But even though Moravec predicts the end of the domination by human beings, his is not a bleak vision. Far from railing against a future in which machines rule the world, Moravec embraces it, taking the startling view that intelligent robots will actually be our evolutionary heirs. Intelligent machines, which will grow from us, learn our skills, and share our goals and values, can be viewed as children of our minds. And since they are our children, we will want them to outdistance us. In fact, in a bid for immortality, many of our descendants will choose to transform into ex humans, as they upload themselves into advanced computers.This provocative new book, the highly anticipated follow-up to his bestselling volume Mind Children, charts the trajectory of robotics in breathtaking detail. A must read for artificial intelligence, technology, and computer enthusiasts, Moravec's freewheeling but informed speculations present a future far different than we ever dared imagine.

    Disciples of Darwin have explained how natural selection produced plants, but what about the human mind?In From Bacteria to Bach and Back, Daniel C. Dennett builds on recent discoveries from biology and computer science to show, step by step, how a comprehending mind could in fact have arisen from a mindless process of natural selection. A crucial shift occurred when humans developed the ability to share memes, or ways of doing things not based in genetic instinct. Competition among memes produced thinking tools powerful enough that our minds don’t just perceive and react, they create and comprehend.An agenda-setting book for a new generation of philosophers and scientists, From Bacteria to Bach and Back will delight and entertain all those curious about how the mind works.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

    The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include:how intelligence can be defined whether machines can 'think' sensory input in machine systems the nature of consciousness the controversial culturing of human neurons.Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.

    You'll learn how to install, configure, operate, manage, and secure the latest release.Covers all the new features and capabilities of the much-anticipated new release of VMware vSphere Discusses the planning, installation, operation, and management for the latest release Reviews migration to the latest vSphere software Offers hands-on instruction and clear explanations with real-world examples Mastering VMware vSphere is the strategic guide you need to maximize the opportunities of virtualization.

    

    A binge drinking session is just the thing to allow Gallegher's brilliant subconscious to emerge and save the day, but what weird critter keeps stealing all the liquor?

    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.

    It is offered for sale in print format as a convenience.Get a head start evaluating Windows Azure - with technical insights from a Microsoft MVP Mitch Tulloch. This guide introduces the latest features and capabilities, with scenario-based advice on how the platform can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now.Topics include: Understanding Windows Azure Windows Azure Compute Services Windows Azure Network Services Windows Azure Data Services Windows Azure App Services Getting Started with Windows Azure

    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.

    Gershenfeld offers a glimpse at the brave new post-computerized world, where microchips work for us instead of against us. He argues that we waste the potential of the microchip when we confine it to a box on our desk: the real electronic revolution will come when computers have all but disappeared into the walls around us. Imagine a digital book that looks like a traditional book printed on paper and is pleasant to read in bed but has all the mutability of a screen display. How about a personal fabricator that can organize digitized atoms into anything you want, or a musical keyboard that can be woven into a denim jacket? Gershenfeld tells the story of his Things that Think group at MIT's Media Lab, the group of innovative scientists and researchers dedicated to integrating digital technology into the fabric of our lives.

    Acclaimed technologist and inventor Amir Husain explains how we can live amidst the coming age of sentient machines and artificial intelligence—and not only survive, but thrive.Artificial “machine” intelligence is playing an ever-greater role in our society. We are already using cruise control in our cars, automatic checkout at the drugstore, and are unable to live without our smartphones. The discussion around AI is polarized; people think either machines will solve all problems for everyone, or they will lead us down a dark, dystopian path into total human irrelevance. Regardless of what you believe, the idea that we might bring forth intelligent creation can be intrinsically frightening. But what if our greatest role as humans so far is that of creators? Amir Husain, a brilliant inventor and computer scientist, argues that we are on the cusp of writing our next, and greatest, creation myth. It is the dawn of a new form of intellectual diversity, one that we need to embrace in order to advance the state of the art in many critical fields, including security, resource management, finance, and energy. “In The Sentient Machine, Husain prepares us for a brighter future; not with hyperbole about right and wrong, but with serious arguments about risk and potential” (Dr. Greg Hyslop, Chief Technology Officer, The Boeing Company). He addresses broad existential questions surrounding the coming of AI: Why are we valuable? What can we create in this world? How are we intelligent? What constitutes progress for us? And how might we fail to progress? Husain boils down complex computer science and AI concepts into clear, plainspoken language and draws from a wide variety of cultural and historical references to illustrate his points. Ultimately, Husain challenges many of our societal norms and upends assumptions we hold about “the good life.”

    It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills—and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These “bots” started with human programming and logic, but now their reach extends beyond what their creators ever expected. In this fascinating, frightening book, Christopher Steiner tells the story of how algorithms took over—and shows why the “bot revolution” is about to spill into every aspect of our lives, often silently, without our knowledge. The May 2010 “Flash Crash” exposed Wall Street’s reliance on trading bots to the tune of a 998-point market drop and $1 trillion in vanished market value. But that was just the beginning. In Automate This, we meet bots that are driving cars, penning haiku, and writing music mistaken for Bach’s. They listen in on our customer service calls and figure out what Iran would do in the event of a nuclear standoff. There are algorithms that can pick out the most cohesive crew of astronauts for a space mission or identify the next Jeremy Lin. Some can even ingest statistics from baseball games and spit out pitch-perfect sports journalism indistinguishable from that produced by humans. The interaction of man and machine can make our lives easier. But what will the world look like when algorithms control our hospitals, our roads, our culture, and our national security? What hap­pens to businesses when we automate judgment and eliminate human instinct? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?  Who knows—maybe there’s a bot learning to do your job this minute.

    Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. Richly illustrated, Complexity: A Guided Tour--winner of the 2010 Phi Beta Kappa Book Award in Science--offers a wide-ranging overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for its contribution to solving some of the most important scientific questions of our time.

    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.