Download or read book Machine Decision Is Not Final written by Benjamin H. Bratton and published by MIT Press. This book was released on 2024-07-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An interdisciplinary, cross-cultural collection that decenters familiar narratives to provide a fresh perspective on what artificial intelligence is today, and what it might become. Historians, media theorists, science-fiction writers, philosophers, and artists from China and elsewhere reexamine the nation’s intense engagement with AI, moving beyond the clichés that still dominate contemporary debate. Today, visions of the contested future of AI veer between common planetary goals and a new Cold War, as culturally-specific models of intelligence, speculative traditions, and thought experiments come up against the emergence of novel forms of cognition that cannot be reduced to any historical cultural tradition. This uniquely positioned volume provides expert insight into this tension, using China as a touchstone for rethinking "artificiality" and "intelligence" as sites of difference in a way that is already present in the difficulty of precisely translating the Chinese term 人工智能. Tracking the history of Chinese AI from the pre-Cultural Revolution to the post-Deng Xiaoping eras right up to contemporary debates surrounding facial recognition, the writers in this collection draw on a mixture of speculative thought experiments and cutting-edge use cases to offer singular views on topics including AI and Chinese philosophy, AI ethics and policymaking, the development of computational models in early Chinese cybernetics, and the aesthetics of Sinofuturism. Spanning borders between different worlds, histories, futures, and foundational models, Machine Decision is Not Final is not only a timely reappraisal of the stakes of AI development, but a tool for constructing more global imaginaries for the future of AI. Contributors Blaise Aguera y Arcas, Bo An, Benjamin Bratton, Shuang Frost, Vince Garton, Steve Goodman, Yvette Granata, Anna Greenspan, Amy Ireland, Xia Jia, Bogna Konior, Vincent Le, Lawrence Lek, Lukas Likavcan, Suzanne Livingston, Iris Long, Bingchun Meng, Reza Negarestani, Chen Quifan, Gabriele de Seta, Hongzhe Wang, Wang Xin, Mi You
Download or read book Our Final Invention written by James Barrat and published by Macmillan. This book was released on 2013-10-01 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elon Musk named Our Final Invention one of 5 books everyone should read about the future A Huffington Post Definitive Tech Book of 2013 Artificial Intelligence helps choose what books you buy, what movies you see, and even who you date. It puts the "smart" in your smartphone and soon it will drive your car. It makes most of the trades on Wall Street, and controls vital energy, water, and transportation infrastructure. But Artificial Intelligence can also threaten our existence. In as little as a decade, AI could match and then surpass human intelligence. Corporations and government agencies are pouring billions into achieving AI's Holy Grail—human-level intelligence. Once AI has attained it, scientists argue, it will have survival drives much like our own. We may be forced to compete with a rival more cunning, more powerful, and more alien than we can imagine. Through profiles of tech visionaries, industry watchdogs, and groundbreaking AI systems, Our Final Invention explores the perils of the heedless pursuit of advanced AI. Until now, human intelligence has had no rival. Can we coexist with beings whose intelligence dwarfs our own? And will they allow us to?
Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
Download or read book Federal Decisions written by and published by . This book was released on 1884 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Reinforcement and Systemic Machine Learning for Decision Making written by Parag Kulkarni and published by John Wiley & Sons. This book was released on 2012-07-11 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm—creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making. Chapters include: Introduction to Reinforcement and Systemic Machine Learning Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning Systemic Machine Learning and Model Inference and Information Integration Adaptive Learning Incremental Learning and Knowledge Representation Knowledge Augmentation: A Machine Learning Perspective Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.
Download or read book The AI Does Not Hate You written by Tom Chivers and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A deep-dive into the weird and wonderful world of Artificial Intelligence. 'The AI does not hate you, nor does it love you, but you are made of atoms which it can use for something else'. This is a book about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right, and why they might be wrong. It is a book about the cutting edge of our thinking on intelligence and rationality right now by the people who stay up all night worrying about it. Along the way, we discover why we probably don't need to worry about a future AI resurrecting a perfect copy of our minds and torturing us for not inventing it sooner, but we perhaps should be concerned about paperclips destroying life as we know it; how Mickey Mouse can teach us an important lesson about how to program AI; and how a more rational approach to life could be what saves us all. --
Download or read book The Automobile written by and published by . This book was released on 1910 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book After the Digital Tornado written by Kevin Werbach and published by Cambridge University Press. This book was released on 2020-07-23 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks powered by algorithms are pervasive. Major contemporary technology trends - Internet of Things, Big Data, Digital Platform Power, Blockchain, and the Algorithmic Society - are manifestations of this phenomenon. The internet, which once seemed an unambiguous benefit to society, is now the basis for invasions of privacy, massive concentrations of power, and wide-scale manipulation. The algorithmic networked world poses deep questions about power, freedom, fairness, and human agency. The influential 1997 Federal Communications Commission whitepaper “Digital Tornado” hailed the “endless spiral of connectivity” that would transform society, and today, little remains untouched by digital connectivity. Yet fundamental questions remain unresolved, and even more serious challenges have emerged. This important collection, which offers a reckoning and a foretelling, features leading technology scholars who explain the legal, business, ethical, technical, and public policy challenges of building pervasive networks and algorithms for the benefit of humanity. This title is also available as Open Access on Cambridge Core.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Human Compatible written by Stuart Jonathan Russell and published by Penguin Books. This book was released on 2019 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.
Download or read book A Citizen s Guide to Artificial Intelligence written by John Zerilli and published by MIT Press. This book was released on 2021-02-23 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.
Download or read book The Railway and Engineering Review written by Walter Mason Camp and published by . This book was released on 1908 with total page 1214 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Spatula written by Irving P. Fox and published by . This book was released on 1914 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning and Decision Support in Stroke written by Fabien Scalzo and published by Frontiers Media SA. This book was released on 2020-07-09 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book ECAI 2010 written by European Coordinating Committee for Artificial Intelligence and published by IOS Press. This book was released on 2010 with total page 1184 pages. Available in PDF, EPUB and Kindle. Book excerpt: LC copy bound in 2 v.: v. 1, p. 1-509; v. 2, p. [509]-1153.
Download or read book Machine Learning for Practical Decision Making written by Christo El Morr and published by Springer Nature. This book was released on 2022-11-29 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines. The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches.
Download or read book Machine Learning for Decision Makers written by Patanjali Kashyap and published by Apress. This book was released on 2018-01-04 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.
