Author : Hector J. Levesque
Publisher : MIT Press
Page : 190 pages
File Size : 34,70 MB
Release : 2017
Category : Computers
ISBN : 0262036045
What kind of AI? -- The big puzzle -- Knowledge and behavior -- Making it and faking it -- Learning with and without experience -- Book smarts and street smarts -- The long tail and the limits to training -- Symbols and symbol processing -- Knowledge-based systems -- AI technology
Author : Hector J. Levesque
Publisher : MIT Press
Page : 190 pages
File Size : 35,21 MB
Release : 2018-03-09
Category : Computers
ISBN : 0262535203
What artificial intelligence can tell us about the mind and intelligent behavior. What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to “good old fashioned artificial intelligence,” which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns—as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk. Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence—the Winograd Schema Test, developed by Levesque and his colleagues. “If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it,” he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.
Author : Ronald J. Brachman
Publisher : MIT Press
Page : 320 pages
File Size : 46,69 MB
Release : 2022-05-17
Category : Computers
ISBN : 0262369222
How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.
Author : Martin W. Bauer
Publisher : Taylor & Francis
Page : 286 pages
File Size : 27,61 MB
Release : 2024-06-28
Category : Computers
ISBN : 1040086527
Common sense is the endless frontier in the development of artificial intelligence, but what exactly is common sense, can we replicate it in algorithmic form, and if we can – should we? Bauer, Schiele and their contributors from a range of disciplines analyse the nature of common sense, and the consequent challenges of incorporating into artificial intelligence models. They look at different ways we might understand common sense and which of these ways are simulated within computer algorithms. These include sensory integration, self-evident truths, rhetorical common places, and mutuality and intentionality of actors within a moral community. How far are these possible features within and of machines? Approaching from a range of perspectives including Sociology, Political Science, Media and Culture, Psychology and Computer Science, the contributors lay out key questions, practical challenges and "common sense" concerns underlying the incorporation of common sense within machine learning algorithms for simulating intelligence, socialising robots, self-driving vehicles, personnel selection, reading, automatic text analysis, and text production. A valuable resource for students and scholars of Science–Technology–Society Studies, Sociologists, Psychologists, Media and Culture Studies, human–computer interaction with an interest in the post-human, and programmers tackling the contextual questions of machine learning.
Author : Robert Epstein
Publisher : Springer Science & Business Media
Page : 520 pages
File Size : 48,15 MB
Release : 2008-12-01
Category : Computers
ISBN : 1402096240
An exhaustive work that represents a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate weighty issues such as whether a self-conscious computer would create an internet ‘world mind’. This hugely important volume explores nothing less than the future of the human race itself.
Author : Nicholas Agar
Publisher : MIT Press
Page : 231 pages
File Size : 13,8 MB
Release : 2019-03-12
Category : Technology & Engineering
ISBN : 0262038749
An argument in favor of finding a place for humans (and humanness) in the future digital economy. In the digital economy, accountants, baristas, and cashiers can be automated out of employment; so can surgeons, airline pilots, and cab drivers. Machines will be able to do these jobs more efficiently, accurately, and inexpensively. But, Nicholas Agar warns in this provocative book, these developments could result in a radically disempowered humanity. The digital revolution has brought us new gadgets and new things to do with them. The digital revolution also brings the digital economy, with machines capable of doing humans' jobs. Agar explains that developments in artificial intelligence enable computers to take over not just routine tasks but also the kind of “mind work” that previously relied on human intellect, and that this threatens human agency. The solution, Agar argues, is a hybrid social-digital economy. The key value of the digital economy is efficiency. The key value of the social economy is humanness. A social economy would be centered on connections between human minds. We should reject some digital automation because machines will always be poor substitutes for humans in roles that involve direct contact with other humans. A machine can count out pills and pour out coffee, but we want our nurses and baristas to have minds like ours. In a hybrid social-digital economy, people do the jobs for which feelings matter and machines take on data-intensive work. But humans will have to insist on their relevance in a digital age.
Author : Herb Kunze
Publisher : CRC Press
Page : 717 pages
File Size : 27,77 MB
Release : 2023-07-26
Category : Technology & Engineering
ISBN : 1000907899
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between mathematics and AI/ML and provides an overview of the current research streams. Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind ML and shows how mathematics can be used in AI. The book illustrates how to improve existing algorithms by using advanced mathematics and offers cutting-edge AI technologies. The book goes on to discuss how ML can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between ML and complex mathematical techniques is also highlighted within the book. This book is written for researchers, practitioners, engineers, and AI consultants.
Author : Melanie Mitchell
Publisher : Farrar, Straus and Giroux
Page : 336 pages
File Size : 21,57 MB
Release : 2019-10-15
Category : Computers
ISBN : 0374715238
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.
Author : Ronald J. Brachman
Publisher : MIT Press
Page : 319 pages
File Size : 13,78 MB
Release : 2023-10-17
Category : Computers
ISBN : 0262547325
How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.
Author : Dean Buonomano
Publisher : W. W. Norton & Company
Page : 357 pages
File Size : 12,42 MB
Release : 2017-04-04
Category : Science
ISBN : 0393247953
"Beautifully written, eloquently reasoned…Mr. Buonomano takes us off and running on an edifying scientific journey." —Carol Tavris, Wall Street Journal In Your Brain Is a Time Machine, leading neuroscientist Dean Buonomano embarks on an "immensely engaging" exploration of how time works inside the brain (Barbara Kiser, Nature). The human brain, he argues, is a complex system that not only tells time, but creates it; it constructs our sense of chronological movement and enables "mental time travel"—simulations of future and past events. These functions are essential not only to our daily lives but to the evolution of the human race: without the ability to anticipate the future, mankind would never have crafted tools or invented agriculture. This virtuosic work of popular science will lead you to a revelation as strange as it is true: your brain is, at its core, a time machine.
