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This collection of essays by 12 members of the MIT staff, provides an inside reporton the scope and expectations of current research in one of the world's major AI centers. Thechapters on artificial intelligence, expert systems, vision, robotics, and natural language provideboth a broad overview of current areas of activity and an assessment of the field at a time of greatpublic interest and rapid technological progress.Contents: Artificial Intelligence (Patrick H.Winston and Karen Prendergast). KnowledgeBased Systems (Randall Davis). Expert-System Tools andTechniques (Peter Szolovits). Medical Diagnosis: Evolution of Systems Building Expertise (Ramesh S.Patil). Artificial Intelligence and Software Engineering (Charles Rich and Richard C. Waters).Intelligent Natural Language Processing (Robert C. Berwick). Automatic Speech Recognition andUnderstanding (Victor W. Zue). Robot Programming and Artificial Intelligence (Tomas Lozano-Perez).Robot Hands and Tactile Sensing (John M. Hollerbach). Intelligent Vision (Michael Brady). MakingRobots See (W. Eric L. Grimson). Autonomous Mobile Robots (Rodney A. Brooks).W. Eric L. Grimson,author of From Images to Surfaces: A Computational Study of the Human Early Vision System (MIT Press1981), and Ramesh S. Patil are both Assistant Professors in the Department of Electrical Engineeringand Computer Science at MIT. AI in the 1980s and Beyond is included in the Artificial IntelligenceSeries, edited by Patrick H. Winston and Michael Brady.
With a 30-year career in artificial intelligence (AI) and computer science, Hall reviews the history of AI, predicting the probable achievements in the near future and provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.
The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it.
This Festschrift volume, published in celebration of the 50th Anniversary of Artificial Intelligence, includes 34 refereed papers written by leading researchers in the field of Artificial Intelligence. The papers were carefully selected from the invited lectures given at the 50th Anniversary Summit of AI, held at the Centro Stefano Franscini, Monte Verità, Ascona, Switzerland, July 9-14, 2006. The summit provided a venue for discussions on a broad range of topics.
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
As artificial intelligence (AI) becomes more and more woven into our everyday lives—and underpins so much of the infrastructure we rely on—the ethical, security, and privacy implications require a critical approach that draws not simply on the programming and algorithmic foundations of the technology. Bringing together legal studies, philosophy, cybersecurity, and academic literature, Beyond the Algorithm examines these complex issues with a comprehensive, easy-to-understand analysis and overview. The book explores the ethical challenges that professionals—and, increasingly, users—are encountering as AI becomes not just a promise of the future, but a powerful tool of the present. An overview of the history and development of AI, from the earliest pioneers in machine learning to current applications and how it might shape the future Introduction to AI models and implementations, as well as examples of emerging AI trends Examination of vulnerabilities, including insight into potential real-world threats, and best practices for ensuring a safe AI deployment Discussion of how to balance accountability, privacy, and ethics with regulatory and legislative concerns with advancing AI technology A critical perspective on regulatory obligations, and repercussions, of AI with copyright protection, patent rights, and other intellectual property dilemmas An academic resource and guide for the evolving technical and intellectual challenges of AI Leading figures in the field bring to life the ethical issues associated with AI through in-depth analysis and case studies in this comprehensive examination.
With so much artificial intelligence (AI) in the headlines, it is no surprise that businesses are scrambling to exploit this exciting and transformative technology. Clearly, those who are the first to deliver business-relevant AI will gain significant advantage. However, there is a problem! Our perception of AI success in society is primarily based on our experiences with consumer applications from the big web companies. The adoption of AI in the enterprise has been slow due to various challenges. Business applications address far more complex problems and the data needed to address them is less plentiful. There is also the critical need for alignment of AI with relevant business processes. In addition, the use of AI requires new engineering practices for application maintenance and trust. So, how do you deliver working AI applications in the enterprise? Beyond Algorithms: Delivering AI for Business answers this question. Written by three engineers with decades of experience in AI (and all the scars that come with that), this book explains what it takes to define, manage, engineer, and deliver end-to-end AI applications that work. This book presents: Core conceptual differences between AI and traditional business applications A new methodology that helps to prioritise AI projects and manage risks Practical case studies and examples with a focus on business impact and solution delivery Technical Deep Dives and Thought Experiments designed to challenge your brain and destroy your weekends
In today's rapidly evolving business landscape, artificial intelligence (AI) has emerged as a transformative force, revolutionizing how organizations operate, compete, and innovate. "AI in Business" is your comprehensive guide to understanding and leveraging the power of AI in the corporate world. This ebook provides a concise yet thorough exploration of the myriad ways AI is reshaping industries and driving business success. From enhancing customer experiences to optimizing operational efficiency, AI offers unparalleled opportunities for growth and innovation. Through real-world examples, case studies, and expert insights, "AI in Business" equips you with the knowledge and strategies needed to harness the full potential of AI within your organization. Discover the essential concepts of AI, explore its diverse applications across various business functions, and learn how to navigate the challenges and ethical considerations associated with its implementation. Whether you're a business leader seeking to stay ahead of the curve or a professional looking to capitalize on the AI revolution, this ebook provides actionable guidance for unlocking the competitive advantage of AI in today's dynamic marketplace. Join us on a journey into the future of business, where AI is not just a tool but a strategic imperative for success. "AI in Business" is your roadmap to navigating this exciting new frontier and driving sustainable growth in an AI-driven world.
Researchers in artificial intelligence and scholars in the humanities consider the past, present, and future of artificial intelligence from a multidisciplinary perspective.