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.

    In Why Greatness Cannot Be Planned, Stanley and Lehman begin with a surprising scientific discovery in artificial intelligence that leads ultimately to the conclusion that the objective obsession has gone too far. They make the case that great achievement can't be bottled up into mechanical metrics; that innovation is not driven by narrowly focused heroic effort; and that we would be wiser (and the outcomes better) if instead we whole-heartedly embraced serendipitous discovery and playful creativity.Controversial at its heart, yet refreshingly provocative, this book challenges readers to consider life without a destination and discovery without a compass.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

    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.

    Psychologist Geoffrey Miller offers the most convincing-and radical-explanation for how and why the human mind evolved.Consciousness, morality, creativity, language, and art: these are the traits that make us human. Scientists have traditionally explained these qualities as merely a side effect of surplus brain size, but Miller argues that they were sexual attractors, not side effects. He bases his argument on Darwin's theory of sexual selection, which until now has played second fiddle to Darwin's theory of natural selection, and draws on ideas and research from a wide range of fields, including psychology, economics, history, and pop culture. Witty, powerfully argued, and continually thought-provoking, The Mating Mind is a landmark in our understanding of our own species.

    Its authors present a new view of cognition that has important social and ethical implications, for, they assert, the only world we humans can have is the one we create together through the actions of our coexistence. Written for a general audience as well as for students, scholars, and scientists and abundantly illustrated with examples from biology, linguistics, and new social and cultural phenomena, this revised edition includes a new afterword by Dr. Varela, in which he discusses the effect the book has had in the years since its first publication.

    Negroponte's fans will want to get a copy of Being Digital, which is an edited version of the 18 articles he wrote for Wired about "being digital." Negroponte's text is mostly a history of media technology rather than a set of predictions for future technologies. In the beginning, he describes the evolution of CD-ROMs, multimedia, hypermedia, HDTV (high-definition television), and more. The section on interfaces is informative, offering an up-to-date history on visual interfaces, graphics, virtual reality (VR), holograms, teleconferencing hardware, the mouse and touch-sensitive interfaces, and speech recognition. In the last chapter and the epilogue, Negroponte offers visionary insight on what "being digital" means for our future. Negroponte praises computers for their educational value but recognizes certain dangers of technological advances, such as increased software and data piracy and huge shifts in our job market that will require workers to transfer their skills to the digital medium. Overall, Being Digital provides an informative history of the rise of technology and some interesting predictions for its future.

    The latter has long been the subject of speculation, but over the past two decades researchers have developed remarkable new tools for probing the hidden, or subliminal, workings of the mind. The result of this explosion of research is a new science of the unconscious and a sea change in our understanding of how the subliminal mind affects the way we live.Employing his trademark wit and lucid, accessible explanations of the most obscure scientific subjects, Leonard Mlodinow takes us on a tour of this research, unraveling the complexities of the subliminal self and increasing our understanding of how the human mind works and how we interact with friends, strangers, spouses, and coworkers. In the process he changes our view of ourselves and the world around us.

    Ratey provides insight into the basic structure and chemistry of the brain, and demonstrates how its systems shape our perceptions, emotions, and behavior. By giving us a greater understanding of how the brain responds to the guidance of its user, he provides us with knowledge that can enable us to improve our lives.In A User’s Guide to the Brain, Ratey clearly and succinctly surveys what scientists now know about the brain and how we use it. He looks at the brain as a malleable organ capable of improvement and change, like any muscle, and examines the way specific motor functions might be applied to overcome neural disorders ranging from everyday shyness to autism. Drawing on examples from his practice and from everyday life, Ratey illustrates that the most important lesson we can learn about our brains is how to use them to their maximum potential.

    For over a century, a diverse array of researchers have been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it.In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when bringing the abstract world of mathematical modelling into contact with the messy details of biology.Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. Throughout Grace will look at the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics, and reveals in full the remarkable fruits of this endeavour.

    Today, we know that our brains and nervous systems change throughout our lifetimes. This concept of neuroplasticity has captured the imagination of a public eager for self-improvement--and has inspired countless Internet entrepreneurs who peddle dubious "brain training" games and apps. In this book, Moheb Costandi offers a concise and engaging overview of neuroplasticity for the general reader, describing how our brains change continuously in response to our actions and experiences.Costandi discusses key experimental findings, and describes how our thinking about the brain has evolved over time. He explains how the brain changes during development, and the "synaptic pruning" that takes place before brain maturity. He shows that adult brains can grow new cells (citing, among many other studies, research showing that sexually mature male canaries learn a new song every year). He describes the kind of brain training that can bring about improvement in brain function. It's not gadgets and games that promise to "rewire your brain" but such sustained cognitive tasks as learning a musical instrument or a new language. (Costandi also notes that London cabbies increase their gray matter after rigorous training in their city's complicated streets.) He tells how brains compensate after stroke or injury; describes addiction and pain as maladaptive forms of neuroplasticity; and considers brain changes that accompany childhood, adolescence, parenthood, and aging. Each of our brains is custom-built. Neuroplasticity is at the heart of what makes us human.

    When we are awake we identify with our body, but if we let our mind wander or daydream, we project a mentally imagined self into the remembered past or anticipated future. As we fall asleep, the impression of being a bounded self distinct from the world dissolves, but the self reappears in the dream state. If we have a lucid dream, we no longer identify only with the self within the dream. Our sense of self now includes our dreaming self, the "I" as dreamer. Finally, as we meditate--either in the waking state or in a lucid dream--we can observe whatever images or thoughts arise and how we tend to identify with them as "me." We can also experience sheer awareness itself, distinct from the changing contents that make up our image of the self.Contemplative traditions say that we can learn to let go of the self, so that when we die we can witness its dissolution with equanimity. Thompson weaves together neuroscience, philosophy, and personal narrative to depict these transformations, adding uncommon depth to life's profound questions. Contemplative experience comes to illuminate scientific findings, and scientific evidence enriches the vast knowledge acquired by contemplatives.

    Integrating recent insights from evolutionary biology, genetics, psychology, economics, and other fields, Boyer offers precise models of why humans engage in social behaviors such as forming families, tribes, and nations, or creating gender roles. In fascinating, thought-provoking passages, he explores questions such as, Why is there conflict between groups? Why do people believe low-value information such as rumors? Why are there religions? What is social justice? What explains morality? Boyer provides a new picture of cultural transmission that draws on the pragmatics of human communication, the constructive nature of memory in human brains, and human motivation for group formation and cooperation.

    General introductions by Janet Murray and Lev Manovich, along with short introductions to each of the texts, place the works in their historical context and explain their significance. The texts were originally published between World War II--when digital computing, cybernetic feedback, and early notions of hypertext and the Internet first appeared--and the emergence of the World Wide Web--when they entered the mainstream of public life.The texts are by computer scientists, artists, architects, literary writers, interface designers, cultural critics, and individuals working across disciplines. The contributors include (chronologically) Jorge Luis Borges, Vannevar Bush, Alan Turing, Ivan Sutherland, William S. Burroughs, Ted Nelson, Italo Calvino, Marshall McLuhan, Billy Kl?Jean Baudrillard, Nicholas Negroponte, Alan Kay, Bill Viola, Sherry Turkle, Richard Stallman, Brenda Laurel, Langdon Winner, Robert Coover, and Tim Berners-Lee. The CD accompanying the book contains examples of early games, digital art, independent literary efforts, software created at universities, and home-computer commercial software. Also on the CD is digitized video, documenting new media programs and artwork for which no operational version exists. One example is a video record of Douglas Engelbart's first presentation of the mouse, word processor, hyperlink, computer-supported cooperative work, video conferencing, and the dividing up of the screen we now call non-overlapping windows; another is documentation of Lynn Hershman's Lorna, the first interactive video art installation.

    Most of it is caught by filters before ever reaching an in-box. Where does it come from? As Finn Brunton explains in Spam, it is produced and shaped by many different populations around the world: programmers, con artists, bots and their botmasters, pharmaceutical merchants, marketers, identity thieves, crooked bankers and their victims, cops, lawyers, network security professionals, vigilantes, and hackers. Every time we go online, we participate in the system of spam, with choices, refusals, and purchases the consequences of which we may not understand.This is a book about what spam is, how it works, and what it means. Brunton provides a cultural history that stretches from pranks on early computer networks to the construction of a global criminal infrastructure. The history of spam, Brunton shows us, is a shadow history of the Internet itself, with spam emerging as the mirror image of the online communities it targets. Brunton traces spam through three epochs: the 1970s to 1995, and the early, noncommercial computer networks that became the Internet; 1995 to 2003, with the dot-com boom, the rise of spam's entrepreneurs, and the first efforts at regulating spam; and 2003 to the present, with the war of algorithms--spam versus anti-spam. Spam shows us how technologies, from email to search engines, are transformed by unintended consequences and adaptations, and how online communities develop and invent governance for themselves.