The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible.

    Yet, despite the astonishing discoveries of science, we still have only the vaguest idea of how the brain works. In The Idea of the Brain, scientist and historian Matthew Cobb traces how our conception of the brain has evolved over the centuries. Although it might seem to be a story of ever-increasing knowledge of biology, Cobb shows how our ideas about the brain have been shaped by each era's most significant technologies. Today we might think the brain is like a supercomputer. In the past, it has been compared to a telegraph, a telephone exchange, or some kind of hydraulic system. What will we think the brain is like tomorrow, when new technology arises? The result is an essential read for anyone interested in the complex processes that drive science and the forces that have shaped our marvelous brains.

    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).

    Michael Paul Mason is one of an elite group of experts who coordinate care in the complicated aftermath of tragic injuries that can last a lifetime. On the road with Mason, we encounter survivors of brain injuries as they struggle to map and make sense of the new worlds they inhabit.

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    Widely accepted as the authoritative text and reference on electronic circuit design, both analog and digital, this book revolutionized the teaching of electronics by emphasizing the methods actually used by circuit designers -- a combination of some basic laws, rules of thumb, and a large bag of tricks. The result is a largely nonmathematical treatment that encourages circuit intuition, brainstorming, and simplified calculations of circuit values and performance. The new Art of Electronics retains the feeling of informality and easy access that helped make the first edition so successful and popular. It is an ideal first textbook on electronics for scientists and engineers and an indispensable reference for anyone, professional or amateur, who works with electronic circuits.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    It avoids overburdening the reader with topographical detail that is unnecessary for the medical student. Minimum assumptions are made of existing knowledge of the subject.'Key point' boxes for reinforcement and quick revision Glossary of important terms 'Clinical detail' boxes closely integrated with relevant neuroanatomyComplete revision and updating of text. Revision nad expansion of summary chapter, providing overview of entire subject. Clinical material updated to reflect current prevalence of neurological disease. Artwork entirely redrawn for improved clarity and closer integration with text.

    Thoroughly updated to include Java 6, the Third Edition of Horstmann's bestselling text helps you absorb computing concepts and programming principles, develop strong problem-solving skills, and become a better programmer, all while exploring the elements of Java that are needed to write real-life programs. A top-notch introductory text for beginners, Big Java, Third Edition is also a thorough reference for students and professionals alike to Java technologies, Internet programming, database access, and many other areas of computer science.Features of the Third Edition: The 'Objects Gradual' approach leads you into object-oriented thinking step-by-step, from using classes, implementing simple methods, all the way to designing your own object-oriented programs. A strong emphasis on test-driven development encourages you to consider outcomes as you write programming code so you design better, more usable programs Helpful "Testing Track" introduces techniques and tools step by step, ensuring that you master one before moving on to the next New teaching and learning tools in WileyPLUS--including a unique assignment checker that enables you to test your programming problems online before you submit them for a grade Graphics topics are developed gradually throughout the text, conveniently highlighted in separate color-coded sections Updated coverage is fully compatible with Java 5 and includes a discussion of the latest Java 6 features

    This began to change with the devising of methods to try to tap into what was going on in the 'black box' of the mind, and the development of 'cognitive psychology'. With the study of patients who had suffered brain damage or injury to limited parts of the brain, outlines of brain components and processes began to take shape, and by the end of the 1970s, a new science, cognitive neuroscience, was born. But it was with the development of ways of accessing activation of the working brain using imaging techniques such as PET and fMRI that cognitive neuroscience came into its own, as a science cutting across psychology and neuroscience, with strong connections to philosophy of mind. Experiments involving subjects in scanners while doing various tasks, thinking, problem solving, and remembering are shedding light on the brain processes involved. The research is exciting and new, and often makes media headlines. But there is much misunderstanding about what brain imaging tells us, and the interpretation of studies on cognition.In this Very Short Introduction Richard Passingham, a distinguished cognitive neuroscientist, gives a provocative and exciting account of the nature and scope of this relatively new field, and the techniques available to us, focusing on investigation of the human brain. He explains what brain imaging shows, pointing out common misconceptions, and gives a brief overview of the different aspects of human cognition: perceiving, attending, remembering, reasoning, deciding, and acting. Passingham concludes with a discussion of the exciting advances that may lie ahead.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

    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.

    Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide. THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains: * a complete hypertext version of the full printed book. * the source code and URLs for all cited implementations. * over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Though referenced like a work of research, Brizedine's writing style is fully accessible. Brizendine provides a fascinating look at the life cycle of the female brain from birth ("baby girls will connect emotionally in ways that baby boys don't") to birthing ("Motherhood changes you because it literally alters a woman's brain-structurally, functionally, and in many ways, irreversibly") to menopause (when "the female brain is nowhere near ready to retire") and beyond. At the same time, Brizedine is not above reviewing the basics: "We may think we're a lot more sophisticated than Fred or Wilma Flintstone, but our basic mental outlook and equipment are the same." While this book will be of interest to anyone who wonders why men and women are so different, it will be particularly useful for women and parents of girls.

    Gravetter, and co-author Lori-Ann B. Forzano have written a text for research methods that helps you see how interesting and exciting experimental and non-experimental research can be. Inviting and conversational, RESEARCH METHODS FOR THE BEHAVIORAL SCIENCES, Third Edition, leads you through the research process from start to finish. The text opens with tips and strategies for generating research ideas, moves to selecting measures and participants, and then offers an examination of research strategy and design. This step-by-step approach emphasizes the decisions researchers must make at each stage of the process. The authors avoid a "cookbook" approach to the facts by linking terminology with applied concepts; their "lecture in a book" style emphasizes discussion and explanation of topics. Each chapter ends with a set of exercises and activities.