Pulitzer prize-winning New York Times science writer John Markoff argues that we must decide to design ourselves into our future, or risk being excluded from it altogether.In the past decade, Google introduced us to driverless cars; Apple debuted Siri, a personal assistant that we keep in our pockets; and an Internet of Things connected the smaller tasks of everyday life to the farthest reaches of the Web. Robots have become an integral part of society on the battlefield and the road; in business, education, and health care. Cheap sensors and powerful computers will ensure that in the coming years, these robots will act on their own. This new era offers the promise of immensely powerful machines, but it also reframes a question first raised more than half a century ago, when the intelligent machine was born. Will we control these systems, or will they control us?In Machines of Loving Grace, John Markoff offers a sweeping history of the complicated and evolving relationship between humans and computers. In recent years, the pace of technological change has accelerated dramatically, posing an ethical quandary. If humans delegate decisions to machines, who will be responsible for the consequences? As Markoff chronicles the history of automation, from the birth of the artificial intelligence and intelligence augmentation communities in the 1950s and 1960s, to the modern-day brain trusts at Google and Apple in Silicon Valley, and on to the expanding robotics economy around Boston, he traces the different ways developers have addressed this fundamental problem and urges them to carefully consider the consequences of their work. We are on the brink of the next stage of the computer revolution, Markoff argues, and robots will profoundly transform modern life. Yet it remains for us to determine whether this new world will be a utopia. Moreover, it is now incumbent upon the designers of these robots to draw a bright line between what is human and what is machine.After nearly forty years covering the tech industry, Markoff offers an unmatched perspective on the most drastic technology-driven societal shifts since the introduction of the Internet. Machines of Loving Grace draws on an extensive array of research and interviews to present an eye-opening history of one of the most pressing questions of our time, and urges us to remember that we still have the opportunity to design ourselves into the future—before it's too late.

    Escher -- goes to some of the strangest spots imaginable. It takes us to a place where the purely intellectual enters our daily world: where our outraged senses, overloaded with grocery bills, the price of gas, and what to eat for lunch, are expected to absorb really bizarre ideas. And no better guide to this weird universe exists than the brilliant thinker Clifford A. Pickover, the 21st century's answer to Buckminster Fuller. Come along as Pickover traces the origins of the Mobius strip from the mid-1800s, when the visionary scientist Dr. August Mobius became the first to describe the properties of one-sided surfaces, to the present, where it is an integral part of mathematics, magic, science, art, engineering, literature, and music. It has become a metaphor for change, strangeness, looping, and rejuvenation. Touching on everything from molecules and metal sculptures to postage stamps, architectural structures, and models of our entire universe, The Mobius Strip is lavishly illustrated and gives readers a glimpse into other worlds and new ways of thinking as Pickover reaches across cultures and dimensions.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    But from the perspective of mathematics, groupings of ten are arbitrary, and can have serious shortcomings. Twelve would be better for divisibility, and eight is smaller and well suited to repeated halving. Grouping by two, as in binary code, has turned out to have its own remarkable advantages.Paul Lockhart reveals arithmetic not as the rote manipulation of numbers--a practical if mundane branch of knowledge best suited for balancing a checkbook or filling out tax forms--but as a set of ideas that exhibit the fascinating and sometimes surprising behaviors usually reserved for higher branches of mathematics. The essence of arithmetic is the skillful arrangement of numerical information for ease of communication and comparison, an elegant intellectual craft that arises from our desire to count, add to, take away from, divide up, and multiply quantities of important things. Over centuries, humans devised a variety of strategies for representing and using numerical information, from beads and tally marks to adding machines and computers. Lockhart explores the philosophical and aesthetic nature of counting and of different number systems, both Western and non-Western, weighing the pluses and minuses of each.A passionate, entertaining survey of foundational ideas and methods, Arithmetic invites readers to experience the profound and simple beauty of its subject through the eyes of a modern research mathematician.

    It's about states, armies and corporations. It's about orders from on high. Even history "from below" is often about trade unions and workers' parties. But what if that's simply because hierarchical institutions create the archives that historians rely on? What if we are missing the informal, less well documented social networks that are the true sources of power and drivers of change?The 21st century has been hailed as the Age of Networks. However, in The Square and the Tower, Niall Ferguson argues that networks have always been with us, from the structure of the brain to the food chain, from the family tree to freemasonry. Throughout history, hierarchies housed in high towers have claimed to rule, but often real power has resided in the networks in the town square below. For it is networks that tend to innovate. And it is through networks that revolutionary ideas can contagiously spread. Just because conspiracy theorists like to fantasize about such networks doesn't mean they are not real.From the cults of ancient Rome to the dynasties of the Renaissance, from the founding fathers to Facebook, The Square and the Tower tells the story of the rise, fall and rise of networks, and shows how network theory--concepts such as clustering, degrees of separation, weak ties, contagions and phase transitions--can transform our understanding of both the past and the present.Just as The Ascent of Money put Wall Street into historical perspective, so The Square and the Tower does the same for Silicon Valley. And it offers a bold prediction about which hierarchies will withstand this latest wave of network disruption--and which will be toppled.

    There she saw first-hand how deeply intertwined Silicon Valley was with the federal government, and always had been, and how shallow the common understanding of the secrets of the Valley's success actually was. Now, after almost five years of pioneering research, O'Mara has produced the definitive history of Silicon Valley for our time, the story of mavericks and visionaries, but also of powerful institutions creating the framework for innovation, from the Pentagon to Stanford University. It is also a story of a community that started off remarkably homogeneous and elitist and stayed that way, and whose belief in its own mythology has deepened into a collective hubris that has led to astonishing triumphs as well as devastating second-order effects.Deploying a wonderfully rich and diverse cast of protagonists, from the justly famous to the unjustly obscure, across four generations of explosive growth in the Valley, from the Forties to the present, O'Mara has wrestled into magnificent narrative form one of the most fateful developments in modern American history. She is on the ground with all of the key tech companies, and chronicles the evolution in their offerings through each successive era, and she has a profound fingertip feel for the politics of the sector, and its relation to the larger cultural narrative about tech as it has evolved over the years. Perhaps most impressively, O'Mara has penetrated the inner kingdom of tech venture capital firms, the insular and still remarkably old-boy world that became the cockpit of American capitalism and the crucible for bringing technological innovation to market, or not. The transformation of big tech into the engine room of the American economy and the nexus of so many of our hopes and dreams--and increasingly nightmares--can be understood, in Margaret O'Mara's masterful hands, as the story of one California valley. As her majestic history makes clear, its fate is the fate of us all.

    It’ll have you scratching your head wondering why we even bother to go to school.Think Magellan was the first man to circumnavigate the globe, baseball was invented in America, Henry VIII had six wives, Mount Everest is the tallest mountain? Wrong, wrong, wrong, and wrong again. You’ll be surprised at how much you don’t know! Check out THE BOOK OF GENERAL IGNORANCE for more fun entries and complete answers to the following:How long can a chicken live without its head?About two years.What do chameleons do?They don’t change color to match the background. Never have; never will. Complete myth. Utter fabrication. Total Lie. They change color as a result of different emotional states.How many legs does a centipede have?Not a hundred.How many toes has a two-toed sloth?It’s either six or eight.Who was the first American president?Peyton Randolph.What were George Washington’s false teeth made from?Mostly hippopotamus.What was James Bond’s favorite drink?Not the vodka martini.

    This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable.Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women?Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

    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.