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.

    James Wallace brings readers up to date on the Gates saga to 1997 and reveals the inside story of the struggle to keep Microsoft on top in the World Wide Web game.

    It all points to a world that is getting faster at a dizzying pace.Azeem Azhar, renowned technology analyst and host of the Exponential View podcast, offers a revelatory new model for understanding how technology is evolving so fast, and why it fundamentally alters the world. He roots his analysis in the idea of an “exponential gap” in which technological developments rapidly outpace our society’s ability to catch up. Azhar shows that this divide explains many problems of our time—from political polarization to ballooning inequality to unchecked corporate power. With stunning clarity of vision, he delves into how the exponential gap is a near-inevitable consequence of the rise of AI, automation, and other exponential technologies, like renewable energy, 3D printing, and synthetic biology, which loom over the horizon.And he offers a set of policy solutions that can prevent the growing exponential gap from fragmenting, weakening, or even destroying our societies. The result is a wholly new way to think about technology, one that will transform our understanding of the economy, politics, and the future.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.