Psychologists have long been aware that most people maintain an often irrationally positive outlook on life. In fact, optimism may be crucial to our existence. Tali Sharot’s experiments, research, and findings in cognitive science have contributed to an increased understanding of the biological basis of optimism. In this fascinating exploration, she takes an in-depth, clarifying look at how the brain generates hope and what happens when it fails; how the brains of optimists and pessimists differ; why we are terrible at predicting what will make us happy; how emotions strengthen our ability to recollect; how anticipation and dread affect us; and how our optimistic illusions affect our financial, professional, and emotional decisions.  With its cutting-edge science and its wide-ranging and accessible narrative, The Optimism Bias provides us with startling new insight into the workings of the brain.From the Hardcover edition.

    Dennett, Gerald Edelman, and Roger Penrose, all firing volleys in what has come to be called the consciousness wars. Now, in The Conscious Mind, philosopher David J. Chalmers offers a cogent analysis of this heated debate as he unveils a major new theory of consciousness, one that rejects the prevailing reductionist trend of science, while offering provocative insights into the relationship between mind and brain.Writing in a rigorous, thought-provoking style, the author takes us on a far-reaching tour through the philosophical ramifications of consciousness. Chalmers convincingly reveals how contemporary cognitive science and neurobiology have failed to explain how and why mental events emerge from physiological occurrences in the brain. He proposes instead that conscious experience must be understood in an entirely new light--as an irreducible entity (similar to such physical properties as time, mass, and space) that exists at a fundamental level and cannot be understood as the sum of its parts. And after suggesting some intriguing possibilities about the structure and laws of conscious experience, he details how his unique reinterpretation of the mind could be the focus of a new science. Throughout the book, Chalmers provides fascinating thought experiments that trenchantly illustrate his ideas. For example, in exploring the notion that consciousness could be experienced by machines as well as humans, Chalmers asks us to imagine a thinking brain in which neurons are slowly replaced by silicon chips that precisely duplicate their functions--as the neurons are replaced, will consciousness gradually fade away? The book also features thoughtful discussions of how the author's theories might be practically applied to subjects as diverse as artificial intelligence and the interpretation of quantum mechanics.All of us have pondered the nature and meaning of consciousness. Engaging and penetrating, The Conscious Mind adds a fresh new perspective to the subject that is sure to spark debate about our understanding of the mind for years to come.

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    Sapolsky's storytelling concept is delightful but it also has a powerful intrinsic logic: he starts by looking at the factors that bear on a person's reaction in the precise moment a behavior occurs, and then hops back in time from there, in stages, ultimately ending up at the deep history of our species and its evolutionary legacy.And so the first category of explanation is the neurobiological one. A behavior occurs--whether an example of humans at our best, worst, or somewhere in between. What went on in a person's brain a second before the behavior happened? Then Sapolsky pulls out to a slightly larger field of vision, a little earlier in time: What sight, sound, or smell caused the nervous system to produce that behavior? And then, what hormones acted hours to days earlier to change how responsive that individual is to the stimuli that triggered the nervous system? By now he has increased our field of vision so that we are thinking about neurobiology and the sensory world of our environment and endocrinology in trying to explain what happened.Sapolsky keeps going: How was that behavior influenced by structural changes in the nervous system over the preceding months, by that person's adolescence, childhood, fetal life, and then back to his or her genetic makeup? Finally, he expands the view to encompass factors larger than one individual. How did culture shape that individual's group, what ecological factors millennia old formed that culture? And on and on, back to evolutionary factors millions of years old.The result is one of the most dazzling tours d'horizon of the science of human behavior ever attempted, a majestic synthesis that harvests cutting-edge research across a range of disciplines to provide a subtle and nuanced perspective on why we ultimately do the things we do...for good and for ill. Sapolsky builds on this understanding to wrestle with some of our deepest and thorniest questions relating to tribalism and xenophobia, hierarchy and competition, morality and free will, and war and peace. Wise, humane, often very funny, Behave is a towering achievement, powerfully humanizing, and downright heroic in its own right.

    Unlike traditional empirical psychology, it is more oriented toward the how than the what. An experiment in mind design is more likely to be an attempt to build something and make it work--as in artificial intelligence--than to observe or analyze what already exists. Mind design is psychology by reverse engineering.When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's Computing Machinery and Intelligence) and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are philosophical in that they address fundamental issues and concepts; and all are scientific in that they are technically sophisticated and concerned with concrete empirical research.ContributorsRodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder

    Then he wrote a groundbreaking operating system and distributed it via the Internet -- for free. Today Torvalds is an international folk hero. And his creation LINUX is used by over 12 million people as well as by companies such as IBM.Now, in a narrative that zips along with the speed of e-mail, Torvalds gives a history of his renegade software while candidly revealing the quirky mind of a genius. The result is an engrossing portrayal of a man with a revolutionary vision, who challenges our values and may change our world.

    The meme is also one of the most important--and controversial--concepts to emerge since 'The Origin of the Species' appeared nearly 150 years ago.In 'The Meme Machine' Susan Blackmore boldly asserts: "Just as the design of our bodies can be understood only in terms of natural selection, so the design of our minds can be understood only in terms of memetic selection." Indeed, Blackmore shows that once our distant ancestors acquired the crucial ability to imitate, a second kind of natural selection began, a survival of the fittest amongst competing ideas and behaviors. Ideas and behaviors that proved most adaptive - making tools, for example, or using language--survived and flourished, replicating themselves in as many minds as possible. These memes then passed themselves on from generation to generation by helping to ensure that the genes of those who acquired them also survived and reproduced. Applying this theory to many aspects of human life, Blackmore offers brilliant explanations for why we live in cities, why we talk so much, why we can't stop thinking, why we behave altruistically, how we choose our mates, and much more.With controversial implications for our religious beliefs, our free will, our very sense of "self," 'The Meme Machine' offers a provocative theory everyone will soon be talking about.

    It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

    Over the past decade, Silicon Valley executives like Eric Schmidt and Elon Musk, Special Operators like the Navy SEALs and the Green Berets, and maverick scientists like Sasha Shulgin and Amy Cuddy have turned everything we thought we knew about high performance upside down. Instead of grit, better habits, or 10,000 hours, these trailblazers have found a surprising short cut. They're harnessing rare and controversial states of consciousness to solve critical challenges and outperform the competition.New York Times bestselling author Steven Kotler and high performance expert Jamie Wheal spent four years investigating the leading edges of this revolution—from the home of SEAL Team Six to the Googleplex, the Burning Man festival, Richard Branson’s Necker Island, Red Bull’s training center, Nike’s innovation team, and the United Nations’ Headquarters. And what they learned was stunning: In their own ways, with differing languages, techniques, and applications, every one of these groups has been quietly seeking the same thing: the boost in information and inspiration that altered states provide.Today, this revolution is spreading to the mainstream, fueling a trillion dollar underground economy and forcing us to rethink how we can all lead richer, more productive, more satisfying lives. Driven by four accelerating forces—psychology, neurobiology, technology and pharmacology—we are gaining access to and insights about some of the most contested and misunderstood terrain in history. Stealing Fire is a provocative examination of what’s actually possible; a guidebook for anyone who wants to radically upgrade their life.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    In The Ego Tunnel, philosopher Thomas Metzinger claims otherwise: No such thing as a self exists. The conscious self is the content of a model created by our brain—an internal image, but one we cannot experience as an image. Everything we experience is “a virtual self in a virtual reality.”But if the self is not “real,” why and how did it evolve? How does the brain construct it? Do we still have souls, free will, personal autonomy, or moral accountability? In a time when the science of cognition is becoming as controversial as evolution, The Ego Tunnel provides a stunningly original take on the mystery of the mind.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    How have we achieved so much despite understanding so little? Cognitive scientists Steven Sloman and Philip Fernbach argue that we survive and thrive despite our mental shortcomings because we live in a rich community of knowledge. The key to our intelligence lies in the people and things around us. We're constantly drawing on information and expertise stored outside our heads: in our bodies, our environment, our possessions, and the community with which we interact--and usually we don't even realize we're doing it. The human mind is both brilliant and pathetic. We have mastered fire, created democratic institutions, stood on the moon, and sequenced our genome. And yet each of us is error prone, sometimes irrational, and often ignorant. The fundamentally communal nature of intelligence and knowledge explains why we often assume we know more than we really do, why political opinions and false beliefs are so hard to change, and why individually oriented approaches to education and management frequently fail. But our collaborative minds also enable us to do amazing things. This book contends that true genius can be found in the ways we create intelligence using the world around us.

    In pursuit of these things, it is undeterred by emotion, fear, or morality. Dopamine is the source of our every urge, that little bit of biology that makes an ambitious business professional sacrifice everything in pursuit of success, or that drives a satisfied spouse to risk it all for the thrill of someone new. Simply put, it is why we seek and succeed; it is why we discover and prosper. Yet, at the same time, it’s why we gamble and squander. From dopamine’s point of view, it’s not the having that matters. It’s getting something—anything—that’s new. From this understanding—the difference between possessing something versus anticipating it—we can understand in a revolutionary new way why we behave as we do in love, business, addiction, politics, religion – and we can even predict those behaviors in ourselves and others. In The Molecule of More: How a Single Chemical in Your Brain Drives Love, Sex, and Creativity—and will Determine the Fate of the Human Race, George Washington University professor and psychiatrist Daniel Z. Lieberman, MD, and Georgetown University lecturer Michael E. Long present a potentially life-changing proposal: Much of human life has an unconsidered component that explains an array of behaviors previously thought to be unrelated, including why winners cheat, why geniuses often suffer with mental illness, why nearly all diets fail, and why the brains of liberals and conservatives really are different.

    There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter "Economic Reality" has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems."People sometimes ask me what they should read to find out about artificial intelligence. Herbert Simon's book The Sciences of the Artificial is always on the list I give them. Every page issues a challenge to conventional thinking, and the layman who digests it well will certainly understand what the field of artificial intelligence hopes to accomplish. I recommend it in the same spirit that I recommend Freud to people who ask about psychoanalysis, or Piaget to those who ask about child psychology: If you want to learn about a subject, start by reading its founding fathers." -- George A. Miller