Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    An unpopular war. A military and diplomatic team in disarray. Those are the challenges President Obama has faced as he attempts to make a success of U.S involvement in Afghanistan. They are also the challenges President Truman surmounted in the winter of 1950 as he began managing a war in Korea that risked becoming bigger and more costly. It was the first significant armed conflict of the Cold War: United States troops under the command of General Douglas MacArthur came to the aid of the South Koreans after North Korea invaded. When Communist China entered the conflict on the side of the North Koreans, the crisis seemed on the verge of flaring into a world war. Truman was determined not to let that happen. MacArthur kept urging a widening of the war into China itself and ignoring his Commander in Chief. On April 11, 1951, after MacArthur had “shot his mouth off,” as one diplomat put it, one too many times, Truman fired him. The story of their showdown—one of the most dramatic in U.S. history between a Commander in Chief and his top soldier in the field—is captured in all its detail by David McCullough in his biography Truman, and presented here in a e-book called Truman Fires MacArthur (an excerpt of Truman, McCullough’s Pulitzer Prize-winning biography), which was the headline carried in many newspapers around the country the next day. Truman Fires MacArthur will continue to ride the headlines. It will go on sale as an ebook just as the Rolling Stone profile that exposed General Stanley McChrystal’s insurrection and forced his resignation hits newsstands, and media coverage of the showdown continues to draw historical analogies between Truman and Obama.

    It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What hap­pens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?  Who knows—maybe there’s a bot learning to do your job this minute.

    For five years in his mid-twenties, he sailed on the BEAGLE around the world, exploring jungles, climbing mountains, trekking across deserts. With every new landfall, he had new adventures: he rode through bandit country, was thrown into jail by revolutionaries, took part in an armed raid with marines, survived two earthquakes, hunted and fished. He suffered the terrible cold and rain of Tierra del Fuego, the merciless heat of the Australian outback and the inner pangs of heartbreak. He also made the discoveries that finally led him to formulate his theory of Natural Selection as the driving force of evolution. The five-year voyage of the BEAGLE was the basis for all Darwin's later work; but it also turned him from a friendly idler into the greatest scientist of his century. Kevin Jackson is a writer, broadcaster and film-maker. His most recent book is Constellation of Genius: 1922 and All That Jazz (Farrar Strauss Giroux, 2013). He lives in Cambridge, England.

    They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work―and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities.While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human―and to crack the creativity code.

    Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

    What should you and your company be doing today to ensure that you're poised for success and keeping up with your competitors in the age of AI?Artificial Intelligence: The Insights You Need from Harvard Business Review brings you today's most essential thinking on AI and explains how to launch the right initiatives at your company to capitalize on the opportunity of the machine intelligence revolution.Business is changing. Will you adapt or be left behind?Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.

    

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.In AI Superpowers, Kai-Fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power.Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.

    After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layerperceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.

    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.

    Digital technologies—with hardware, software, and networks at their core—will in the near future diagnose diseases more accurately than doctors can, apply enormous data sets to transform retailing, and accomplish many tasks once considered uniquely human.In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee—two thinkers at the forefront of their field—reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.Amid this bounty will also be wrenching change. Professions of all kinds—from lawyers to truck drivers—will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.A fundamentally optimistic book, The Second Machine Age alters how we think about issues of technological, societal, and economic progress.

    Matthew Bannister said he was going to reinvent the station, the most popular in Europe. But things didn't go exactly to plan. The station lost millions of listeners. Its most famous DJs left, and their replacements proved to be disasters. Radio 1's commercial rivals regarded the internal turmoil with glee. For a while a saviour arrived, in the shape of Chris Evans. But his behaviour caused further upheavals, and his eventual departure provoked another mass desertion by listeners. What was to be done? In the middle of this crisis, Radio 1 bravely (or foolishly) allowed the writer Simon Garfield to observe its workings from the inside. For a year he was allowed unprecedented access to management meetings and to DJs in their studios, to research briefings and playlist conferences. Everyone interviewed spoke in passionate detail about their struggle to make their station credible and successful once more. The result is a gripping and often hilarious portrait a much loved national institution as it battles back from the brink of calamity.

    But ask a physicist and there’s no doubt that James Clerk Maxwell will be near the top of the list.  Maxwell, an unassuming Victorian Scotsman, explained how we perceive colour. He uncovered the way gases behave. And, most significantly, he transformed the way physics was undertaken in his explanation of the interaction of electricity and magnetism, revealing the nature of light and laying the groundwork for everything from Einstein’s special relativity to modern electronics.   Along the way, he set up one of the most enduring challenges in physics, one that has taxed the best minds ever since. ‘Maxwell’s demon’ is a tiny but thoroughly disruptive thought experiment that suggests the second law of thermodynamics, the law that governs the flow of time itself, can be broken. This is the story of a groundbreaking scientist, a great contributor to our understanding of the way the world works, and his duplicitous demon.