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Valiant's theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life's complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003eUsed Book in Good Condition\u003c\/li\u003e\u003c\/ul\u003e\n        ","brand":"Basic Books","offers":[{"title":"Default Title","offer_id":51281833427232,"sku":"NEW0465032710","price":28.38,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/31K3j6Me6AL.jpg?v=1772376097"},{"product_id":"our-final-invention-artificial-intelligence-and-the-end-of-1250058783","title":"Our Final Invention: Artificial Intelligence and the End of","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 1250058783\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Barrat, James\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eElon Musk named Our Final Invention one of 5 books everyone should read about the futureA Huffington Post Definitive Tech Book of 2013In as little as a decade, artificial intelligence could match and then surpass human intelligence. 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He succeeds well in choosing the topics - both theory and practice - that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.\"Aur?ien G?on, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: \"The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesnt hesitate to go into the math equations: thats one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field.\"Karolis Urbonas, Head of Data Science at Amazon: \"A great introduction to machine learning from a world-class practitioner.\"Chao Han, VP, Head of R\u0026amp;D at Lucidworks: \"I wish such a book existed when I was a statistics graduate student trying to learn about machine learning.\"Sujeet Varakhedi, Head of Engineering at eBay: \"Andriys book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: \"A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.Vincent Pollet, Head of Research at Nuance: \"The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning.Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: \"This is a compact ?ow to do data science?manual and I predict it will become a go-to resource for academics and practitioners alike. At 100 pages (or a little more), the book is short enough to read in a single sitting. Yet, despite its length, it covers all the major machine learning approaches, ranging from classical linear and logistic regression, through to modern support vector machines, deep learning, boosting, and random forests. There is also no shortage of details on the various approaches and the interested reader can gain further information on any particular method via the innovative companion book wiki. The book does not assume any high level mathematical or statistical training or even programming experience, so should be accessible to almost anyone willing to invest the time to learn about these methods. It should certainly be required reading for anyone starting a PhD program in this area and will serve as a useful reference as they progress further. Finally, the book illustrates some of the algorithms using Python code, one of the most popular coding languages for machine learning. 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This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform.GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone.This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research. Presents a concise but sufficient introduction to general-purpose GPU computing which can help the layman become familiar with this emerging computing technique Describes implementation details, such as parallel models and performance metrics, so readers can easily utilize the techniques to accelerate their algorithmic programs Appeals to readers from the domain of high performance computing (HPC) who will find the relatively young research domain of swarm intelligence very interesting Includes many real-world applications, which can be of great help in deciding whether or not swarm intelligence algorithms or GPGPU is appropriate for the task at hand\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Miakarts Books","offers":[{"title":"Default Title","offer_id":51286431826208,"sku":null,"price":59.51,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/71qbzTZkAgL.jpg?v=1772478279"},{"product_id":"my-mother-was-a-computer-digital-subjects-and-literary-text-0226321479","title":"My Mother Was a Computer: Digital Subjects and Literary Text","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0226321479\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Hayles, N. 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My Mother Was a Computer gives us the tools necessary to make sense of these complex relationships. Hayles argues that we live in an age of intermediation that challenges our ideas about language, subjectivity, literary objects, and textuality. This process of intermediation takes place where digital media interact with cultural practices associated with older media, and here Hayles sharply portrays such interactions: how code differs from speech; how electronic text differs from print; the effects of digital media on the idea of the self; the effects of digitality on printed books; our conceptions of computers as living beings; the possibility that human consciousness itself might be computational; and the subjective cosmology wherein humans see the universe through the lens of their own digital age.We are the children of computers in more than one sense, and no critic has done more than N. Katherine Hayles to explain how these technologies define us and our culture. Heady and provocative, My Mother Was a Computer will be judged as her best work yet.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"University of Chicago Press","offers":[{"title":"Default Title","offer_id":51290738983200,"sku":"NEW0226321479","price":93.33,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/31mbD4DIuqL.jpg?v=1772563523"},{"product_id":"artificial-intelligence-a-systems-approach-from-architectur-0262048981","title":"Artificial Intelligence: A Systems Approach from Architectur","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0262048981\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Martinez, David R.\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eThe first text to take a systems engineering approach to artificial intelligence (AI), from architecture principles to the development and deployment of AI capabilities.Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book.Key features:In-depth look at modern computing technologies Systems engineering description and means to successfully undertake an AI product or service development through deployment Existing methods for applying machine learning operations (MLOps) AI system architecture including a description of each of the AI pipeline building blocks Challenges and approaches to attend to responsible AI in practice Tools to develop a strategic roadmap and techniques to foster an innovative team environment Multiple use cases that stem from the authors MIT classes, as well as from AI practitioners, AI project managers, early-career AI team leaders, technical executives, and entrepreneurs Exercises and Jupyter notebook examples\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"MIT Press","offers":[{"title":"Default Title","offer_id":51290995884320,"sku":"NEW0262048981","price":88.88,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/616v3GJEDDL.jpg?v=1772566278"},{"product_id":"signals-and-boundaries-building-blocks-for-complex-adaptive-0262525933","title":"Signals and Boundaries: Building Blocks for Complex Adaptive","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0262525933\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Holland, John H.\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eAn overarching framework for comparing and steering complex adaptive systems is developed through understanding the mechanisms that generate their intricate signal\/boundary hierarchies.Complex adaptive systems (cas), including ecosystems, governments, biological cells, and markets, are characterized by intricate hierarchical arrangements of boundaries and signals. In ecosystems, for example, niches act as semi-permeable boundaries, and smells and visual patterns serve as signals; governments have departmental hierarchies with memoranda acting as signals; and so it is with other cas. Despite a wealth of data and descriptions concerning different cas, there remain many unanswered questions about \"steering\" these systems. In Signals and Boundaries, John Holland argues that understanding the origin of the intricate signal\/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering cas through the mechanisms that generate their signal\/boundary hierarchies.Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal\/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"MIT Press","offers":[{"title":"Default Title","offer_id":51291038712096,"sku":"NEW0262525933","price":23.12,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/71tj_MxZ-6L.jpg?v=1772566913"},{"product_id":"mind-design-ii-philosophy-psychology-and-artificial-intel-0262581531","title":"Mind Design II: Philosophy, Psychology, and Artificial Intel","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0262581531\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Haugeland, John\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eMind design is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Unlike traditional empirical psychology, it is more oriented toward the \"how\" than the \"what.\" An experiment in mind design is more likely to be an attempt to build something and make it work-as in artificial intelligence-than to observe or analyze what already exists. Mind design is psychology by reverse engineering.When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's \"Computing Machinery and Intelligence\") and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are \"philosophical\" in that they address fundamental issues and concepts; and all are \"scientific\" in that they are technically sophisticated and concerned with concrete empirical research.ContributorsRodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"MIT Press","offers":[{"title":"Default Title","offer_id":51291275723040,"sku":"NEW0262581531","price":31.1,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/71QFFnXcD0L.jpg?v=1772570367"},{"product_id":"logic-primer-2nd-edition-by-allen-colin-0262511266","title":"Logic Primer - 2nd Edition by Allen, Colin","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0262511266\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Allen, Colin\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eLogic Primer presents a rigorous introduction to natural deduction systems of sentential and first-order logic.Logic Primer presents a rigorous introduction to natural deduction systems of sentential and first-order logic. The text is designed to foster the student-instructor relationship. The key concepts are laid out in concise definitions and comments, with the expectation that the instructor will elaborate upon them. New to the second edition is the addition of material on the logic of identity in chapters 3 and 4. An innovative interactive Web site, consisting of a \"Logic Daemon\" and a \"Quizmaster,\" encourages students to formulate their own proofs and links them to appropriate explanations in the book.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"A Bradford Book","offers":[{"title":"Default Title","offer_id":51291415118112,"sku":"NEW0262511266","price":63.91,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/61EQHwRXl6L.jpg?v=1772571537"},{"product_id":"you-look-like-a-thing-and-i-love-you-how-artificial-intelli-0316525243","title":"You Look Like a Thing and I Love You: How Artificial Intelli","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0316525243\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Shane, Janelle\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eAs heard on NPR's \"Science Friday,\" discover the book recommended by Malcolm Gladwell, Susan Cain, Daniel Pink, and Adam Grant: an \"affectionately down-to-earth to the year's most hype-prone field of tech\" (theverge.com).\"You look like a thing and I love you\" is one of the best pickup lines ever . . . 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.\"I can't think of a better way to learn about artificial intelligence, and I've never had so much fun along the way.\" -Adam Grant, New York Times bestselling author of Originals\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Voracious","offers":[{"title":"Default Title","offer_id":51292360311072,"sku":"NEW0316525243","price":28.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/71cNXEEbmEL.jpg?v=1772587574"},{"product_id":"geometric-fundamentals-of-robotics-monographs-in-computer-s-0387208747","title":"Geometric Fundamentals of Robotics (Monographs in Computer S","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0387208747\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Selig, J.M.\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eGeometric Fundamentals of Robotics provides an elegant introduction to the geometric concepts that are important to applications in robotics. This second edition is still unique in providing a deep understanding of the subject: rather than focusing on computational results in kinematics and robotics, it includes significant state-of-the-art material that reflects important advances in the field, connecting robotics back to mathematical fundamentals in group theory and geometry.Geometric Fundamentals of Robotics serves a wide audience of graduate students as well as researchers in a variety of areas, notably mechanical engineering, computer science, and applied mathematics. It is also an invaluable reference text.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Springer","offers":[{"title":"Default Title","offer_id":51292818964768,"sku":"NEW0387208747","price":77.51,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/51nZS0eRJ0L.jpg?v=1772595577"},{"product_id":"logic-for-applications-texts-in-computer-science-by-nerode-0387948937","title":"Logic for Applications (Texts in Computer Science) by Nerode","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0387948937\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Nerode, Anil\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eIn writing this book, our goal was to produce a text suitable for a first course in mathematical logic more attuned than the traditional textbooks to the re cent dramatic growth in the applications oflogic to computer science. Thus, our choice oftopics has been heavily influenced by such applications. Of course, we cover the basic traditional topics: syntax, semantics, soundnes5, completeness and compactness as well as a few more advanced results such as the theorems of Skolem-Lowenheim and Herbrand. Much ofour book, however, deals with other less traditional topics. Resolution theorem proving plays a major role in our treatment of logic especially in its application to Logic Programming and PRO LOG. We deal extensively with the mathematical foundations ofall three ofthese subjects. In addition, we include two chapters on nonclassical logics - modal and intuitionistic - that are becoming increasingly important in computer sci ence. We develop the basic material on the syntax and semantics (via Kripke frames) for each of these logics. In both cases, our approach to formal proofs, soundness and completeness uses modifications of the same tableau method in troduced for classical logic. We indicate how it can easily be adapted to various other special types of modal logics. A number of more advanced topics (includ ing nonmonotonic logic) are also briefly introduced both in the nonclassical logic chapters and in the material on Logic Programming and PROLOG.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Springer","offers":[{"title":"Default Title","offer_id":51301386125600,"sku":"NEW0387948937","price":152.2,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/61E4b-RB7yL.jpg?v=1772726897"},{"product_id":"scaling-up-machine-learning-parallel-and-distributed-approa-0521192242","title":"Scaling up Machine Learning: Parallel and Distributed Approa","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0521192242\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Bekkerman, Ron\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003eThis book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs, and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce, and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised, and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algorithms and deep dives into several applications make the book equally useful for researchers, students, and practitioners.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Miakarts Books","offers":[{"title":"Default Title","offer_id":51303177421088,"sku":null,"price":85.26,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/61e_tbDqXlL.jpg?v=1772747076"},{"product_id":"human-compatible-artificial-intelligence-and-the-problem-of-0525558616","title":"Human Compatible: Artificial Intelligence and the Problem of","description":"\n        \u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0525558616\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Russell, Stuart\u003c\/p\u003e\n        \u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\n        \u003cp\u003e\"The most important book on AI this year.\" --The Guardian\"Mr. Russell's exciting book goes deep, while sparkling with dry witticisms.\" --The Wall Street Journal\"The most important book I have read in quite some time\" (Daniel Kahneman); \"A must-read\" (Max Tegmark); \"The book we've all been waiting for\" (Sam Harris)A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machinesIn the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable.In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage.If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.\u003c\/p\u003e\n        \u003cul\u003e\u003cli\u003e\u003c\/ul\u003e\n        ","brand":"Miakarts Books","offers":[{"title":"Default Title","offer_id":51305138061600,"sku":null,"price":56.35,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/71h9jhxr7vL.jpg?v=1772751421"},{"product_id":"jessie-willcox-smith-by-schnessel-s-michael-0690014937","title":"Jessie Willcox Smith by Schnessel, S. Michael","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0690014937\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Schnessel, S. Michael\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e new\u003c\/p\u003e\u003cp\u003eJessie Willcox Smith was the creator of the ideal child. In over 40 illustrated books and in hundreds of magazine illustrations and covers she pictured a child that was without equal in reality - innocent, unblemished, never naughty, always perfect. Smith's touching, sensitive portraits of children at play won the hearts of millions of Americans in the early part of this century, just as her works are once again captivating collectors today.\u003c\/p\u003e\u003cul\u003e\u003cli\u003eUsed Book in Good Condition\u003c\/li\u003e\u003c\/ul\u003e","brand":"Brand: Crowell","offers":[{"title":"Default Title","offer_id":51305600188704,"sku":"NEW0690014937","price":66.68,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/81Z3kB2svyL.jpg?v=1785790858"},{"product_id":"math-into-latex-0817641319","title":"Math Into LaTeX","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0817641319\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e George Gr\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e New\u003c\/p\u003e\u003cp\u003eA new chapter \"A Visual Introduction to MikTeX,\" an open source implementation of TeX and LaTeX for Windows operating systemsAnother new chapter describing amsrefs, a simpler method for formatting references that incorporates and replaces BibTeX dataIntegrates a major revision to the amsart document class, along with updated examples\u003c\/p\u003e","brand":"Birkh","offers":[{"title":"Default Title","offer_id":51310350893344,"sku":"NEW0817641319","price":111.11,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/717ZqE3xqHL.jpg?v=1772825991"},{"product_id":"machine-intelligence-perspectives-on-the-computational-model-artificial-intelligence-and-cognitive-science-conceptual-issues-0815327684","title":"Machine Intelligence: Perspectives on the Computational Model (Artificial Intelligence and Cognitive Science: Conceptual Issues)","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0815327684\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Clark, Andy\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e New\u003c\/p\u003e\u003cp\u003eSummarizes and illuminates two decades of researchGathering important papers by both philosophers and scientists, this collection illuminates the central themes that have arisen during the last two decades of work on the conceptual foundations of artificial intelligence and cognitive science. Each volume begins with a comprehensive introduction that places the coverage in a broader perspective and links it with material in the companion volumes. The collection is of interest in many disciplines including computer science, linguistics, biology, information science, psychology, neuroscience, iconography, and philosophy.Examines initial efforts and the latest controversiesThe topics covered range from the bedrock assumptions of the computational approach to understanding the mind, to the more recent debates concerning cognitive architectures, all the way to the latest developments in robotics, artificial life, and dynamical systems theory. The collection first examines the lineage of major research programs, beginning with the basic idea of machine intelligence itself, then focuses on specific aspects of thought and intelligence, highlighting the much-discussed issue of consciousness, the equally important, but less densely researched issue of emotional response, and the more traditionally philosophical topic of language and meaning.Provides a gamut of perspectivesThe editors have included several articles that challenge crucial elements of the familiar research program of cognitive science, as well as important writings whose previous circulation has been limited. Within each volume the papers are organized to reflect a variety of research programs and issues. The substantive introductions that accompany each volume further organize the material and provide readers with a working sense of the issues and the connection between articles.\u003c\/p\u003e","brand":"Routledge","offers":[{"title":"Default Title","offer_id":51310365933856,"sku":"NEW0815327684","price":212.21,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0980\/7426\/3840\/files\/411_i8M2SSL.jpg?v=1772826362"},{"product_id":"artificial-intelligence-engines-a-tutorial-introduction-to-the-mathematics-of-deep-learning-0956372813","title":"Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning","description":"\u003cp\u003e\u003cstrong\u003eISBN:\u003c\/strong\u003e 0956372813\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor:\u003c\/strong\u003e Stone, James V\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e New\u003c\/p\u003e\u003cp\u003e\"authoritative, funny, and concise\" Steven Strogatz, Professor of Applied Mathematics, Cornell University.The brain has always had a fundamental advantage over conventional computers: it can learn. However, a new generation of artificial intelligence algorithms, in the form of deep neural networks, is rapidly eliminating that advantage. Deep neural networks rely on adaptive algorithms to master a wide variety of tasks, including cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, backgammon and Go, at super-human levels of performance. In this richly illustrated book, key neural network learning algorithms are explained informally first, followed by detailed mathematical analyses. Topics include both historically important neural networks (perceptrons, Hopfield nets, Boltzmann machines and backpropagation networks), and modern deep neural networks (variational autoencoders, convolutional networks, generative adversarial networks, and reinforcement learning using SARSA and Q-learning). Online computer programs, collated from open source repositories, give hands-on experience of neural networks, and PowerPoint slides provide support for teaching. 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