From Stephen Levy—the author who made "hackers" a household word—comes this account of a revolution that is already affecting every citizen in the twenty-first century. Crypto tells the inside story of how a group of "crypto rebels"—nerds and visionaries turned freedom fighters—teamed up with corporate interests to beat Big Brother and ensure our privacy on the Internet. Levy's history of one of the most controversial and important topics of the digital age reads like the best futuristic fiction.

    They're burning through cash, sales have stalled, and investors are nowhere to be found. Welcome to the reality of the new tech boom. Sure, it has produced its glittering share of billion-dollar "exits." But for the vast majority of startups life is nasty, brutish, and short on glamour. NO EXIT explores the feverish world of company founders who are desperately trying to keep their dream afloat. It’s a harrowing and hilarious look at the Silicon Valley no one sees. This is an extended version of a story that appears in the May 2014 issue of WIRED magazine.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    But all too often, these numbers are wrong. This book is a lively guide to spotting bad statistics and learning to think critically about these influential numbers. Damned Lies and Statistics is essential reading for everyone who reads or listens to the news, for students, and for anyone who relies on statistical information to understand social problems.Joel Best bases his discussion on a wide assortment of intriguing contemporary issues that have garnered much recent media attention, including abortion, cyberporn, homelessness, the Million Man March, teen suicide, the U.S. census, and much more. Using examples from the New York Times, the Washington Post, and other major newspapers and television programs, he unravels many fascinating examples of the use, misuse, and abuse of statistical information.In this book Best shows us exactly how and why bad statistics emerge, spread, and come to shape policy debates. He recommends specific ways to detect bad statistics, and shows how to think more critically about "stat wars," or disputes over social statistics among various experts. Understanding this book does not require sophisticated mathematical knowledge; Best discusses the most basic and most easily understood forms of statistics, such as percentages, averages, and rates.This accessible book provides an alternative to either naively accepting the statistics we hear or cynically assuming that all numbers are meaningless. It shows how anyone can become a more intelligent, critical, and empowered consumer of the statistics that inundate both the social sciences and our media-saturated lives.

    His writing is as much art as it is science. He is the most viable system I know." Dr Russell L Ackoff, The Institute for Interactive Management, Pennsylvania, USA. "If anyone can make it [Operations Research] understandably readable and positively interesting it is Stafford Beer everyone in management should be grateful to him for using clear and at times elegant English and even elegant diagrams." The Economist Based on the Massey Lectures, this book examines the reasons why the institutions of our society may well be failing, and opens a discussion as to what could be done. Drawing on the science of effective organization, which is his definition of cybernetics, Stafford Beer explains key cybernetic principles in words and pictures that all can understand. He concludes that our society commits more and more resources to plastering over the cracks in the system which simply reappear while freedom itself is increasingly eroded. The institutions must be redesigned, and returned to the people, to whom the scientific tools for doing this ought to belong.

    Genes are important, but only as part of a process constrained by environment, physical laws, and the universal tendencies of complex adaptive systems. In a new preface for this edition, Goodwin reflects on the advances in both genetics and the sciences of complexity since the book's original publication.

    Accepting the increasingly widespread belief that industrialized culture inevitably erodes the natural world, Endgame sets out to explore how this relationship impels us towards a revolutionary and as-yet undiscovered shift in strategy. Building on a series of simple but increasingly provocative premises, Jensen leaves us hoping for what may be inevitable: a return to agrarian communal life via the disintegration of civilization itself.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Though the answers may seem simple, their profound implications make the prisoner's dilemma one of the great unifying concepts of science. Watching players bluff in a poker game inspired John von Neumann--father of the modern computer and one of the sharpest minds of the century--to construct game theory, a mathematical study of conflict and deception. Game theory was readily embraced at the RAND Corporation, the archetypical think tank charged with formulating military strategy for the atomic age, and in 1950 two RAND scientists made a momentous discovery.Called the prisoner's dilemma, it is a disturbing and mind-bending game where two or more people may betray the common good for individual gain. Introduced shortly after the Soviet Union acquired the atomic bomb, the prisoner's dilemma quickly became a popular allegory of the nuclear arms race. Intellectuals such as von Neumann and Bertrand Russell joined military and political leaders in rallying to the preventive war movement, which advocated a nuclear first strike against the Soviet Union. Though the Truman administration rejected preventive war the United States entered into an arms race with the Soviets and game theory developed into a controversial tool of public policy--alternately accused of justifying arms races and touted as the only hope of preventing them.A masterful work of science writing, Prisoner's Dilemma weaves together a biography of the brilliant and tragic von Neumann, a history of pivotal phases of the cold war, and an investigation of game theory's far-reaching influence on public policy today. Most important, Prisoner's Dilemma is the incisive story of a revolutionary idea that has been hailed as a landmark of twentieth-century thought.

    

    Our eyes play tricks on us; our stories change in the retelling; and most of us are fairly sure we’re way above average. In Why We Make Mistakes, journalist Joseph T. Hallinan sets out to explore the science of human error—how we think, see, remember, and forget, and how this sets us up for wholly irresistible mistakes.In his quest to understand our imperfections, Hallinan delves into psychology, neuroscience, and economics, with forays into aviation, consumer behavior, geography, football, stock picking, and more. He discovers that some of the same qualities that make us efficient also make us error prone. Why We Make Mistakes is enlivened by real-life stories--of weathermen whose predictions are uncannily accurate and a witness who sent an innocent man to jail--and offers valuable advice, such as how to remember where you’ve hidden something important. He explains why multitasking is a bad idea, why men make errors women don’t. This book will open your eyes to the reasons behind your mistakes and have you vowing to do better the next time.

    Roads bind our world--metaphorically and literally--transforming landscapes and the lives of the people who inhabit them. Roads have unparalleled power to impact communities, unite worlds and sunder them, and reveal the hopes and fears of those who travel them. With his marvelous eye for detail and his contagious enthusiasm, Ted Conover explores six of these key byways worldwide. In Peru, he traces the journey of a load of rare mahogany over the Andes to its origin, an untracked part of the Amazon basin soon to be traversed by a new east-west route across South America. In East Africa, he visits truckers whose travels have been linked to the worldwide spread of AIDS. In the West Bank, he monitors highway checkpoints with Israeli soldiers and then passes through them with Palestinians, witnessing the injustices and danger borne by both sides. He shuffles down a frozen riverbed with teenagers escaping their Himalayan valley to see how a new road will affect the now-isolated Indian region of Ladakh. From the passenger seat of a new Hyundai piling up the miles, he describes the exuberant upsurge in car culture as highways proliferate across China. And from inside an ambulance, he offers an apocalyptic but precise vision of Lagos, Nigeria, where congestion and chaos on freeways signal the rise of the global megacity. A spirited, urgent book that reveals the costs and benefits of being connected--how, from ancient Rome to the present, roads have played a crucial role in human life, advancing civilization even as they set it back.

    Huge commercial databases track your finances and sell that information to anyone willing to pay. Host sites on the World Wide Web record every page you view, and “smart” toll roads know where you drive. Every day, new technology nibbles at our privacy. Does that make you nervous?David Brin is worried, but not just about privacy. He fears that society will overreact to these technologies by restricting the flow of information, frantically enforcing a reign of secrecy. Such measures, he warns, won’t really preserve our privacy. Governments, the wealthy, criminals, and the techno-elite will still find ways to watch us. But we’ll have fewer ways to watch them. We’ll lose the key to a free society: accountability.The Transparent Society is a call for “reciprocal transparency.” If police cameras watch us, shouldn’t we be able to watch police stations? If credit bureaus sell our data, shouldn't we know who buys it? Rather than cling to an illusion of anonymity - a historical anomaly, given our origins in close-knit villages - we should focus on guarding the most important forms of privacy and preserving mutual accountability. The biggest threat to our freedom, Brin warns, is that surveillance technology will be used by too few people, now by too many.A society of glass houses may seem too fragile. Fearing technology-aided crime, governments seek to restrict online anonymity; fearing technology-aided tyranny, citizens call for encrypting all data. Brins shows how, contrary to both approaches, windows offer us much better protection than walls; after all, the strongest deterrent against snooping has always been the fear of being spotted. Furthermore, Brin argues, Western culture now encourages eccentricity - we’re programmed to rebel! That gives our society a natural protection against error and wrong-doing, like a body’s immune system. But “social T-cells” need openness to spot trouble and get the word out.The Transparent Society is full of such provocative and far-reaching analysis. The inescapable rush of technology is forcing us to make new choices about how we want to live. This daring book reminds us that an open society is more robust and flexible than one where secrecy reigns. In an era of gnat-sized cameras, universal databases, and clothes-penetrating radar, it will be more vital than ever for us to be able to watch the watchers. With reciprocal transparency we can detect dangers early and expose wrong-doers. We can gauge the credibility of pundits and politicians. We can share technological advances and news. But all of these benefits depend on the free, two-way flow of information.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases