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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Ronald J. Brachman is Director of the Jacobs Technion-Cornell Institute at Cornell Tech in New York City and Professor of Computer Science at Cornell University. During a long career in industry, he held leadership positions at Bell Labs, Yahoo, and DARPA. Hector J. Levesque is Professor Emeritus in the Department of Computer Science at the University of Toronto. He is the author of Common Sense, the Turing Test, and the Quest for Real AI (MIT Press), and other books.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Bellwetherbooks, McKeesport, PA, USA
paperback. Zustand: Fine. LIKE NEW!!! Has a red or black remainder mark on bottom/exterior edge of pages. Bestandsnummer des Verkäufers 473028
Anzahl: Mehr als 20 verfügbar
Anbieter: Big River Books, Powder Springs, GA, USA
Zustand: like_new. This book is in Like New condition. It is unused, but has a remainder mark on the edge of the pages. Otherwise it is a new book. Bestandsnummer des Verkäufers BRV.0262547325.LN
Anzahl: 3 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 45547483-n
Anzahl: 15 verfügbar
Anbieter: Rarewaves USA, OSWEGO, IL, USA
Paperback. Zustand: New. 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. Bestandsnummer des Verkäufers LU-9780262547321
Anzahl: Mehr als 20 verfügbar
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: new. Paperback. How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise.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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9780262547321
Anbieter: Massive Bookshop, Greenfield, MA, USA
Paperback. Zustand: New. Bestandsnummer des Verkäufers 9780262547321
Anzahl: 10 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 45547483
Anzahl: 15 verfügbar
Anbieter: INDOO, Avenel, NJ, USA
Zustand: As New. Unread copy in mint condition. Bestandsnummer des Verkäufers RH9780262547321
Anzahl: Mehr als 20 verfügbar
Anbieter: INDOO, Avenel, NJ, USA
Zustand: New. Brand New. Bestandsnummer des Verkäufers 9780262547321
Anzahl: Mehr als 20 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26396062951
Anzahl: 3 verfügbar