Common sense, the Turing Test, and the quest for real AI
"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: co...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Levesque, Hector J. - 1951- [verfasserIn] |
|---|
| Format: |
E-Book |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
Cambridge, Massachusetts London, England: The MIT Press ; 2017 |
|---|
| Schlagwörter: |
Artificial intelligence, Philosophy |
|---|
| Anmerkung: |
Includes bibliographical references and index |
|---|---|
| Umfang: |
1 Online-Ressource (xv, 172 pages) ; illustrations |
| Links: | |
|---|---|
| ISBN: |
0-262-03604-5 0-262-33836-X 978-0-262-03604-7 978-0-262-33836-3 |
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1066891931 |
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| 100 | 1 | |a Levesque, Hector J. |d 1951- |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Common sense, the Turing Test, and the quest for real AI |c Hector J. Levesque |
| 264 | 1 | |a Cambridge, Massachusetts |a London, England |b The MIT Press |c 2017 | |
| 300 | |a 1 Online-Ressource (xv, 172 pages) |b illustrations | ||
| 336 | |a Text |b txt |2 rdacontent | ||
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| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 520 | |a "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."--Provided by publisher | ||
| 520 | |a 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 | ||
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0262036045 0-262-03604-5 026233836X : electronic bk. 0-262-33836-X 9780262036047 978-0-262-03604-7 9780262338363 : electronic bk. 978-0-262-33836-3 (DE-627)1066891931 (DE-599)GBV1066891931 (OCoLC)1047883538 (ZBM)1364.68002 (MITPRESS)7904033 (EBP)052923371 DE-627 eng DE-627 rda eng XD-US BF441 COM 000000 bisacsh *68-01 msc 68T01 msc Levesque, Hector J. 1951- verfasserin aut Common sense, the Turing Test, and the quest for real AI Hector J. Levesque Cambridge, Massachusetts London, England The MIT Press 2017 1 Online-Ressource (xv, 172 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index "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."--Provided by publisher 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 Thought and thinking Intellect Computational intelligence Artificial intelligence Philosophy Thought and thinking Intellect Computational intelligence Artificial intelligence ; Philosophy Airplanes Algebra Animals Artificial intelligence Auditory system Automobiles Bibliographies Biology Blades Blogs Bridges Buildings Calculus Cats Cognition Companies Computational intelligence Computer science Computers Concrete Context DNA Dogs Feature extraction Floors Games History IEEE Sections Ice Image color analysis Indexes Keyboards Knowledge based systems Knowledge representation Legged locomotion Libraries Machinery Manuals Market research Mathematics Medical services Meteorology Mirrors Motion pictures Neurons Neuroscience Pediatrics Planets Planning Presses Proposals Psychology Reliability Robots Rockets Senior citizens Sociology Sports equipment Statistics Stock markets Systematics Training Urban areas Videos Visualization Vocabulary Writing 9780262036047 Print version Levesque, Hector J., 1951- Common sense, the Turing Test, and the quest for real AI Cambridge, Massachusetts ; London, England : The MIT Press, [2017] (DLC)2016033671 https://ieeexplore.ieee.org/book/7904033 X:MITPRESS Verlag lizenzpflichtig https://zbmath.org/?q=an:1364.68002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext ZDB-37-IEM 2017 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OPC-MAT GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 006.301 22 01 0018 3848471604 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3476079473 olr-MIT i z 15-05-19 62 01 0028 3601568489 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 02-03-20 100 01 3100 4472464918 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011218472 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/7904033 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/7904033 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/7904033 62 01 0028 https://ieeexplore.ieee.org/book/7904033 100 01 3100 https://ieeexplore.ieee.org/book/7904033 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/7904033 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/7904033 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| spelling |
0262036045 0-262-03604-5 026233836X : electronic bk. 0-262-33836-X 9780262036047 978-0-262-03604-7 9780262338363 : electronic bk. 978-0-262-33836-3 (DE-627)1066891931 (DE-599)GBV1066891931 (OCoLC)1047883538 (ZBM)1364.68002 (MITPRESS)7904033 (EBP)052923371 DE-627 eng DE-627 rda eng XD-US BF441 COM 000000 bisacsh *68-01 msc 68T01 msc Levesque, Hector J. 1951- verfasserin aut Common sense, the Turing Test, and the quest for real AI Hector J. Levesque Cambridge, Massachusetts London, England The MIT Press 2017 1 Online-Ressource (xv, 172 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index "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."--Provided by publisher 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 Thought and thinking Intellect Computational intelligence Artificial intelligence Philosophy Thought and thinking Intellect Computational intelligence Artificial intelligence ; Philosophy Airplanes Algebra Animals Artificial intelligence Auditory system Automobiles Bibliographies Biology Blades Blogs Bridges Buildings Calculus Cats Cognition Companies Computational intelligence Computer science Computers Concrete Context DNA Dogs Feature extraction Floors Games History IEEE Sections Ice Image color analysis Indexes Keyboards Knowledge based systems Knowledge representation Legged locomotion Libraries Machinery Manuals Market research Mathematics Medical services Meteorology Mirrors Motion pictures Neurons Neuroscience Pediatrics Planets Planning Presses Proposals Psychology Reliability Robots Rockets Senior citizens Sociology Sports equipment Statistics Stock markets Systematics Training Urban areas Videos Visualization Vocabulary Writing 9780262036047 Print version Levesque, Hector J., 1951- Common sense, the Turing Test, and the quest for real AI Cambridge, Massachusetts ; London, England : The MIT Press, [2017] (DLC)2016033671 https://ieeexplore.ieee.org/book/7904033 X:MITPRESS Verlag lizenzpflichtig https://zbmath.org/?q=an:1364.68002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext ZDB-37-IEM 2017 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OPC-MAT GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 006.301 22 01 0018 3848471604 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3476079473 olr-MIT i z 15-05-19 62 01 0028 3601568489 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 02-03-20 100 01 3100 4472464918 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011218472 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/7904033 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/7904033 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/7904033 62 01 0028 https://ieeexplore.ieee.org/book/7904033 100 01 3100 https://ieeexplore.ieee.org/book/7904033 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/7904033 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/7904033 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfields_unstemmed |
0262036045 0-262-03604-5 026233836X : electronic bk. 0-262-33836-X 9780262036047 978-0-262-03604-7 9780262338363 : electronic bk. 978-0-262-33836-3 (DE-627)1066891931 (DE-599)GBV1066891931 (OCoLC)1047883538 (ZBM)1364.68002 (MITPRESS)7904033 (EBP)052923371 DE-627 eng DE-627 rda eng XD-US BF441 COM 000000 bisacsh *68-01 msc 68T01 msc Levesque, Hector J. 1951- verfasserin aut Common sense, the Turing Test, and the quest for real AI Hector J. Levesque Cambridge, Massachusetts London, England The MIT Press 2017 1 Online-Ressource (xv, 172 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index "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."--Provided by publisher 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 Thought and thinking Intellect Computational intelligence Artificial intelligence Philosophy Thought and thinking Intellect Computational intelligence Artificial intelligence ; Philosophy Airplanes Algebra Animals Artificial intelligence Auditory system Automobiles Bibliographies Biology Blades Blogs Bridges Buildings Calculus Cats Cognition Companies Computational intelligence Computer science Computers Concrete Context DNA Dogs Feature extraction Floors Games History IEEE Sections Ice Image color analysis Indexes Keyboards Knowledge based systems Knowledge representation Legged locomotion Libraries Machinery Manuals Market research Mathematics Medical services Meteorology Mirrors Motion pictures Neurons Neuroscience Pediatrics Planets Planning Presses Proposals Psychology Reliability Robots Rockets Senior citizens Sociology Sports equipment Statistics Stock markets Systematics Training Urban areas Videos Visualization Vocabulary Writing 9780262036047 Print version Levesque, Hector J., 1951- Common sense, the Turing Test, and the quest for real AI Cambridge, Massachusetts ; London, England : The MIT Press, [2017] (DLC)2016033671 https://ieeexplore.ieee.org/book/7904033 X:MITPRESS Verlag lizenzpflichtig https://zbmath.org/?q=an:1364.68002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext ZDB-37-IEM 2017 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OPC-MAT GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 006.301 22 01 0018 3848471604 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3476079473 olr-MIT i z 15-05-19 62 01 0028 3601568489 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 02-03-20 100 01 3100 4472464918 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011218472 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/7904033 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/7904033 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/7904033 62 01 0028 https://ieeexplore.ieee.org/book/7904033 100 01 3100 https://ieeexplore.ieee.org/book/7904033 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/7904033 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/7904033 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsGer |
0262036045 0-262-03604-5 026233836X : electronic bk. 0-262-33836-X 9780262036047 978-0-262-03604-7 9780262338363 : electronic bk. 978-0-262-33836-3 (DE-627)1066891931 (DE-599)GBV1066891931 (OCoLC)1047883538 (ZBM)1364.68002 (MITPRESS)7904033 (EBP)052923371 DE-627 eng DE-627 rda eng XD-US BF441 COM 000000 bisacsh *68-01 msc 68T01 msc Levesque, Hector J. 1951- verfasserin aut Common sense, the Turing Test, and the quest for real AI Hector J. Levesque Cambridge, Massachusetts London, England The MIT Press 2017 1 Online-Ressource (xv, 172 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index "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."--Provided by publisher 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 Thought and thinking Intellect Computational intelligence Artificial intelligence Philosophy Thought and thinking Intellect Computational intelligence Artificial intelligence ; Philosophy Airplanes Algebra Animals Artificial intelligence Auditory system Automobiles Bibliographies Biology Blades Blogs Bridges Buildings Calculus Cats Cognition Companies Computational intelligence Computer science Computers Concrete Context DNA Dogs Feature extraction Floors Games History IEEE Sections Ice Image color analysis Indexes Keyboards Knowledge based systems Knowledge representation Legged locomotion Libraries Machinery Manuals Market research Mathematics Medical services Meteorology Mirrors Motion pictures Neurons Neuroscience Pediatrics Planets Planning Presses Proposals Psychology Reliability Robots Rockets Senior citizens Sociology Sports equipment Statistics Stock markets Systematics Training Urban areas Videos Visualization Vocabulary Writing 9780262036047 Print version Levesque, Hector J., 1951- Common sense, the Turing Test, and the quest for real AI Cambridge, Massachusetts ; London, England : The MIT Press, [2017] (DLC)2016033671 https://ieeexplore.ieee.org/book/7904033 X:MITPRESS Verlag lizenzpflichtig https://zbmath.org/?q=an:1364.68002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext ZDB-37-IEM 2017 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OPC-MAT GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 006.301 22 01 0018 3848471604 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3476079473 olr-MIT i z 15-05-19 62 01 0028 3601568489 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 02-03-20 100 01 3100 4472464918 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011218472 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/7904033 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/7904033 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/7904033 62 01 0028 https://ieeexplore.ieee.org/book/7904033 100 01 3100 https://ieeexplore.ieee.org/book/7904033 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/7904033 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/7904033 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsSound |
0262036045 0-262-03604-5 026233836X : electronic bk. 0-262-33836-X 9780262036047 978-0-262-03604-7 9780262338363 : electronic bk. 978-0-262-33836-3 (DE-627)1066891931 (DE-599)GBV1066891931 (OCoLC)1047883538 (ZBM)1364.68002 (MITPRESS)7904033 (EBP)052923371 DE-627 eng DE-627 rda eng XD-US BF441 COM 000000 bisacsh *68-01 msc 68T01 msc Levesque, Hector J. 1951- verfasserin aut Common sense, the Turing Test, and the quest for real AI Hector J. Levesque Cambridge, Massachusetts London, England The MIT Press 2017 1 Online-Ressource (xv, 172 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index "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."--Provided by publisher 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 Thought and thinking Intellect Computational intelligence Artificial intelligence Philosophy Thought and thinking Intellect Computational intelligence Artificial intelligence ; Philosophy Airplanes Algebra Animals Artificial intelligence Auditory system Automobiles Bibliographies Biology Blades Blogs Bridges Buildings Calculus Cats Cognition Companies Computational intelligence Computer science Computers Concrete Context DNA Dogs Feature extraction Floors Games History IEEE Sections Ice Image color analysis Indexes Keyboards Knowledge based systems Knowledge representation Legged locomotion Libraries Machinery Manuals Market research Mathematics Medical services Meteorology Mirrors Motion pictures Neurons Neuroscience Pediatrics Planets Planning Presses Proposals Psychology Reliability Robots Rockets Senior citizens Sociology Sports equipment Statistics Stock markets Systematics Training Urban areas Videos Visualization Vocabulary Writing 9780262036047 Print version Levesque, Hector J., 1951- Common sense, the Turing Test, and the quest for real AI Cambridge, Massachusetts ; London, England : The MIT Press, [2017] (DLC)2016033671 https://ieeexplore.ieee.org/book/7904033 X:MITPRESS Verlag lizenzpflichtig https://zbmath.org/?q=an:1364.68002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext ZDB-37-IEM 2017 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OPC-MAT GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 006.301 22 01 0018 3848471604 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3476079473 olr-MIT i z 15-05-19 62 01 0028 3601568489 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 02-03-20 100 01 3100 4472464918 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011218472 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/7904033 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/7904033 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/7904033 62 01 0028 https://ieeexplore.ieee.org/book/7904033 100 01 3100 https://ieeexplore.ieee.org/book/7904033 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/7904033 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/7904033 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
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Common sense, the Turing Test, and the quest for real AI |
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"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."--Provided by publisher 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 Includes bibliographical references and index |
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"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."--Provided by publisher 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 Includes bibliographical references and index |
| abstract_unstemmed |
"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."--Provided by publisher 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 Includes bibliographical references and index |
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| title_short |
Common sense, the Turing Test, and the quest for real AI |
| url |
https://ieeexplore.ieee.org/book/7904033 https://zbmath.org/?q=an:1364.68002 |
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