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

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

    For the first time in history, the secrets of the living brain are being revealed by a battery of high tech brain scans devised by physicists. Now what was once solely the province of science fiction has become a startling reality. Recording memories, telepathy, videotaping our dreams, mind control, avatars, and telekinesis are not only possible; they already exist. The Future of the Mind gives us an authoritative and compelling look at the astonishing research being done in top laboratories around the world—all based on the latest advancements in neuroscience and physics. One day we might have a "smart pill" that can enhance our cognition; be able to upload our brain to a computer, neuron for neuron; send thoughts and emotions around the world on a "brain-net"; control computers and robots with our mind; push the very limits of immortality; and perhaps even send our consciousness across the universe. Dr. Kaku takes us on a grand tour of what the future might hold, giving us not only a solid sense of how the brain functions but also how these technologies will change our daily lives. He even presents a radically new way to think about "consciousness" and applies it to provide fresh insight into mental illness, artificial intelligence and alien consciousness. With Dr. Kaku's deep understanding of modern science and keen eye for future developments, The Future of the Mind is a scientific tour de force--an extraordinary, mind-boggling exploration of the frontiers of neuroscience.

    However, as the authors of this accessible guide demonstrate, there are at least some things we do understand about the brain, things which may lead us to think quite differently about the way we view ourselves and workings of our minds. Starting off with a brief tour of the history of neuroscience, from Aristotle's view that the function of the brain was to cool the heart to the ancient practice of drilling a hole in the skull to relieve headaches, the book covers all of the key areas - including the anatomy and development of the brain, the workings of the sensory and nervous systems, the function of sleep and the capacity for language - in a clear and comprehensible manner. The authors also consider the roots - and possible treatments - of some of the most common psychological disorders, and examine the way in which science may help us to find answers to philosophical questions about the nature of consciousness and the identity of the self. to be able to extend life well beyond the standard three score years and ten, this lively and entertaining introduction assumes no previous scientific knowledge and will be suitable for readers of all backgrounds.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective.Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.

    In the last century, there have been massive breakthroughs that have rewritten the science of the brain, and yet the puzzles faced by the ancient Greeks are still present. In The Consciousness Instinct, the neuroscience pioneer Michael S. Gazzaniga puts the latest research in conversation with the history of human thinking about the mind, giving a big-picture view of what science has revealed about consciousness.The idea of the brain as a machine, first proposed centuries ago, has led to assumptions about the relationship between mind and brain that dog scientists and philosophers to this day. Gazzaniga asserts that this model has it backward--brains make machines, but they cannot be reduced to one. New research suggests the brain is actually a confederation of independent modules working together. Understanding how consciousness could emanate from such an organization will help define the future of brain science and artificial intelligence and close the gap between brain and mind.Captivating and accessible, with insights drawn from a lifetime at the forefront of the field, The Consciousness Instinct sets the course for the neuroscience of tomorrow.

    The implications of this revolutionary scientific paradigm extend into virtually every aspect of our psychology, our history and culture, our religion -- and indeed our future.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    This report provides a brief yet comprehensive introduction to Python for engineers, researchers, and data scientists who are already familiar with another programming language.Author Jake VanderPlas, an interdisciplinary research director at the University of Washington, explains Python’s essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and more, using Python 3 syntax.You’ll explore:- Python syntax basics and running Python codeBasic semantics of Python variables, objects, and operators- Built-in simple types and data structures- Control flow statements for executing code blocks conditionally- Methods for creating and using reusable functionsIterators, list comprehensions, and generators- String manipulation and regular expressions- Python’s standard library and third-party modules- Python’s core data science tools- Recommended resources to help you learn more

    Evolutionary Dynamics is concerned with these equations of life. In this book, Martin A. Nowak draws on the languages of biology and mathematics to outline the mathematical principles according to which life evolves. His work introduces readers to the powerful yet simple laws that govern the evolution of living systems, no matter how complicated they might seem. Evolution has become a mathematical theory, Nowak suggests, and any idea of an evolutionary process or mechanism should be studied in the context of the mathematical equations of evolutionary dynamics. His book presents a range of analytical tools that can be used to this end: fitness landscapes, mutation matrices, genomic sequence space, random drift, quasispecies, replicators, the Prisoner's Dilemma, games in finite and infinite populations, evolutionary graph theory, games on grids, evolutionary kaleidoscopes, fractals, and spatial chaos. Nowak then shows how evolutionary dynamics applies to critical real-world problems, including the progression of viral diseases such as AIDS, the virulence of infectious agents, the unpredictable mutations that lead to cancer, the evolution of altruism, and even the evolution of human language. His book makes a clear and compelling case for understanding every living system--and everything that arises as a consequence of living systems--in terms of evolutionary dynamics.

    In 1935, aged 22, he developed the mathematical theory upon which all subsequent stored-program digital computers are modeled.At the outbreak of hostilities with Germany in September 1939, he joined the Government Codebreaking team at Bletchley Park, Buckinghamshire and played a crucial role in deciphering Engima, the code used by the German armed forces to protect their radio communications. Turing's work on the versionof Enigma used by the German navy was vital to the battle for supremacy in the North Atlantic. He also contributed to the attack on the cyphers known as Fish, which were used by the German High Command for the encryption of signals during the latter part of the war. His contribution helped toshorten the war in Europe by an estimated two years.After the war, his theoretical work led to the development of Britain's first computers at the National Physical Laboratory and the Royal Society Computing Machine Laboratory at Manchester University.Turing was also a founding father of modern cognitive science, theorizing that the cortex at birth is an unorganized machine which through training becomes organized into a universal machine or something like it. He went on to develop the use of computers to model biological growth, launchingthe discipline now referred to as Artificial Life.The papers in this book are the key works for understanding Turing's phenomenal contribution across all these fields. The collection includes Turing's declassified wartime Treatise on the Enigma; letters from Turing to Churchill and to codebreakers; lectures, papers, and broadcasts which opened upthe concept of AI and its implications; and the paper which formed the genesis of the investigation of Artifical Life.

    Some of these species can move and eat, see, reproduce, and die. Some behave like birds or ants. One such life form may turn out to be our best weapon in the war against AIDS.What these species have in common is that they exist inside computers, their DNA is digital, and they have come into being not through God's agency but through the efforts of a generation of scientists who seek to create life in silico.But even as it introduces us to these brilliant heretics and unravels the intricacies of their work. Artificial Life examines its subject's dizzying philosophical implications: Is a self-replicating computer program any less alive than a flu virus? Are carbon-and-water-based entities merely part of the continuum of living things? And is it possible that one day "a-life" will look back at human beings and dismiss us as an evolutionary way station -- or, worse still, a dead end?

    

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.