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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
Book Synopsis Common Sense, the Turing Test, and the Quest for Real AI by : Hector J. Levesque
Download or read book Common Sense, the Turing Test, and the Quest for Real AI written by Hector J. Levesque and published by MIT Press. This book was released on 2017 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
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.
Book Synopsis Machines like Us by : Ronald J. Brachman
Download or read book Machines like Us written by Ronald J. Brachman and published by MIT Press. This book was released on 2023-10-17 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
Book Synopsis Common Sense, the Turing Test, and the Quest for Real AI by : Hector J. Levesque
Download or read book Common Sense, the Turing Test, and the Quest for Real AI written by Hector J. Levesque and published by MIT Press. This book was released on 2018-03-09 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Extending over a period of 30 years, this is a collection of papers written by John McCarthy on artificial intelligence. They range from informal surveys written for a general audience to technical discussions of challenging research problems that should be of interest to specialists.
Book Synopsis Formalizing Common Sense by : John McCarthy
Download or read book Formalizing Common Sense written by John McCarthy and published by Intellect L & D E F A E. This book was released on 1998 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extending over a period of 30 years, this is a collection of papers written by John McCarthy on artificial intelligence. They range from informal surveys written for a general audience to technical discussions of challenging research problems that should be of interest to specialists.
We've outsourced too much of our thinking. How do we get it back? Have you ever followed your GPS device to a deserted parking lot? Or unquestioningly followed the advice of an expert—perhaps a doctor or financial adviser—only to learn later that your own thoughts and doubts were correct? And what about the stories we've all heard over the years about sick patients—whether infected with Ebola or COVID-19—who were sent home or allowed to travel because busy staff people were following a protocol to the letter rather than using common sense? Why and how do these kinds of things happen? As Harvard lecturer and global trend watcher Vikram Mansharamani shows in this eye-opening and perspective-shifting book, our complex, data-flooded world has made us ever more reliant on experts, protocols, and technology. Too often, we've stopped thinking for ourselves. With stark and compelling examples drawn from business, sports, and everyday life, Mansharamani illustrates how in a very real sense we have outsourced our thinking to a troubling degree, relinquishing our autonomy. Of course, experts, protocols, and computer-based systems are essential to helping us make informed decisions. What we need is a new approach for integrating these information sources more effectively, harnessing the value they provide without undermining our ability to think for ourselves. The author provides principles and techniques for doing just that, empowering readers with a more critical and nuanced approach to making decisions. Think for Yourself is an indispensable guide for those looking to restore self-reliant thinking in a data-driven and technology-dependent yet overwhelmingly uncertain world.
Book Synopsis Think for Yourself by : Vikram Mansharamani
Download or read book Think for Yourself written by Vikram Mansharamani and published by Harvard Business Press. This book was released on 2020-06-16 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: We've outsourced too much of our thinking. How do we get it back? Have you ever followed your GPS device to a deserted parking lot? Or unquestioningly followed the advice of an expert—perhaps a doctor or financial adviser—only to learn later that your own thoughts and doubts were correct? And what about the stories we've all heard over the years about sick patients—whether infected with Ebola or COVID-19—who were sent home or allowed to travel because busy staff people were following a protocol to the letter rather than using common sense? Why and how do these kinds of things happen? As Harvard lecturer and global trend watcher Vikram Mansharamani shows in this eye-opening and perspective-shifting book, our complex, data-flooded world has made us ever more reliant on experts, protocols, and technology. Too often, we've stopped thinking for ourselves. With stark and compelling examples drawn from business, sports, and everyday life, Mansharamani illustrates how in a very real sense we have outsourced our thinking to a troubling degree, relinquishing our autonomy. Of course, experts, protocols, and computer-based systems are essential to helping us make informed decisions. What we need is a new approach for integrating these information sources more effectively, harnessing the value they provide without undermining our ability to think for ourselves. The author provides principles and techniques for doing just that, empowering readers with a more critical and nuanced approach to making decisions. Think for Yourself is an indispensable guide for those looking to restore self-reliant thinking in a data-driven and technology-dependent yet overwhelmingly uncertain world.
This book includes high-quality papers presented at the International Conference on Data Science and Management (ICDSM 2019), organised by the Gandhi Institute for Education and Technology, Bhubaneswar, from 22 to 23 February 2019. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.
Book Synopsis Advances in Data Science and Management by : Samarjeet Borah
Download or read book Advances in Data Science and Management written by Samarjeet Borah and published by Springer Nature. This book was released on 2020-01-13 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality papers presented at the International Conference on Data Science and Management (ICDSM 2019), organised by the Gandhi Institute for Education and Technology, Bhubaneswar, from 22 to 23 February 2019. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.
The lives of four high school seniors intersect weeks before a meteor is set to pass through Earth's orbit, with a 66.6% chance of striking and destroying all life on the planet.
Book Synopsis We All Looked Up by : Tommy Wallach
Download or read book We All Looked Up written by Tommy Wallach and published by Simon and Schuster. This book was released on 2015-03-24 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: The lives of four high school seniors intersect weeks before a meteor is set to pass through Earth's orbit, with a 66.6% chance of striking and destroying all life on the planet.
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.
Book Synopsis AI and Common Sense by : Martin W. Bauer
Download or read book AI and Common Sense written by Martin W. Bauer and published by Taylor & Francis. This book was released on 2024-06-28 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world. Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states. The first full book on commonsense reasoning to use the event calculus. Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall. Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves. Includes fully worked out proofs and circumscriptions for every example.
Book Synopsis Commonsense Reasoning by : Erik T. Mueller
Download or read book Commonsense Reasoning written by Erik T. Mueller and published by Elsevier. This book was released on 2010-07-26 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world. Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states. The first full book on commonsense reasoning to use the event calculus. Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall. Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves. Includes fully worked out proofs and circumscriptions for every example.
Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.
Book Synopsis Rebooting AI by : Gary Marcus
Download or read book Rebooting AI written by Gary Marcus and published by Vintage. This book was released on 2019-09-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.
