Somehow, within each of our brains, billions of neurons work to create our conscious experience. How does this happen? Why do we experience life in the first person? After over twenty years researching the brain, world-renowned neuroscientist Anil Seth puts forward a radical new theory of consciousness and self. His unique theory of what it means to 'be you' challenges our understanding of perception and reality and it turns what you thought you knew about yourself on its head.'Awe-inspiring and humane.' NEW STATESMAN (Books of the Year)'Fascinating.' FINANCIAL TIMES (Books of the Year)'Profound.' GUARDIAN (Books of the Year)'Brilliant.' CLAIRE TOMALIN, NEW YORK TIMES'Outstanding.' PSYCHOLOGY TODAY 'Amazing . . . a brilliant read.'RUSSELL BRAND'Beautifully written, crystal clear, deeply insightful.'DAVID EAGLEMAN, Pulitzer Prize-nominated author of Livewired'Offers us new cause for astonishment and wonder.'ANNAKA HARRIS, author of Conscious'A fascinating book. A joy to read.'NIGEL WARBURTON'Truly compelling.'PROFESSOR KARL FRISTON, Universty College London'A wonderfully accessible and comprehensive account.'SEAN CARROLL, author of Something Deeply Hidden

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    Kandel, whose remarkable scientific career and deep interest in art give him a unique perspective, demonstrates how science can inform the way we experience a work of art and seek to understand its meaning. Kandel illustrates how reductionism―the distillation of larger scientific or aesthetic concepts into smaller, more tractable components―has been used by scientists and artists alike to pursue their respective truths. He draws on his Nobel Prize-winning work revealing the neurobiological underpinnings of learning and memory in sea slugs to shed light on the complex workings of the mental processes of higher animals.In Reductionism in Art and Brain Science, Kandel shows how this radically reductionist approach, applied to the most complex puzzle of our time―the brain―has been employed by modern artists who distill their subjective world into color, form, and light. Kandel demonstrates through bottom-up sensory and top-down cognitive functions how science can explore the complexities of human perception and help us to perceive, appreciate, and understand great works of art. At the heart of the book is an elegant elucidation of the contribution of reductionism to the evolution of modern art and its role in a monumental shift in artistic perspective. Reductionism steered the transition from figurative art to the first explorations of abstract art reflected in the works of Turner, Monet, Kandinsky, Schoenberg, and Mondrian. Kandel explains how, in the postwar era, Pollock, de Kooning, Rothko, Louis, Turrell, and Flavin used a reductionist approach to arrive at their abstract expressionism and how Katz, Warhol, Close, and Sandback built upon the advances of the New York School to reimagine figurative and minimal art. Featuring captivating drawings of the brain alongside full-color reproductions of modern art masterpieces, this book draws out the common concerns of science and art and how they illuminate each other.

    They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work―and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities.While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human―and to crack the creativity code.

    This author presents a set of patterns that organize all the informal experience successful Smalltalk programmers have learned the hard way. When programmers understand these patterns, they can write much more effective code. The concept of Smalltalk patterns is introduced, and the book explains why they work. Next, the book introduces proven patterns for working with methods, messages, state, collections, classes and formatting. Finally, the book walks through a development example utilizing patterns. For programmers, project managers, teachers and students -- both new and experienced. This book presents a set of patterns that organize all the informal experience of successful Smalltalk programmers. This book will help you understand these patterns, and empower you to write more effective code.

    A powerful warning about the hidden dangers in today's fascination with the paranormal -- the angel phenomenon, spirit guides, UFOs, vampires, Ouija boards, fantasy games, and others.

    But with a typical price tag of $5,000 to $10,000 for a usability consultant to conduct each round of tests, it rarely happens. In this how-to companion to Don't Make Me Think: A Common Sense Approach to Web Usability, Steve Krug spells out an approach to usability testing that anyone can easily apply to their own web site, application, or other product. (As he said in Don't Make Me Think, "It's not rocket surgery".)In this new book, Steve explains how to: -Test any design, from a sketch on a napkin to a fully-functioning web site or application-Keep your focus on finding the most important problems (because no one has the time or resources to fix them all)-Fix the problems that you find, using his "The least you can do" approachBy pairing the process of testing and fixing products down to its essentials (A morning a month, that's all we ask ), Rocket Surgery makes it realistic for teams to test early and often, catching problems while it's still easy to fix them. Rocket Surgery Made Easy adds demonstration videos to the proven mix of clear writing, before-and-after examples, witty illustrations, and practical advice that made Don't Make Me Think so popular.

    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.

    You'll progress from a complete beginner regarding Arduino programming and electronics knowledge to intermediate skills and the confidence to create your own amazing Arduino projects. Absolutely no experience in programming or electronics required!Rather than requiring you to wade through pages of theory before you start making things, this book has a hands-on approach. You will dive into making projects right from the start, learning how to use various electronic components and how to program the Arduino to control or communicate with those components.Each project is designed to build upon the knowledge learned in earlier projects and to further your knowledge in programming as well as skills with electronics. By the end of the book you will be able create your own projects confidently and with creativity.Please note: the print version of this title is black & white; the eBook is full color. You can download the color diagrams in the book from http: //www.apress.com/9781430232407

    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.

    Its unique approach communicates the richness and diversity of CIS in a lucid and accessible format. This fully revised and updated second edition reinforces the view of CIS as a gateway to science and problem solving, sets out the scientific principles that govern its use, and describes the impact of people on its development, design, and success. The second edition of Geographic Information Systems and Science includes:A new five-part structure: Foundations; Principles; Techniques; Analysis; and Management and Policy.All-new personality boxes of current GIS practitioners.New real-world applications of GIS.New or expanded coverage of important current topics:Location-based servicesDistributed computingVirtual and augmented realitiesHomeland securityBusiness GIS and geodemographicsThe emergence of geoportalsGrand challenges of GIScienceA new suite of instructor and student resources http://www.wiley.com/go/longleyThe second edition of Geographic Information Systems and Science is essential reading for undergraduates taking courses in GIS within departments of Geography, Environmental Science, Business (and Public) Administration, Computer Science, Urban Studies, Planning, Information Science, Civil Engineering, and Archaeology. It is also provides a key resource for foundation GIS courses on taught MSc and other higher-degree programs. Professional users of GIS from governmental organizations and industries across the private sector will find this book an invaluable resource with a wealth of relevant applications.

    Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer winning in games like Jeopardy and go does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules. These approaches are too narrow to achieve genuine intelligence. The world we live in is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Marcus and Davis show us what we need to first accomplish before we get there and argue that if we are wise along the way, we won't need to worry about a future of machine overlords. If we heed their advice, humanity can create an AI that we can trust in our homes, our cars, and our doctor's offices. Reboot provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of what we can achieve and how AI can make our lives better.

    Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization’s massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It’s a big, big data world out there – let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

    Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught?   In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters."   In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.