Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2024-03-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Download or read book Elements of Artificial Intelligence written by Steven L. Tanimoto and published by W.H. Freeman. This book was released on 1994-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Elements of Artificial Intelligence Using Common Lisp written by Steven Tanimoto and published by W H Freeman & Company. This book was released on 1995 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides an introductory-level overview of artificial intelligence (AI). It features clear presentation of principles integrated with short, workable programs which are designed to help students to learn by experimentation and to develop an intuitive understanding of the subject.
Download or read book Elements of Artificial Neural Networks written by Kishan Mehrotra and published by MIT Press. This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.
Download or read book An Introductory Guide to Artificial Intelligence for Legal Professionals written by Juan Pavón and published by Kluwer Law International B.V.. This book was released on 2020-05-14 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of very large data sets and the increase in computing power to process them has led to a renewed intensity in corporate and governmental use of Artificial Intelligence (AI) technologies. This groundbreaking book, the first devoted entirely to the growing presence of AI in the legal profession, responds to the necessity of building up a discipline that due to its novelty requires the pooling of knowledge and experiences of well-respected experts in the AI field, taking into account the impact of AI on the law and legal practice. Essays by internationally known expert authors introduce the essentials of AI in a straightforward and intelligible style, offering jurists as many practical examples and business cases as possible so that they are able to understand the real application of this technology and its impact on their jobs and lives. Elements of the analysis include the following: crucial terms: natural language processing, machine learning and deep learning; regulations in force in major jurisdictions; ethical and social issues; labour and employment issues, including the impact that robots have on employment; prediction of outcome in the legal field (judicial proceedings, patent granting, etc.); massive analysis of documents and identification of patterns from which to derive conclusions; AI and taxation; issues of competition and intellectual property; liability and responsibility of intelligent systems; AI and cybersecurity; AI and data protection; impact on state tax revenues; use of autonomous killer robots in the military; challenges related to privacy; the need to embrace transparency and sustainability; pressure brought by clients on prices; minority languages and AI; danger that the existing gap between large and small businesses will further increase; how to avoid algorithmic biases when AI decides; AI application to due diligence; AI and non-disclosure agreements; and the role of chatbots. Interviews with pioneers in the field are included, so readers get insights into the issues that people are dealing with in day-to-day actualities. Whether conceiving AI as a transformative technology of the labour market and training or an economic and business sector in need of legal advice, this introduction to AI will help practitioners in tax law, labour law, competition law and intellectual property law understand what AI is, what it serves, what is the state of the art and the potential of this technology, how they can benefit from its advantages and what are the risks it presents. As the global economy continues to suffer the repercussions of a framework that was previously fundamentally self-regulatory, policymakers will recognize the urgent need to formulate rules to properly manage the future of AI.
Download or read book Elements of Machine Learning written by Pat Langley and published by Morgan Kaufmann. This book was released on 1996 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is the computational study of algorithms that improve performance based on experience, and this book covers the basic issues of artificial intelligence. Individual sections introduce the basic concepts and problems in machine learning, describe algorithms, discuss adaptions of the learning methods to more complex problem-solving tasks and much more.
Download or read book The Elements of Artificial Intelligence Using written by Steven Tanimoto and published by . This book was released on 1990 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Smart and Intelligent Systems written by Abbas Moallem and published by CRC Press. This book was released on 2021-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is perfect for engineering students in data sciences, artificial intelligence, practitioners at all levels in the field of human factors and ergonomics, systems engineering, computer science, software engineering and robotics"--
Download or read book An Introduction to Ethics in Robotics and AI written by Christoph Bartneck and published by Springer Nature. This book was released on 2020-08-11 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book introduces the reader to the foundations of AI and ethics. It discusses issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between people and the AI systems and Robotics they use. Designed to be accessible for a broad audience, reading this book does not require prerequisite technical, legal or philosophical expertise. Throughout, the authors use examples to illustrate the issues at hand and conclude the book with a discussion on the application areas of AI and Robotics, in particular autonomous vehicles, automatic weapon systems and biased algorithms. A list of questions and further readings is also included for students willing to explore the topic further.
Download or read book The Elements of Artificial Intelligence written by Steven Tanimoto and published by Rockville, MD : Computer Science Press. This book was released on 1987 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Essence of Artificial Intelligence written by Alison Cawsey and published by Pearson. This book was released on 1998 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, practical introduction to artificial intelligence, this title starts with the fundamentals of knowledge representation, inference, expert systems, natural language processing, machine learning, neural networks, agents, robots, and much more. Examples and algorithms are presented throughout, and the book includes a complete glossary.
Download or read book Artificial Intelligence written by Melanie Mitchell and published by Farrar, Straus and Giroux. This book was released on 2019-10-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Download or read book Mem elements for Neuromorphic Circuits with Artificial Intelligence Applications written by Christos Volos and published by Academic Press. This book was released on 2021-06-17 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence
Download or read book The Elements of Statistical Learning written by Trevor Hastie and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Download or read book Artificial Intelligence in Medicine written by David Riaño and published by Springer. This book was released on 2019-06-19 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
Download or read book Competing in the Age of AI written by Marco Iansiti and published by Harvard Business Press. This book was released on 2020-01-07 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: "a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
