In the next ten years, change will happen even faster. As Hillary Clinton's Senior Advisor for Innovation, Alec Ross travelled nearly a million miles to forty-one countries, the equivalent of two round-trips to the moon. From refugee camps in the Congo and Syrian war zones, to visiting the world's most powerful people in business and government, Ross's travels amounted to a four-year masterclass in the changing nature of innovation. In The Industries of the Future, Ross distils his observations on the forces that are changing the world. He highlights the best opportunities for progress and explains how countries thrive or sputter. Ross examines the specific fields that will most shape our economic future over the next ten years, including robotics, artificial intelligence, the commercialization of genomics, cybercrime and the impact of digital technology. Blending storytelling and economic analysis, he answers questions on how we will need to adapt. Ross gives readers a vivid and informed perspective on how sweeping global trends are affecting the ways we live, now and tomorrow.

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    It argues that evolution designed us both to teach and learn, and that the drive to learn is our most important instinct. It also reveals as fascinating insights about our adult capacities and how even young children -- as well as adults -- use some of the same methods that allow scientists to learn so much about the world. Filled with surprise at every turn, this vivid, lucid, and often funny book gives us a new view of the inner life of children and the mysteries of the mind.

    We will soon be able to meet and exceed the basic needs of every man, woman and child on the planet. Abundance for all is within our grasp. This bold, contrarian view, backed up by exhaustive research, introduces our near-term future, where exponentially growing technologies and three other powerful forces are conspiring to better the lives of billions. An antidote to pessimism by tech entrepreneur turned philanthropist, Peter H. Diamandis and award-winning science writer Steven Kotler. Since the dawn of humanity, a privileged few have lived in stark contrast to the hardscrabble majority. Conventional wisdom says this gap cannot be closed. But it is closing—fast. The authors document how four forces—exponential technologies, the DIY innovator, the Technophilanthropist, and the Rising Billion—are conspiring to solve our biggest problems. Abundance establishes hard targets for change and lays out a strategic roadmap for governments, industry and entrepreneurs, giving us plenty of reason for optimism.Examining human need by category—water, food, energy, healthcare, education, freedom—Diamandis and Kotler introduce dozens of innovators making great strides in each area: Larry Page, Steven Hawking, Dean Kamen, Daniel Kahneman, Elon Musk, Bill Joy, Stewart Brand, Jeff Skoll, Ray Kurzweil, Ratan Tata, Craig Venter, among many, many others.

    From the transistor to the laser, it s hard to find an aspect of modern life that hasn t been touched by Bell Labs. Why did so many transformative ideas come from Bell Labs? In "The Idea Factory," Jon Gertner traces the origins of some of the twentieth century s most important inventions and delivers a riveting and heretofore untold chapter of American history. At its heart this is a story about the life and work of a small group of brilliant and eccentric men Mervin Kelly, Bill Shockley, Claude Shannon, John Pierce, and Bill Baker who spent their careers at Bell Labs. Their job was to research and develop the future of communications. Small-town boys, childhood hobbyists, oddballs: they give the lie to the idea that Bell Labs was a grim cathedral of top-down command and control.Gertner brings to life the powerful alchemy of the forces at work behind Bell Labs inventions, teasing out the intersections between science, business, and society. He distills the lessons that abide: how to recruit and nurture young talent; how to organize and lead fractious employees; how to find solutions to the most stubbornly vexing problems; how to transform a scientific discovery into a marketable product, then make it even better, cheaper, or both. Today, when the drive to invent has become a mantra, Bell Labs offers us a way to enrich our understanding of the challenges and solutions to technological innovation. Here, after all, was where the foundational ideas on the management of innovation were born. "The Idea Factory" is the story of the origins of modern communications and the beginnings of the information age a deeply human story of extraordinary men who were given extraordinary means time, space, funds, and access to one another and edged the world into a new dimension."

    What they don't realize—and what Daniel Hillis's short book brilliantly demonstrates—is that computers' seemingly complex operations can be broken down into a few simple parts that perform the same simple procedures over and over again.Computer wizard Hillis offers an easy-to-follow explanation of how data is processed that makes the operations of a computer seem as straightforward as those of a bicycle. Avoiding technobabble or discussions of advanced hardware, the lucid explanations and colorful anecdotes in The Pattern on the Stone go straight to the heart of what computers really do.Hillis proceeds from an outline of basic logic to clear descriptions of programming languages, algorithms, and memory. He then takes readers in simple steps up to the most exciting developments in computing today—quantum computing, parallel computing, neural networks, and self-organizing systems.Written clearly and succinctly by one of the world's leading computer scientists, The Pattern on the Stone is an indispensable guide to understanding the workings of that most ubiquitous and important of machines: the computer.

    It has built on itself for centuries, becoming vast and increasingly specialized. Most of us are ignorant about the fundamental principles of the civilization that supports us, happily utilizing the latest—or even the most basic—technology without having the slightest idea of why it works or how it came to be. If you had to go back to absolute basics, like some sort of postcataclysmic Robinson Crusoe, would you know how to re-create an internal combustion engine, put together a microscope, get metals out of rock, accurately tell time, weave fibers into clothing, or even how to produce food for yourself? Regarded as one of the brightest young scientists of his generation, Lewis Dartnell proposes that the key to preserving civilization in an apocalyptic scenario is to provide a quickstart guide, adapted to cataclysmic circumstances. The Knowledge describes many of the modern technologies we employ, but first it explains the fundamentals upon which they are built. Every piece of technology rests on an enormous support network of other technologies, all interlinked and mutually dependent. You can’t hope to build a radio, for example, without understanding how to acquire the raw materials it requires, as well as generate the electricity needed to run it. But Dartnell doesn’t just provide specific information for starting over; he also reveals the greatest invention of them all—the phenomenal knowledge-generating machine that is the scientific method itself. This would allow survivors to learn technological advances not explicitly explored in The Knowledge as well as things we have yet to discover. The Knowledge is a brilliantly original guide to the fundamentals of science and how it built our modern world as well as a thought experiment about the very idea of scientific knowledge itself.

    Today, twenty million people worldwide are surfing the Net. Where Wizards Stay Up Late is the exciting story of the pioneers responsible for creating the most talked about, most influential, and most far-reaching communications breakthrough since the invention of the telephone. In the 1960's, when computers where regarded as mere giant calculators, J.C.R. Licklider at MIT saw them as the ultimate communications devices. With Defense Department funds, he and a band of visionary computer whizzes began work on a nationwide, interlocking network of computers. Taking readers behind the scenes, Where Wizards Stay Up Late captures the hard work, genius, and happy accidents of their daring, stunningly successful venture.

    The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard.Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

    The controversial book linking intelligence to class and race in modern society, and what public policy can do to mitigate socioeconomic differences in IQ, birth rate, crime, fertility, welfare, and poverty.

    Here, for the first time and in detail, Zimbardo tells the full story of the Stanford Prison Experiment, the landmark study in which a group of college-student volunteers was randomly divided into “guards” and “inmates” and then placed in a mock prison environment. Within a week, the study was abandoned, as ordinary college students were transformed into either brutal, sadistic guards or emotionally broken prisoners. By illuminating the psychological causes behind such disturbing metamorphoses, Zimbardo enables us to better understand a variety of harrowing phenomena, from corporate malfeasance to organized genocide to how once upstanding American soldiers came to abuse and torture Iraqi detainees in Abu Ghraib. He replaces the long-held notion of the “bad apple” with that of the “bad barrel”—the idea that the social setting and the system contaminate the individual, rather than the other way around.

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    Paradoxical portraits of seven neurological patients, including a surgeon consumed by the compulsive tics of Tourette's syndrome unless he is operating; an artist who loses all sense of color in a car accident, but finds new creative power in black & white; & others.

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

     The more tools you have at your disposal, the more likely you'll use the right tool for the job — and get it done right. The same is true when it comes to your thinking. The quality of your outcomes depends on the mental models in your head. And most people are going through life with little more than a hammer. Until now. The Great Mental Models: General Thinking Concepts is the first book in The Great Mental Models series designed to upgrade your thinking with the best, most useful and powerful tools so you always have the right one on hand. This volume details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making, productivity, and how clearly you see the world. You will discover what forces govern the universe and how to focus your efforts so you can harness them to your advantage, rather than fight with them or worse yet— ignore them. Upgrade your mental toolbox and get the first volume today!