the toys shipped to Pilón on a boat that took cargo along the coast. Arriving a day or two after New Year’s Day, Celia would likely have stayed the night with her sister Silvia in the fancy Alta Vista neighborhood. When she got home to Pilón, the Servants of Mary wrapped the toys. Elbia recalls, “I remember being on the porch of her house where the gifts were separated and wrapped, each with the name and address of the child. Many times we started this work at night and ended at dawn, tired and satisfied.” Once back in Pilón, she set her sights completely on January 6, when the toys were distributed.
Torres drove to the Moncada and got Pepin released, but Canizares had been tough (according to Sánchez lore) and asked the mayor sarcastically, “What do you think you are doing at Moncada making inquiries about an arrest that is an army affair?” In other words, you might be the mayor of Santiago, but I am head of the entire eastern division of the country. Wasting no time, Canizares informed Mayor Torres that the army had finished their interrogation and were aware that Celia Sánchez had stayed in Pepin’s house at Alta Vista. Furthermore, they knew that Pepin was sending medical supplies to the Sierra Maestra, even though Pepin had denied everything. Still, Canizares said, he would release him. Torres, confused by the about-face, related all this to Silvia, who rejoiced that her husband was free. Three days later, soldiers arrived again. During this search, Silvia got a call from a doctor saying her husband had just been arrested while making a sales call.
Tesla: Man Out of Time by Margaret Cheney
My work will be done late at night when the power load will be least.”26 Curtis, who was associated with the Colorado Springs Electric Company, immediately set to work on the inventor’s problem. His solution would have far-reaching consequences. 13. HURLER OF LIGHTNING Leonard Curtis’s reply from Colorado Springs could not have brought better news: “All things arranged, land will be free. You will live at the Alta Vista Hotel. I have interest in the City Power Plant so electricity is free to you.” Tesla, overjoyed, threw himself into detailed preparations, especially the ordering of machinery that would have to be shipped. Meanwhile, Scherff and his shop assistant, Kolman Czito, were called upon to labor almost around the clock for a major move of laboratory equipment. Of paramount importance was the reorganizing of his finances.
George Scherff was left behind to run the New York laboratory, with precise and lengthy instructions for more equipment to be built, bought, and shipped. Of course Tesla left him with neither adequate money nor a power of attorney to cover the day-to-day expenses. As the inventor saw the matter, when he considered it at all, his staff would soon share in his own wealth and fame. Arriving at Colorado Springs on May 18, he was taken directly to the Alta Vista Hotel. After examining the creaky elevator, he chose room No. 207 (divisible by three and only one flight up), and left instructions for the maid to deliver eighteen clean towels daily. He said he preferred to do his own dusting. The land made available to him was about a mile east of Colorado Springs, in the shadow of Pike’s Peak. Its main use was grazing pasture for the town’s dairy herd. His closest neighbor was to be the Colorado School for the Deaf and Blind, a choice reflecting some discretion.
Hooked: How to Build Habit-Forming Products by Nir Eyal
Airbnb, AltaVista, Cass Sunstein, choice architecture, cognitive bias, cognitive dissonance, en.wikipedia.org, framing effect, game design, Google Glasses, 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, the new new thing, Toyota Production System, Y Combinator
[lxii] To ease the way for link-sharers, Twitter created an embeddable Tweet button for third-party sites, allowing them to offer visitors a one-click way to tweet directly from their pages (figure 9). The external trigger opens a preset message, reducing the cognitive effort of composing the tweet and saving several steps to sharing. Figure 9 Searching with Google Google, the world’s most popular search engine, was not the first to market. It competed against incumbents such as Yahoo!, Lycos, AltaVista, and Excite when it launched in the late 1990s. How did Google come to dominate the multi-billion dollar industry? For one, Google’s PageRank algorithm proved to be a much more effective way to index the web. By ranking pages based on how frequently other sites linked to them, Google improved search relevancy. Compared with directory-based search tools such as Yahoo!, Google was a massive time-saver.
The Internet of Money by Andreas M. Antonopoulos
AltaVista, altcoin, bitcoin, blockchain, clean water, cognitive dissonance, cryptocurrency, ethereum blockchain, financial exclusion, global reserve currency, litecoin, London Interbank Offered Rate, Marc Andreessen, Oculus Rift, packet switching, peer-to-peer lending, Ponzi scheme, QR code, ransomware, reserve currency, Satoshi Nakamoto, self-driving car, Skype, smart contracts, the medium is the message, trade route, underbanked, WikiLeaks, zero-sum game
"In network-centric systems, attacks cause the system to adapt, evolve, and become more resistant." 3.11.1. Attacks Build Resistance I’ve been involved with the internet since 1989. I remember very clearly, in the early days when lots of articles were written about how the internet was not resilient, could not scale to do voice, was not secure. I remember times when denial-of-service attacks would take down Yahoo, AltaVista, and even Google for hours, sometimes days. What happened between then and now? How many times have you seen Google go down in the last five years? Have people stopped attacking Google? Quite the opposite. Google can now sustain gigabits of denial-of-service anywhere in the world and dynamically reroute. The same applies for all internet applications. The attacks didn’t stop. The system became immune because, like a human immune system, if you are exposed to a virus and it doesn’t kill you, you evolve resistance, and the next time you’re exposed to the virus, it does nothing to you.
4chan, Albert Einstein, AltaVista, Andrew Keen, augmented reality, Burning Man, Carrington event, cognitive dissonance, crowdsourcing, dematerialisation, en.wikipedia.org, Filter Bubble, Firefox, Google Glasses, informal economy, information retrieval, invention of movable type, invention of the printing press, invisible hand, James Watt: steam engine, Jaron Lanier, jimmy wales, Kevin Kelly, lifelogging, Loebner Prize, Marshall McLuhan, McMansion, moral panic, Nicholas Carr, pattern recognition, pre–internet, Republic of Letters, Silicon Valley, Skype, Snapchat, social web, Steve Jobs, the medium is the message, The Wisdom of Crowds, Turing test
Clearly we aren’t about to drop such help, especially as the store of human knowledge expands. So what we’re really dealing with is a question of attitude. Has the Internet turned a helpful tactic into a monostrategy? Seife continues: As the Web grew, my browsers began to bloat with bookmarked Web sites. And as search engines matured, I stopped bothering even with bookmarks; I soon relied on AltaVista, HotBot, and then Google to help me find—and recall—ideas. My meta-memories, my pointers to ideas, started being replaced by meta-meta-memories, by pointers to pointers to data. Each day, my brain fills with these quasi-memories, with pointers, and with pointers to pointers to pointers, each one a dusty IOU sitting where a fact or idea should reside. As for me, I’ve grown tired of using a brain that’s full of signposts only, a head full of bookmarks and tags and arrows that direct me to external sources of information but never to the information itself.
Web Scraping With Python: Collecting Data From the Modern Web by Ryan Mitchell
AltaVista, Amazon Web Services, cloud computing, en.wikipedia.org, Firefox, Guido van Rossum, meta analysis, meta-analysis, natural language processing, optical character recognition, random walk, self-driving car, Turing test, web application
If you go to just about any large web‐ 222 | Appendix C: The Legalities and Ethics of Web Scraping site and look for its robots.txt file, you will find it in the root web folder: http:// website.com/robots.txt. The syntax for robots.txt files was developed in 1994 during the initial boom of web search engine technology. It was about this time that search engines scouring the entire Internet, such as AltaVista and DogPile, started competing in earnest with sim‐ ple lists of sites organized by subject, such as the one curated by Yahoo! This growth of search across the Internet meant an explosion in not only the number of web crawlers, but in the availability of information collected by those web crawlers to the average citizen. While we might take this sort of availability for granted today, some webmasters were shocked when information they published deep in the file structure of their website became available on the front page of search results in major search engines.
So You've Been Publicly Shamed by Jon Ronson
4chan, AltaVista, Berlin Wall, Broken windows theory, Burning Man, Clive Stafford Smith, cognitive dissonance, Desert Island Discs, don't be evil, Donald Trump, drone strike, Google Hangouts, illegal immigration, Menlo Park, PageRank, Ralph Nader, Rosa Parks, Silicon Valley, Skype, Steve Jobs, urban planning, WikiLeaks
And now here she was, working with Farukh to reduce herself to safe banalities - to cats and ice cream and Top 40 chart music. We were creating a world where the smartest way to survive is to be bland. * There was a time when Michael Fertik wouldn’t have needed to be so calculating. Back in the mid 1990s search engines were only interested in how many times a particular keyword appeared within a page. To be the number-one Jon Ronson search term on AltaVista or HotBot you just had to write Jon Ronson over and over again. Which for me would be the most fantastic website to chance upon, but for everyone else, less so. But then two students at Stanford, Larry Page and Sergey Brin, had their idea. Why not build a search engine that ranked websites by popularity instead? If someone is linking to your page, that’s one vote. A link, they figured, is like a citation - a nod of respect.
Effective Programming: More Than Writing Code by Jeff Atwood
AltaVista, Amazon Web Services, barriers to entry, cloud computing, endowment effect, Firefox, future of work, game design, Google Chrome, gravity well, job satisfaction, Khan Academy, Kickstarter, loss aversion, Marc Andreessen, Mark Zuckerberg, Merlin Mann, Minecraft, Paul Buchheit, Paul Graham, price anchoring, race to the bottom, recommendation engine, science of happiness, Skype, social software, Steve Jobs, web application, Y Combinator, zero-sum game
Our site was always relatively fast, but even for a historically “fast” site like ours, we realized huge gains in performance from this one simple change. I won’t lie to you. Performance isn’t easy. It’s been a long, hard road getting to where we are now – and we’ve thrown a lot of unicorn dollars toward really nice hardware to run everything on, though I wouldn’t call any of our hardware choices particularly extravagant. And I did follow my own advice, for the record. I distinctly remember switching from AltaVista to Google back in 2000 in no small part because it was blazing fast. To me, performance is a feature, and I simply like using fast websites more than slow websites, so naturally I’m going to build a site that I would want to use. But I think there’s also a lesson to be learned here about the competitive landscape of the public internet, where there are two kinds of websites: the quick and the dead.
The Information: A History, a Theory, a Flood by James Gleick
Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, bank run, bioinformatics, Brownian motion, butterfly effect, citation needed, Claude Shannon: information theory, clockwork universe, computer age, conceptual framework, crowdsourcing, death of newspapers, discovery of DNA, Donald Knuth, double helix, Douglas Hofstadter, en.wikipedia.org, Eratosthenes, Fellow of the Royal Society, Gödel, Escher, Bach, Henri Poincaré, Honoré de Balzac, index card, informal economy, information retrieval, invention of the printing press, invention of writing, Isaac Newton, Jacquard loom, Jacquard loom, Jaron Lanier, jimmy wales, John von Neumann, Joseph-Marie Jacquard, lifelogging, Louis Daguerre, Marshall McLuhan, Menlo Park, microbiome, Milgram experiment, Network effects, New Journalism, Norbert Wiener, On the Economy of Machinery and Manufactures, PageRank, pattern recognition, phenotype, Pierre-Simon Laplace, pre–internet, Ralph Waldo Emerson, RAND corporation, reversible computing, Richard Feynman, Richard Feynman, Rubik’s Cube, Simon Singh, Socratic dialogue, Stephen Hawking, Steven Pinker, stochastic process, talking drums, the High Line, The Wisdom of Crowds, transcontinental railway, Turing machine, Turing test, women in the workforce
Here is how the state of search looked two years later, in 1996. The volume of Internet traffic had grown by a factor of ten each year, from 20 terabytes a month worldwide in 1994 to 200 terabytes a month in 1995, to 2 petabytes in 1996. Software engineers at the Digital Equipment Corporation’s research laboratory in Palo Alto, California, had just opened to the public a new kind of search engine, named AltaVista, continually building and revising an index to every page it could find on the Internet—at that point, tens of millions of them. A search for the phrase truth universally acknowledged and the name Darcy produced four thousand matches. Among them: The complete if not reliable text of Pride and Prejudice, in several versions, stored on computers in Japan, Sweden, and elsewhere, downloadable free or, in one case, for a fee of $2.25.
Aaboe, Asger, 2.1, 2.2 abacus, 4.1, 8.1 A B C Universal Commercial Electric Telegraphic Code, The (Clauson-Thue), 5.1, 5.2 abstraction logic and, 2.1, 2.2 in mathematical computation origins of thinking and words representing, 2.1, 3.1 Adams, Brooks Adams, Frederick Adams, Henry Aeschylus African languages; see also talking drums Aharonov, Dorit Airy, George Biddell “Algebra for Theoretical Genetics, An” (Shannon), 6.1, 6.2, 6.3 algebra of logic, prl.1, 8.1; see also symbolic logic algorithmic information theory, 12.1, 12.2, 12.3, 12.4, 12.5 algorithm(s) to calculate complexity, 12.1, 12.2 to control accuracy and speed of communication, 7.1, 7.2 data compression to describe biological processes, 10.1, 10.2 to generate uninteresting number, 12.1, 12.2 historical evolution of, 2.1, 2.2, 4.1, 7.1 Lovelace’s operations for Analytical Engine as for measurement of computability for measurement of information, 12.1, 12.2, 12.3, 12.4 number tables based on, 4.1, 4.2, 4.3 for proof of number’s randomness, 12.1, 12.2 to reconstruct phylogeny scientific method as, 12.1, 12.2 Shor’s factoring, 13.1, 13.2 Turing machine, 7.1, 7.2 Alice in Wonderland (Carroll) Allen, William alphabet(s) as code evolution of, 2.1, 2.2, 3.1 evolution of telegraph coding systems and, 5.1, 5.2, 5.3, 5.4 information transmission capacity of, 6.1, 7.1 letter frequency in, 1.1, 7.1 Morse code representation of order of letters in, 3.1, 3.2, 3.3 organization of information based on, 3.1, 3.2 AltaVista, epl.1, epl.2 altruism, 10.1, 10.2, 10.3 American Telephone & Telegraph, prl.1, 6.1, 7.1 amino acids, 10.1, 10.2, 10.3, 10.4, 10.5, 10.6 Ampère, André-Marie, 5.1, 5.2 amplitude modulation, 6.1, 6.2, 6.3 analog technology, 8.1, 8.2 Analytical Engine, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.10, 4.11, 4.12, 6.1, 7.1, 8.1 Analytical Society, 4.1, 4.2 Anatomy of Melancholy, The (Burton) Anglo-American Cyclopedia, The (Borges) Anglo-Saxon speech, 3.1, 3.2 anthropocentrism antiaircraft guns and artillery, prl.1, 6.1, 6.2, 7.1, 8.1, 8.2, 8.3, 12.1, 12.2 aperiodic crystals, 9.1, 10.1 Arabic numerals Arcadia (Stoppard), 9.1, 9.2, 14.1 Aristotle and Aristotelian philosophy, prl.1, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 14.1, 14.2 Armani, Giorgio, 14.1, 14.2 Arte of Rhetorique, The (Wilson) artificial intelligence, prl.1, 12.1; see also machines, attribution of thinking to Ashby, W.
Culture works: the political economy of culture by Richard Maxwell
1960s counterculture, AltaVista, Apple's 1984 Super Bowl advert, barriers to entry, Berlin Wall, big-box store, business process, commoditize, corporate governance, cuban missile crisis, deindustrialization, Fall of the Berlin Wall, Francis Fukuyama: the end of history, global village, Howard Rheingold, income inequality, informal economy, intermodal, late capitalism, Marshall McLuhan, medical malpractice, Network effects, profit maximization, Ralph Nader, refrigerator car, Ronald Reagan, Silicon Valley, structural adjustment programs, talking drums, telemarketer, the built environment, Thorstein Veblen, Unsafe at Any Speed, urban renewal, Victor Gruen, Whole Earth Catalog, women in the workforce
The Web’s potential to reduce audiences for television, print, and other traditional media fuels the formation and acquisition of portals by Disney (which owns the Go Network) and General Electric (which owns NBC, the Snap portal, and part of the MSNBC news service). The specter of Web-based software replacing PC and networking operating systems and applications partially drives Microsoft’s move to create its MSN network of sites. The Web’s proven ability to sell computer equipment moves Compaq, a major seller of PCs and installer of Web servers, to buy the Alta Vista portal. Each company can then use its Web presence to cross-promote and sell its other media products, whether these are PCs, software, ﬁlms, television programs, or magazines. Second, within the conﬁnes of the Web itself, portals bring together previously distinct sites and services—news, chat rooms, and so on—to entice users to visit a portal ﬁrst, and stick around longer to buy and form an audience for ads.
Albert Einstein, AltaVista, barriers to entry, Benjamin Mako Hill, c2.com, Cass Sunstein, citation needed, crowdsourcing, Debian, en.wikipedia.org, Firefox, Hacker Ethic, HyperCard, index card, Jane Jacobs, Jason Scott: textfiles.com, jimmy wales, Marshall McLuhan, Network effects, optical character recognition, Ralph Waldo Emerson, Richard Stallman, side project, Silicon Valley, Skype, slashdot, social software, Steve Jobs, The Death and Life of Great American Cities, The Wisdom of Crowds, urban planning, urban renewal, Vannevar Bush, wikimedia commons, Y2K
Looking at tens of thousands of dollars to get advertising in subways and other venues, they realized that this wasn’t going to be a cost-effective model either. Rather than stick to one business idea, Wales and Shell wanted to keep the firm experimental. There were no proven business models for the Internet then, and they wanted to stay nimble. “Learning from mistakes was the fun part,” says Shell. They started to see what was getting attention—Yahoo!, AltaVista, and Excite were the search engines of the time and were gathering lots of momentum. (It would be a few years before the Google juggernaut would be part of the scene.) It was increasingly clear that transaction services were complex—delivery of goods and handling customer service made such a business hard to start up or scale up. Directory services were much cheaper. Put listings online, and if people found it useful they would return.
A Declaration of the Independence of Cyberspace, Albert Einstein, AltaVista, Amazon Mechanical Turk, Asperger Syndrome, availability heuristic, Benoit Mandelbrot, biofilm, Black Swan, British Empire, conceptual framework, corporate governance, Danny Hillis, Douglas Engelbart, Douglas Engelbart, Emanuel Derman, epigenetics, Flynn Effect, Frank Gehry, Google Earth, hive mind, Howard Rheingold, index card, information retrieval, Internet Archive, invention of writing, Jane Jacobs, Jaron Lanier, John Markoff, Kevin Kelly, lifelogging, lone genius, loss aversion, mandelbrot fractal, Marc Andreessen, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, New Journalism, Nicholas Carr, out of africa, Paul Samuelson, peer-to-peer, Ponzi scheme, pre–internet, Richard Feynman, Richard Feynman, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, slashdot, smart grid, social graph, social software, social web, Stephen Hawking, Steve Wozniak, Steven Pinker, Stewart Brand, Ted Nelson, telepresence, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, trade route, upwardly mobile, Vernor Vinge, Whole Earth Catalog, X Prize
Instead of trying to memorize a passage in the book or remember an important statistic, I took an easier path, storing the location of the desirable memory instead of the memory itself. Every dog-ear is a meta-memory, a pointer to an idea I wanted to retain but was too lazy to memorize. The Internet turned an occasional habit into my primary way of storing knowledge. As the Web grew, my browsers began to bloat with bookmarked Websites. And as search engines matured, I stopped bothering even with bookmarks; I soon relied on AltaVista, HotBot, and then Google to help me find—and recall—ideas. My meta- memories, my pointers to ideas, started being replaced by meta-meta-memories, by pointers to pointers to data. Each day, my brain fills with these quasi-memories, with pointers, and with pointers to pointers, each one a dusty IOU sitting where a fact or idea should reside. Now when I expend the effort to squirrel memories away, I store them in the clutter of my hard drive as much as in the labyrinth of my brain.
The Internet Is Not the Answer by Andrew Keen
3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator
This prodigious growth of sites, pages, and hyperlinks was central to Page and Brin’s project and it’s why they named their search engine Google—Sergey Brin’s unintentional misspelling of the word googol, a mathematical term signifying the number1.0 × 10100, which has come to mean an unimaginably large number. What if all the content on the Web, all those 26 million pages with their hundreds of millions of hyperlinks, could be sorted and indexed? Page and Brin wondered. What if Google could organize all the world’s digital information? There already were technologies from well-funded startups like Lycos, AltaVista, Excite, and Yahoo, vying to build a winner-take-all search engine for navigating the Web. But Brin and Page beat them all to it with an astonishingly original method for determining the relevance and reliability of a Web page’s content. Just as Vannevar Bush’s Memex worked through an intricate system of “trails,” Page and Brin saw the logic of the Web in terms of hyperlinks. By crawling the entire Web and indexing all its pages and links, they turned the Web into what Brin, a National Science Foundation fellow at Stanford, identified as “a big equation.”
Social Life of Information by John Seely Brown, Paul Duguid
AltaVista, business process, Claude Shannon: information theory, computer age, cross-subsidies, disintermediation, double entry bookkeeping, Frank Gehry, frictionless, frictionless market, future of work, George Gilder, George Santayana, global village, Howard Rheingold, informal economy, information retrieval, invisible hand, Isaac Newton, John Markoff, Just-in-time delivery, Kenneth Arrow, Kevin Kelly, knowledge economy, knowledge worker, loose coupling, Marshall McLuhan, medical malpractice, moral hazard, Network effects, new economy, Productivity paradox, Robert Metcalfe, rolodex, Ronald Coase, shareholder value, Shoshana Zuboff, Silicon Valley, Steve Jobs, Superbowl ad, Ted Nelson, telepresence, the medium is the message, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, Turing test, Vannevar Bush, Y2K
So bots offer an interesting way to evaluate some of the endisms threatened by information technology. These agents are not just the dream of eager futurists. Many are already hard at work. Without them the Internet, which has grown so dramatically in the past few years, would by now be unmanageable. Diligent agents that endlessly catalogue the World Wide Web for such familiar services as Yahoo!, Lycos, Excite, and Alta Vista have helped to manage it. As a result, you can find needles of information in the Web's vast haystack and order in the midst of its apparent chaos. Indeed, it was the search-and-catalogue capability of their agents that principally transformed these sites from mere search engines into lucrative portalspoints where people plan and begin their voyages on the 'Net (and so points of great interest to advertisers).
The Wisdom of Crowds by James Surowiecki
AltaVista, Andrei Shleifer, asset allocation, Cass Sunstein, Daniel Kahneman / Amos Tversky, experimental economics, Frederick Winslow Taylor, George Akerlof, Howard Rheingold, I think there is a world market for maybe five computers, interchangeable parts, Jeff Bezos, John Meriwether, Joseph Schumpeter, knowledge economy, lone genius, Long Term Capital Management, market bubble, market clearing, market design, moral hazard, Myron Scholes, new economy, offshore financial centre, Picturephone, prediction markets, profit maximization, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Toyota Production System, transaction costs, ultimatum game, Yogi Berra, zero-sum game
But if possible, it’s worth letting yourself be a little amazed at what happened during those routine searches. Each time, Google surveyed billions of Web pages and picked exactly the pages that I would find most useful. The cumulative time for all the searches: about a minute and a half. Google started in 1998, at a time when Yahoo! seemed to have a stranglehold on the search business—and if Yahoo! stumbled, then AltaVista or Lycos looked certain to be the last man standing. But within a couple of years, Google had become the default search engine for anyone who used the Internet regularly, simply because it was able to do a better job of finding the right page quickly. And the way it does that—and does it while surveying three billion Web pages—is built on the wisdom of crowds. Google keeps the details of its technology to itself, but the core of the Google system is the PageRank algorithm, which was first defined by the company’s founders, Sergey Brin and Lawrence Page, in a now-legendary 1998 paper called “The Anatomy of a Large-Scale Hypertextual Web Search Engine.”
Tcl/Tk in a Nutshell by Paul Raines, Jeff Tranter
This chapter is designed to help new Tcl programmers better understand the Tcl language, especially when written code does not perform as expected or produces errors. Much of the material in this chapter was selected from postings to the Usenet newsgroup comp.lang.tcl. Beginning programmers often seek help with coding problems, and suggested answers are given. These postings, along with the author's personal experiences, are presented here. Note Web addresses change over time. Use web search engines such as Yahoo!, AltaVista, Infoseek, and HotBot to help locate the Tcl FAQs if the links noted are out of date. Other excellent sources of "how to" material available on the Web include these: The Tcl Frequently Asked Questions (FAQ), by Larry Virden This is an up-to-date, comprehensive list of frequently asked questions and answers—well worth reading. See http://www.teraform.com/˜lvirden/tcl-faq/. Tcl Usage FAQ, by Joe Moss This covers specific Tcl language usage questions and answers.
23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, augmented reality, Benjamin Mako Hill, Black Swan, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, congestion charging, disintermediation, drone strike, Edward Snowden, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, hindsight bias, informal economy, Internet Archive, Internet of things, Jacob Appelbaum, Jaron Lanier, John Markoff, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, linked data, Lyft, Mark Zuckerberg, moral panic, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, recommendation engine, RFID, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, urban planning, WikiLeaks, zero day
In their early days: Paddy Kamen (5 Jul 2001), “So you thought search engines offer up neutral results? Think again,” Toronto Star, http://www.commercialalert.org/issues/culture/search-engines/so-you-thought-search-engines-offer-up-neutral-results-think-again. search engines visually differentiated: Gary Ruskin (16 Jul 2001), Letter to Donald Clark, US Federal Trade Commission, re: Deceptive advertising complaint against AltaVista Co., AOL Time Warner Inc., Direct Hit Technologies, iWon Inc., LookSmart Ltd., Microsoft Corp. and Terra Lycos S.A., Commercial Alert, http://www.commercialalert.org/PDFs/SearchEngines.pdf. Heather Hippsley (27 Jun 2002), Letter to Gary Ruskin re: Complaint requesting investigation of various Internet search engine companies for paid placement and paid inclusion programs, US Federal Trade Commission, http://www.ftc.gov/sites/default/files/documents/closing_letters/commercial-alert-response-letter/commercialalertletter.pdf.
The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone
3D printing, airport security, AltaVista, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, call centre, centre right, Chuck Templeton: OpenTable, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, Douglas Hofstadter, Elon Musk, facts on the ground, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, Kevin Kelly, Kodak vs Instagram, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Network effects, new economy, optical character recognition, pets.com, Ponzi scheme, quantitative hedge fund, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas L Friedman, Tony Hsieh, Whole Earth Catalog, why are manhole covers round?, zero-sum game
Bezos cautiously told Wired that Search Inside the Book could indeed be such a beginning. “You have to start somewhere,” he said. “You climb the top of the first tiny hill and from there you see the next hill.”3 As Amazon was adding product categories throughout the 1990s, its executives came to an inevitable conclusion: the company had to become good at product search. Early in its history, Amazon had licensed a now-defunct search engine called Alta Vista, a spinoff of computer maker Digital Equipment Corp., but it had quickly proved insufficient. In the late 1990s, Amazon engineers Dwayne Bowman and Ruben Ortega led the development of an internal product-search tool called Botega (a mash-up of their surnames) that capitalized on Amazon’s vast trove of customer data, information the website had been collecting from the moment it officially opened for business.
Albert Einstein, AltaVista, British Empire, Cass Sunstein, cognitive dissonance, correlation does not imply causation, Daniel Kahneman / Amos Tversky, en.wikipedia.org, illegal immigration, index card, Isaac Newton, loss aversion, meta analysis, meta-analysis, mouse model, neurotypical, pattern recognition, placebo effect, Richard Thaler, Saturday Night Live, selection bias, Solar eclipse in 1919, Stephen Hawking, Steven Pinker, the scientific method, Thomas Kuhn: the structure of scientific revolutions
, CAN and NAAR aimed to be more than traditional advocacy organizations: They wanted to shape the direction and scope of biomedical research on autism spectrum disorders by conceiving of, planning, and funding projects on their own. Instead of reading through old textbooks and hunting for journal articles as Rimland had done, this second generation of autism advocates used the Internet to access cutting-edge research: Thanks to service providers like America Online and search engines like Alta Vista, information that had previously been available only to the select few was in wide circulation. When she started CAN, Iversen was so inept at using a computer that she had to pay someone to come to her house and help her download files. At the time, the only noteworthy repository for scientific research papers available to laypeople was a collection of medical literature maintained by the National Institutes of Health’s (NIH) National Library of Medicine.32 Then, seemingly overnight, Iversen said, “all these incredible medical databases suddenly became free.”
The Future of Ideas: The Fate of the Commons in a Connected World by Lawrence Lessig
AltaVista, Andy Kessler, barriers to entry, business process, Cass Sunstein, commoditize, computer age, creative destruction, dark matter, disintermediation, Donald Davies, Erik Brynjolfsson, George Gilder, Hacker Ethic, Hedy Lamarr / George Antheil, Howard Rheingold, Hush-A-Phone, HyperCard, hypertext link, Innovator's Dilemma, invention of hypertext, inventory management, invisible hand, Jean Tirole, Jeff Bezos, Joseph Schumpeter, Kenneth Arrow, Larry Wall, Leonard Kleinrock, linked data, Marc Andreessen, Menlo Park, Network effects, new economy, packet switching, peer-to-peer, peer-to-peer model, price mechanism, profit maximization, RAND corporation, rent control, rent-seeking, RFC: Request For Comment, Richard Stallman, Richard Thaler, Robert Bork, Ronald Coase, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, smart grid, software patent, spectrum auction, Steve Crocker, Steven Levy, Stewart Brand, Ted Nelson, Telecommunications Act of 1996, The Chicago School, transaction costs, zero-sum game
., 35. 51 McChesney, 80, 179. 52 Ibid., 250. 53 Ibid., 148. 54 Ibid., 168. CHAPTER 8 1 See Lawrence Lessig, Code and Other Laws of Cyberspace (New York: Basic Books, 1999). 2 For examples of on-line mapping services, see MapQuest.com at http://www. mapquest.com; Maps On Us at http://www.mapsonus.com; and MapBlast! at http://www. mapblast.com. 3 For examples of on-line translation Web sites, see AltaVista World/Translate at http://world.altavista.com; FreeTranslation.com at http://www.freetranslation.com; and From Language to Language at http://www.langtolang.com. 4 A short list of many examples of on-line dictionaries includes Merriam-Webster OnLine at http://www.m-w.com; Cambridge Dictionaries Online at http://dictionary. cambridge.org; and AllWords.com at http://www.allwords.com. There are also sites that perform aggregate searches through multiple multilingual dictionaries, such as yourDictionary.com at http://www.yourdictionary.com. 5 As we'll see in chapter 11, this is not a slight constraint.
Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance by Ian Goldin, Chris Kutarna
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Airbnb, Albert Einstein, AltaVista, Asian financial crisis, asset-backed security, autonomous vehicles, banking crisis, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, bitcoin, Bonfire of the Vanities, clean water, collective bargaining, Colonization of Mars, Credit Default Swap, crowdsourcing, cryptocurrency, Dava Sobel, demographic dividend, Deng Xiaoping, Doha Development Round, double helix, Edward Snowden, Elon Musk, en.wikipedia.org, epigenetics, experimental economics, failed state, Fall of the Berlin Wall, financial innovation, full employment, Galaxy Zoo, global supply chain, Hyperloop, immigration reform, income inequality, indoor plumbing, industrial cluster, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invention of the printing press, Isaac Newton, Islamic Golden Age, Khan Academy, Kickstarter, labour market flexibility, low cost carrier, low skilled workers, Lyft, Malacca Straits, mass immigration, megacity, Mikhail Gorbachev, moral hazard, Network effects, New Urbanism, non-tariff barriers, Occupy movement, On the Revolutions of the Heavenly Spheres, open economy, Panamax, Pearl River Delta, personalized medicine, Peter Thiel, post-Panamax, profit motive, rent-seeking, reshoring, Robert Gordon, Robert Metcalfe, Search for Extraterrestrial Intelligence, Second Machine Age, self-driving car, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart grid, Snapchat, special economic zone, spice trade, statistical model, Stephen Hawking, Steve Jobs, Stuxnet, TaskRabbit, The Future of Employment, too big to fail, trade liberalization, trade route, transaction costs, transatlantic slave trade, uranium enrichment, We are the 99%, We wanted flying cars, instead we got 140 characters, working poor, working-age population, zero day
To translate just one sliver, the full English edition of Wikipedia, into just one other major language would cost at least $100 million and take over 10,000 person-years.20 Even if someone were willing to pay for it, there may not be enough translators living to make the attempt, depending on the destination language. Computer-driven translation engines can automate the task somewhat; they can often give us the gist of what a foreign utterance means. But as users of every engine from the 1990s’ AltaVista Babelfish to today’s Google Translate can attest, much meaning, most clarity and all style are still lost in translation. That’s because whereas human translators start by recognizing the whole meaning of the source and then try to express it faithfully in destination-language terms, computers start by recognizing individual words—or at best, phrases—and then stitch together foreign analogs with no conception of the overall result.
The Upstarts: How Uber, Airbnb, and the Killer Companies of the New Silicon Valley Are Changing the World by Brad Stone
Affordable Care Act / Obamacare, Airbnb, AltaVista, Amazon Web Services, Andy Kessler, autonomous vehicles, Burning Man, call centre, Chuck Templeton: OpenTable, collaborative consumption, East Village, fixed income, Google X / Alphabet X, housing crisis, inflight wifi, Jeff Bezos, Justin.tv, Kickstarter, Lyft, Marc Andreessen, Mark Zuckerberg, Menlo Park, Necker cube, obamacare, Paul Graham, peer-to-peer, Peter Thiel, race to the bottom, rent control, ride hailing / ride sharing, Ruby on Rails, Sand Hill Road, self-driving car, semantic web, sharing economy, side project, Silicon Valley, Silicon Valley startup, Skype, South of Market, San Francisco, Startup school, Steve Jobs, TaskRabbit, Tony Hsieh, transportation-network company, Uber and Lyft, Uber for X, Y Combinator, Y2K, Zipcar
Though Seamless Wheels was short-lived, it demonstrated an incontrovertible fact: ordering cabs and submitting those tiny paper receipts for reimbursement was an expensive, time-consuming scourge in the business world and an obvious problem that technology could solve. Others noticed this as well, and in 2007, a wealthy Virginia businessman named Tom DePasquale decided to do something about it. His company was called Taxi Magic. Just as the search engine Alta Vista preceded Google, and Myspace dominated before Facebook, Taxi Magic would become the highest-profile precursor to Uber; the company was the first to seize, and squander, the opportunity to revolutionize the taxi industry. In the late 1990s, DePasquale had founded a company called Outtask that made an online tool, Cliqbook, that allowed workers to book and manage their online air travel. In 2006, Concur, one of the most popular makers of expense-account software, acquired Outtask.
Write Great Code, Volume 1 by Randall Hyde
The SCSI command set is very powerful, and it is designed for high-performance applications. It is sufficiently large and complex that space limitations prevent its inclusion here. Readers interested in a deeper look at SCSI programming should refer to The Book of SCSI (by Gary Field, Peter M. Ridge, et al., published by No Starch Press). The complete SCSI specifications appear at various sites on the Web. A quick search for “SCSI specifications” on AltaVista, Google, or any other decent Web search engine should turn up several copies of the specifications. 12.20 The IDE/ATA Interface Although the SCSI interface is very high performance, it is also expensive. A SCSI device requires a sophisticated and fast processor in order to handle all the operations that are possible on the SCSI bus. Furthermore, because SCSI devices can operate on a peer-to-peer basis (that is, one peripheral may talk to another without intervention from a host computer system), each SCSI device must carry around a considerable amount of sophisticated software in ROM on the device’s controller board.