By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

    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.

    In The Invisible Gorilla, Christopher Chabris and Daniel Simons, creators of one of psychology’s most famous experiments, use remarkable stories and counterintuitive scientific findings to demonstrate an important truth: Our minds don’t work the way we think they do. We think we see ourselves and the world as they really are, but we’re actually missing a whole lot.Again and again, we think we experience and understand the world as it is, but our thoughts are beset by everyday illusions. We write traffic laws and build criminal cases on the assumption that people will notice when something unusual happens right in front of them. We’re sure we know where we were on 9/11, falsely believing that vivid memories are seared into our minds with perfect fidelity. And as a society, we spend billions on devices to train our brains because we’re continually tempted by the lure of quick fixes and effortless self-improvement.  The Invisible Gorilla reveals the myriad ways that our intuitions can deceive us, but it’s much more than a catalog of human failings. Chabris and Simons explain why we succumb to these everyday illusions and what we can do to inoculate ourselves against their effects. Ultimately, the book provides a kind of x-ray vision into our own minds, making it possible to pierce the veil of illusions that clouds our thoughts and to think clearly for perhaps the first time.

    Indeed, the brain's power is being confirmed every day in new studies and research. But there is a brain we don't generally hear about, a brain we might not want to hear about…the "prima donna within."Exposing the mind's deceptions and exploring how the mind defends and glorifies the ego, Dr. Cordelia Fine illustrates the brain's tendency to self-delusion. Whether it be hindsight bias, wishful thinking, unrealistic optimism, or moral excuse-making, each of us has a slew of inborn mind-bugs and ordinary prejudices that prevent us from seeing the truth about the world and ourselves. With fascinating studies to support her arguments, Dr. Fine takes us on an insightful, rip-roaringly funny tour through the brain you never knew you had.

    It touches on its evolutionary development, its algorithmic nature and its scientific history by bridging ideas across Neuroscience, Computer Science, Biotechnology, Evolutionary History, Cognitive Science, Political Philosophy, and Artificial Intelligence.Never before had there been nearly as many scientists, resources or productive research focused on these topics, and humanity has achieved some understanding and some clarification. With the speed of progress it is timely to communicate an overreaching perspective, this book puts an emphasis on conveying the essential questions and what we know about their answers in a simple, clear and exciting way.Humans, along with the first RNA molecules, the first life forms, the first brains, the first conscious animals, the first societies and the first artificial agents constitute an amazing and crucial development in a path of increasingly complex computational intelligence. And yet, we occupy a minuscule time period in the history of Earth, a history that has been written by Genes, by Cultures and by Consciousnesses. If we abandon our anthropomorphic bias it becomes obvious that Humans are not so special after all. We are an important but short and transitory step among many others in a bigger story. The story of our computational minds, which is ours but not only ours. What is the relationship between computation, cognition and everything else? What is life and how did it originate? What is the role of culture in human minds? What do we know about the algorithmic nature of the mind, can we engineer it? What is the computational explanation of consciousness? What are some possible future steps in the evolution of minds? The underlying thread is the computational nature of the Mind which results from the mixture of Genes, Cultures and Consciousness. While these three interact in complex ways, they are ultimately computational systems on their own which appeared at different stages of history and which follow their own selective processes operating at different time scales. As technology progresses, the distinction between the three components materializes and will be a key determinant of the future.Among the many topics covered are the origin of life, the concept of computation and its relation to Turing Machines, cultural evolution and the notion of a Selfish Meme, free will and determinism, moral relativity, the hard problem of consciousness, the different theories of concepts from the perspective of cognitive science, the current status of AI and Machine Learning including the symbolic vs sub-symbolic dichotomy, the contrast between logical reasoning and neural networks, and the recent history of Deep Learning, Geoffrey Hinton, DeepMind and its algorithm AlphaGo. It also develops on the history of science and looks into the possible future building on the work of authors like Daniel Dennett, Yuval Harari, Richard Dawkins, Francis Crick, George Church, David Chalmers, Susan Carey, Stanislas Dehaene, Robert Boyd, Joseph Henrich, Daniel Kahneman, Moran Cerf, Josh Tenenbaum, David Deutsch, Steven Pinker, Ray Kurzweil, John von Neumann, Herbert Simon and many more. Andres Campero is a researcher and PhD student at the Brain and Cognitive Sciences Department and at the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT).

    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.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    But humans are more than computers, and the cutting-edge research in cognitive science is increasingly focused on the more mysterious, creative aspects of the mind. The Way We Think is a landmark synthesis that exemplifies this new direction. The theory of conceptual blending is already widely known in laboratories throughout the world; this book is its definitive statement. Gilles Fauconnier and Mark Turner argue that all learning and all thinking consist of blends of metaphors based on simple bodily experiences. These blends are then themselves blended together into an increasingly rich structure that makes up our mental functioning in modern society. A child's entire development consists of learning and navigating these blends. The Way We Think shows how this blending operates; how it is affected by (and gives rise to) language, identity, and concept of category; and the rules by which we use blends to understand ideas that are new to us. The result is a bold, exciting, and accessible new view of how the mind works.

    These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation.

    It discusses neuroanatomy, cell and molecular mechanisms and signaling through a cognitive approach to behaviour. It features an expanded treatment of the nervous system, neurological and psychiatric diseases and perception.

    In a book of unprecedented scope, McGilchrist draws on a vast body of recent brain research, illustrated with case histories, to reveal that the difference is profound—not just this or that function, but two whole, coherent, but incompatible ways of experiencing the world. The left hemisphere is detail oriented, prefers mechanisms to living things & is inclined to self-interest. The right hemisphere has greater breadth, flexibility & generosity. This division helps explain the origins of music & language, & casts new light on the history of philosophy, as well as on some mental illnesses. The 2nd part of the book takes a journey thru the history of Western culture, illustrating the tension between these two worlds as revealed in the thought & belief of thinkers & artists, from Aeschylus to Magritte. He argues that, despite its inferior grasp of reality, the left hemisphere is increasingly taking precedence in the modern world, with potentially disastrous consequences.List of IllustrationsAcknowledgmentsIntroductionAsymmetry and the brain --What do the two hemispheres 'do'? --Language, truth and music --The nature of the two worlds --The primacy of the right hemisphere --The triumph of the left hemisphere --Imitation and the evolution of culture --The ancient world --The Renaissance and the Reformation --The Enlightenment --Romanticism and the Industrial Revolution --The modern and post-modern worldsConclusionNotes BibliographyIndex

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

     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.

    A classic text by the author who developed ELIZA, a natural-language processing system.

    It is the Second Coming and the Apocalypse at the same time: Good AI versus evil AI." --John BrockmanMore than sixty years ago, mathematician-philosopher Norbert Wiener published a book on the place of machines in society that ended with a warning: "we shall never receive the right answers to our questions unless we ask the right questions.... The hour is very late, and the choice of good and evil knocks at our door."In the wake of advances in unsupervised, self-improving machine learning, a small but influential community of thinkers is considering Wiener's words again. In Possible Minds, John Brockman gathers their disparate visions of where AI might be taking us.The fruit of the long history of Brockman's profound engagement with the most important scientific minds who have been thinking about AI--from Alison Gopnik and David Deutsch to Frank Wilczek and Stephen Wolfram--Possible Minds is an ideal introduction to the landscape of crucial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, notably robotics entrepreneur Rodney Brooks, philosopher Daniel Dennett, and bestselling author Steven Pinker, have a very different view. Serious, searching and authoritative, Possible Minds lays out the intellectual landscape of one of the most important topics of our time.