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.

    Blade Runner, The Matrix, Star Wars, Avatar, Star Trek, Ready Player One and Avengers show us futuristic worlds where holograms, intelligent robots, smart devices, virtual avatars, digital transactions, and universe-scale teleportation work together perfectly, somehow seamlessly combining the virtual and the physical with the mechanical and the biological. Science fiction has done an excellent job describing a vision of the future where the digital and physical merge naturally into one — in a way that just works everywhere, for everyone. However, none of these visionary fictional works go so far as to describe exactly how this would actually be accomplished. While it has inspired many of us to ask the question—How do we enable science fantasy to become....science fact? The Spatial Web achieves this by first describing how exponentially powerful computing technologies are creating a great “Convergence.” How Augmented and Virtual Reality will enable us to overlay our information and imaginations onto the world. How Artificial Intelligence will infuse the environments and objects around us with adaptive intelligence. How the Internet of Things and Robotics will enable our vehicles, appliances, clothing, furniture, and homes to become connected and embodied with the power to see, feel, hear, smell, touch and move things in the world, and how Blockchain and Cryptocurrencies will secure our data and enable real-time transactions between the human, machine and virtual economies of the future. The book then dives deeply into the challenges and shortcomings of the World Wide Web, the rise of fake news and surveillance capitalism in Web 2.0 and the risk of algorithmic terrorism and biological hacking and “fake-reality” in Web 3.0. It raises concerns about the threat that emerging technologies pose in the hands of rogue actors whether human, algorithmic, corporate or state-sponsored and calls for common sense governance and global cooperation. It calls for business leaders, organizations and governments to not only support interoperable standards for software code, but critically, for ethical, and social codes as well. Authors Gabriel René and Dan Mapes describe in vivid detail how a new “spatial” protocol is required in order to connect the various exponential technologies of the 21st century into an integrated network capable of tracking and managing the real-time activities of our cities, monitoring and adjusting the supply chains that feed them, optimizing our farms and natural resources, automating our manufacturing and distribution, transforming marketing and commerce, accelerating our global economies, running advanced planet-scale simulations and predictions, and even bridging the gap between our interior individual reality and our exterior collective one. Enabling the ability for humans, machines and AI to communicate, collaborate and coordinate activities in the world at a global scale and how the thoughtful application of these technologies could lead to an unprecedented opportunity to create a truly global “networked” civilization or "Smart World.” The book artfully shifts between cyberpunk futurism, cautionary tale-telling, and life-affirming call-to-arms. It challenges us to consider the importance of today’s technological choices as individuals, organizations, and as a species, as we face the historic opportunity we have to transform the web, the world, and our very definition of reality.

    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.

    

    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.

    Frankenstein marveling at his "modern Prometheus" to the man-meets-machine fiction of Philip K. Dick and Michael Crichton, humans have been enthralled by the possibilities of emotional relationships with their technological creations. Synthesizing cutting-edge research in robotics with the cultural history and psychology of artificial intelligence, Love and Sex with Robots explores this fascination and its far-reaching implications.Using examples drawn from around the world, David Levy shows how automata have evolved from the mechanical marvels of centuries past to the electronic androids of the modern age, and how human interactions with technology have changed over the years. Along the way, Levy explores many aspects of human relationships—the reasons we fall in love, why we form emotional attachments to animals and to virtual pets such as the Tamagotchi, and why these same attachments could extend to love for robots. He also examines the needs we seek to fulfill through sexual relationships, tracking the development of life-sized dolls, machines, and other sexual devices, and demonstrating how society's ideas about what constitutes normal sex have changed—and will continue to change—as sexual technology becomes increasingly sophisticated.Shocking but utterly convincing, Love and Sex with Robots provides insights that are surprisingly relevant to our everyday interactions with technology. This is science brought to life, and Levy makes a compelling and titillating case that the entities we once deemed cold and mechanical will soon become the objects of real companionship and human desire. Anyone reading the book with an open mind will find a wealth of fascinating material on this important new direction of intimate relationships, a direction that, before long, will be regarded as perfectly normal.

    Each self-contained chapter consists of three sections. The first describes the statistic, including how it is used and what information it provides. The second section reviews how it works, how to calculate the formula, the strengths and weaknesses of the technique, and the conditions needed for its use. The final section provides examples that use and interpret the statistic. A glossary of terms and symbols is also included.New features in the second edition include:an interactive CD with PowerPoint presentations and problems for each chapter including an overview of the problem's solution; new chapters on basic research concepts including sampling, definitions of different types of variables, and basic research designs and one on nonparametric statistics; more graphs and more precise descriptions of each statistic; and a discussion of confidence intervals.This brief paperback is an ideal supplement for statistics, research methods, courses that use statistics, or as a reference tool to refresh one's memory about key concepts. The actual research examples are from psychology, education, and other social and behavioral sciences.Materials formerly available with this book on CD-ROM are now available for download from our website www.psypress.com. Go to the book's page and look for the 'Download' link in the right-hand column.

    But MIT Media Lab researcher and technology policy expert Kate Darling argues just the opposite, and that treating robots with a bit of humanity, more like the way we treat animals, will actually serve us better. From a social, legal, and ethical perspective, she shows that our current ways of thinking don't leave room for the robot technology that is soon to become part of our everyday routines. Robots are likely to supplement--rather than replace--our own skills and relationships. So if we consider our history of incorporating animals into our work, transportation, military, and even families, we actually have a solid basis for how to contend with this future.A deeply original analysis of our technological future and the ethical dilemmas that await us, The New Breed explains how the treatment of machines can reveal a new understanding of our own history, our own systems and how we relate--not just to non-humans, but also to each other.

    HOW RISKY IS IT, REALLY?International risk expert David Ropeik takes an in-depth look at our perceptions of risk and explains the hidden factors that make us unnecessarily afraid of relatively small threats and not afraid enough of some really big ones. This read is a comprehensive, accessible, and entertaining mixture of what's been discovered about how and why we fear — too much or too little. It brings into focus the danger of The Perception Gap: when our fears don't match the facts, and we make choices that create additional risks.This book will not decide for you what is really risky and what isn't. That's up to you. HOW RISKY IS IT, REALLY? will tell you how you make those decisions. Understanding how we perceive risk is the first step toward making wiser and healthier choices for ourselves as individuals and for society as a whole.TEST YOUR OWN "RISK RESPONSE" IN DOZENS OF SELF-QUIZZES!

    If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Brooks, director of the MIT Artificial Intelligence Laboratory believes we are. In this lucid and accessible book, Brooks vividly depicts the history of robots and explores the ever-changing relationships between humans and their technological brethren, speculating on the growing role that robots will play in our existence. Knowing the moral battle likely to ensue, he posits a clear philosophical argument as to why we should not fear that change. What results is a fascinating book that offers a deeper understanding of who we are and how we can control what we will become.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    The topic everyone in the world should be talking about.