Ryle's linguistic analysis remaps the conceptual geography of mind, not so much solving traditional philosophical problems as dissolving them into the mere consequences of misguided language. His plain language and esstentially simple purpose place him in the traditioin of Locke, Berkeley, Mill, and Russell.

    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.

    For over a century, a diverse array of researchers have been trying to find a language that can be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it.In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when bringing the abstract world of mathematical modelling into contact with the messy details of biology.Each chapter focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. Throughout Grace will look at the history of the field, starting with experiments done on neurons in frog legs at the turn of the twentieth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. She demonstrates the value of describing the machinery of neuroscience using the elegant language of mathematics, and reveals in full the remarkable fruits of this endeavour.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them. Deep Thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Drawing on his breakthrough research in comparative neuroscience, Terrence Deacon offers a wealth of insights into the significance of symbolic thinking: from the co-evolutionary exchange between language and brains over two million years of hominid evolution to the ethical repercussions that followed man's newfound access to other people's thoughts and emotions.Informing these insights is a new understanding of how Darwinian processes underlie the brain's development and function as well as its evolution. In contrast to much contemporary neuroscience that treats the brain as no more or less than a computer, Deacon provides a new clarity of vision into the mechanism of mind. It injects a renewed sense of adventure into the experience of being human.

    Blade Runner, The Matrix, Star Wars, Avatar, Star Trek, Ready Player One and Avengers show us futuristic worlds where holograms, intelligent robots, smart devices, virtual avatars, digital transactions, and universe-scale teleportation work together perfectly, somehow seamlessly combining the virtual and the physical with the mechanical and the biological. Science fiction has done an excellent job describing a vision of the future where the digital and physical merge naturally into one — in a way that just works everywhere, for everyone. However, none of these visionary fictional works go so far as to describe exactly how this would actually be accomplished. While it has inspired many of us to ask the question—How do we enable science fantasy to become....science fact? The Spatial Web achieves this by first describing how exponentially powerful computing technologies are creating a great “Convergence.” How Augmented and Virtual Reality will enable us to overlay our information and imaginations onto the world. How Artificial Intelligence will infuse the environments and objects around us with adaptive intelligence. How the Internet of Things and Robotics will enable our vehicles, appliances, clothing, furniture, and homes to become connected and embodied with the power to see, feel, hear, smell, touch and move things in the world, and how Blockchain and Cryptocurrencies will secure our data and enable real-time transactions between the human, machine and virtual economies of the future. The book then dives deeply into the challenges and shortcomings of the World Wide Web, the rise of fake news and surveillance capitalism in Web 2.0 and the risk of algorithmic terrorism and biological hacking and “fake-reality” in Web 3.0. It raises concerns about the threat that emerging technologies pose in the hands of rogue actors whether human, algorithmic, corporate or state-sponsored and calls for common sense governance and global cooperation. It calls for business leaders, organizations and governments to not only support interoperable standards for software code, but critically, for ethical, and social codes as well. Authors Gabriel René and Dan Mapes describe in vivid detail how a new “spatial” protocol is required in order to connect the various exponential technologies of the 21st century into an integrated network capable of tracking and managing the real-time activities of our cities, monitoring and adjusting the supply chains that feed them, optimizing our farms and natural resources, automating our manufacturing and distribution, transforming marketing and commerce, accelerating our global economies, running advanced planet-scale simulations and predictions, and even bridging the gap between our interior individual reality and our exterior collective one. Enabling the ability for humans, machines and AI to communicate, collaborate and coordinate activities in the world at a global scale and how the thoughtful application of these technologies could lead to an unprecedented opportunity to create a truly global “networked” civilization or "Smart World.” The book artfully shifts between cyberpunk futurism, cautionary tale-telling, and life-affirming call-to-arms. It challenges us to consider the importance of today’s technological choices as individuals, organizations, and as a species, as we face the historic opportunity we have to transform the web, the world, and our very definition of reality.

    Now in paperback, Dr Jeffrey Schwartz and Sharon Begley's groundbreaking work, The Mind and the Brain, argues exactly the opposite: that the mind has a life of its own.Dr Schwartz, a leading researcher in brain dysfunctions, and Wall Street Journal science columnist Sharon Begley demonstrate that the human mind is an independent entity that can shape and control the functioning of the physical brain. Their work has its basis in our emerging understanding of adult neuroplasticity–the brain's ability to be rewired not just in childhood, but throughout life, a trait only recently established by neuroscientists.Through decades of work treating patients with obsessive–compulsive disorder (OCD), Schwartz made an extraordinary finding: while following the therapy he developed, his patients were effecting significant and lasting changes in their own neural pathways. It was a scientific first: by actively focusing their attention away from negative behaviors and toward more positive ones, Schwartz's patients were using their minds to reshape their brains–and discovering a thrilling new dimension to the concept of neuroplasticity.The Mind and the Brain follows Schwartz as he investigates this newly discovered power, which he calls self–directed neuroplasticity or, more simply, mental force. It describes his work with noted physicist Henry Stapp and connects the concept of 'mental force' with the ancient practice of mindfulness in Buddhist tradition. And it points to potential new applications that could transform the treatment of almost every variety of neurological dysfunction, from dyslexia to stroke–and could lead to new strategies to help us harness our mental powers. Yet as wondrous as these implications are, perhaps even more important is the philosophical dimension of Schwartz's work. For the existence of mental force offers convincing scientific evidence of human free will, and thus of man's inherent capacity for moral choice.

    C. R. Licklider, whose visionary dream of a human-computer symbiosis transformed the course of modern science and led to the development of the personal computer. Reprint.

    Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.

    Dr. Oliver Sacks recounts the stories of patients struggling to adapt to often bizarre worlds of neurological disorder. Here are people who can no longer recognize everyday objects or those they love; who are stricken with violent tics or shout involuntary obscenities; who have been dismissed as autistic or retarded, yet are gifted with uncanny artistic or mathematical talents. If inconceivably strange, these brilliant tales illuminate what it means to be human.

    What is it like to try to heal the body when the mind is under attack? In this book, Dr. Allan Ropper and Brian Burrell take the reader behind the scenes at Harvard Medical School's neurology unit to show how a seasoned diagnostician faces down bizarre, life-altering afflictions. Like Alice in Wonderland, Dr. Ropper inhabits a world where absurdities abound:• A figure skater whose body has become a ticking time-bomb • A salesman who drives around and around a traffic rotary, unable to get off • A college quarterback who can't stop calling the same play • A child molester who, after falling on the ice, is left with a brain that is very much dead inside a body that is very much alive • A mother of two young girls, diagnosed with ALS, who has to decide whether a life locked inside her own head is worth livingHow does one begin to treat such cases, to counsel people whose lives may be changed forever? How does one train the next generation of clinicians to deal with the moral and medical aspects of brain disease? Dr. Ropper and his colleague answer these questions by taking the reader into a rarified world where lives and minds hang in the balance.

    Some philosophers argue that consciousness is something extra, beyond the physical workings of the brain. Others think that if we persist in our standard scientific methods, our questions about consciousness will eventually be answered. And some even suggest that the mystery is so deep, it will never be solved. Decades have been spent trying to explain consciousness from within our current scientific paradigm, but little progress has been made.Now, Philip Goff offers an exciting alternative that could pave the way forward. Rooted in an analysis of the philosophical underpinnings of modern science and based on the early twentieth-century work of Arthur Eddington and Bertrand Russell, Goff makes the case for panpsychism, a theory which posits that consciousness is not confined to biological entities but is a fundamental feature of all physical matter--from subatomic particles to the human brain. In Galileo's Error, he has provided the first step on a new path to the final theory of human consciousness.