will mean for us, it also forces readers to challenge their preconceptions. And it manages to do all this in a way that is both entertaining and engaging.” —The New York Times As we approach a great turning point in history when technology is poised to redefine what it means to be human, The Fourth Age offers fascinating insight into AI, robotics, and their extraordinary implications for our species.In The Fourth Age, Byron Reese makes the case that technology has reshaped humanity just three times in history: - 100,000 years ago, we harnessed fire, which led to language. - 10,000 years ago, we developed agriculture, which led to cities and warfare. - 5,000 years ago, we invented the wheel and writing, which lead to the nation state. We are now on the doorstep of a fourth change brought about by two technologies: AI and robotics. The Fourth Age provides extraordinary background information on how we got to this point, and how—rather than what—we should think about the topics we’ll soon all be facing: machine consciousness, automation, employment, creative computers, radical life extension, artificial life, AI ethics, the future of warfare, superintelligence, and the implications of extreme prosperity. By asking questions like “Are you a machine?” and “Could a computer feel anything?”, Reese leads you through a discussion along the cutting edge in robotics and AI, and, provides a framework by which we can all understand, discuss, and act on the issues of the Fourth Age, and how they’ll transform humanity.

    Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer winning in games like Jeopardy and go does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules. These approaches are too narrow to achieve genuine intelligence. The world we live in is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Marcus and Davis show us what we need to first accomplish before we get there and argue that if we are wise along the way, we won't need to worry about a future of machine overlords. If we heed their advice, humanity can create an AI that we can trust in our homes, our cars, and our doctor's offices. Reboot provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of what we can achieve and how AI can make our lives better.

    Then, attempting to break a Nazi code during World War II, he successfully designed and built one, thus ensuring the Allied victory. Turing became a champion of artificial intelligence, but his work was cut short. As an openly gay man at a time when homosexuality was illegal in England, he was convicted and forced to undergo a humiliating "treatment" that may have led to his suicide.With a novelist's sensitivity, David Leavitt portrays Turing in all his humanity—his eccentricities, his brilliance, his fatal candor—and elegantly explains his work and its implications.

    Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.

    Topics include the limits of knowledge, paradox of complexity, Maxwell's demon, Big Bang theory, much more. 1985 edition.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Though until now it has remained mostly anonymous, its members invented the concept of hacktivism, released the top tool for testing password security, and created what was for years the best technique for controlling computers from afar, forcing giant companies to work harder to protect customers. They contributed to the development of Tor, the most important privacy tool on the net, and helped build cyberweapons that advanced US security without injuring anyone. With its origins in the earliest days of the Internet, the cDc is full of oddball characters -- activists, artists, even future politicians. Many of these hackers have become top executives and advisors walking the corridors of power in Washington and Silicon Valley. The most famous is former Texas Congressman and current presidential candidate Beto O'Rourke, whose time in the cDc set him up to found a tech business, launch an alternative publication in El Paso, and make long-shot bets on unconventional campaigns.Today, the group and its followers are battling electoral misinformation, making personal data safer, and battling to keep technology a force for good instead of for surveillance and oppression. Cult of the Dead Cow shows how governments, corporations, and criminals came to hold immense power over individuals and how we can fight back against them.

    This change is being driven by powerful new cognitive tools, enabled by the internet, which are greatly accelerating scientific discovery. There are many books about how the internet is changing business or the workplace or government. But this is the first book about something much more fundamental: how the internet is transforming the nature of our collective intelligence and how we understand the world.Reinventing Discovery tells the exciting story of an unprecedented new era of networked science. We learn, for example, how mathematicians in the Polymath Project are spontaneously coming together to collaborate online, tackling and rapidly demolishing previously unsolved problems. We learn how 250,000 amateur astronomers are working together in a project called Galaxy Zoo to understand the large-scale structure of the Universe, and how they are making astonishing discoveries, including an entirely new kind of galaxy. These efforts are just a small part of the larger story told in this book--the story of how scientists are using the internet to dramatically expand our problem-solving ability and increase our combined brainpower.This is a book for anyone who wants to understand how the online world is revolutionizing scientific discovery today--and why the revolution is just beginning.

    By “reverse engineering the fastest growing company in the history of the world,” author Jeff Jarvis, proprietor of Buzzmachine.com, one of the Web’s most widely respected media blogs, offers indispensible strategies for solving the toughest new problems facing businesses today. With a new afterword from the author, What Would Google Do? is the business book that every leader or potential leader in every industry must read.

    Charles Darwin played a crucial part in turning heredity into a scientific question, and yet he failed spectacularly to answer it. The birth of genetics in the early 1900s seemed to do precisely that. Gradually, people translated their old notions about heredity into a language of genes. As the technology for studying genes became cheaper, millions of people ordered genetic tests to link themselves to missing parents, to distant ancestors, to ethnic identities. . . .But, Zimmer writes, "Each of us carries an amalgam of fragments of DNA, stitched together from some of our many ancestors. Each piece has its own ancestry, traveling a different path back through human history. A particular fragment may sometimes be cause for worry, but most of our DNA influences who we are--our appearance, our height, our penchants--in inconceivably subtle ways." Heredity isn't just about genes that pass from parent to child. Heredity continues within our own bodies, as a single cell gives rise to trillions of cells that make up our bodies. We say we inherit genes from our ancestors--using a word that once referred to kingdoms and estates--but we inherit other things that matter as much or more to our lives, from microbes to technologies we use to make life more comfortable. We need a new definition of what heredity is and, through Carl Zimmer's lucid exposition and storytelling, this resounding tour de force delivers it. Weaving historical and current scientific research, his own experience with his two daughters, and the kind of original reporting expected of one of the world's best science journalists, Zimmer ultimately unpacks urgent bioethical quandaries arising from new biomedical technologies, but also long-standing presumptions about who we really are and what we can pass on to future generations.

    It examines Stallman's unique personality and how that personality has been at turns a driving force and a drawback in terms of the movement's overall success.Free as in Freedom examines one man's 20-year attempt to codify and communicate the ethics of 1970s era "hacking" culture in such a way that later generations might easily share and build upon the knowledge of their computing forebears. The book documents Stallman's personal evolution from teenage misfit to prescient adult hacker to political leader and examines how that evolution has shaped the free software movement. Like Alan Greenspan in the financial sector, Richard Stallman has assumed the role of tribal elder within the hacking community, a community that bills itself as anarchic and averse to central leadership or authority. How did this paradox come about? Free as in Freedom provides an answer. It also looks at how the latest twists and turns in the software marketplace have diminished Stallman's leadership role in some areas while augmenting it in others.Finally, Free as in Freedom examines both Stallman and the free software movement from historical viewpoint. Will future generations see Stallman as a genius or crackpot? The answer to that question depends partly on which side of the free software debate the reader currently stands and partly upon the reader's own outlook for the future. 100 years from now, when terms such as "computer," "operating system" and perhaps even "software" itself seem hopelessly quaint, will Richard Stallman's particular vision of freedom still resonate, or will it have taken its place alongside other utopian concepts on the 'ash-heap of history?'

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them. Deep Thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake.

    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

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect