fbpx
Wikipedia

Douglas Lenat

March 04, 2023

Douglas Bruce Lenat (born 1950) is the CEO of Cycorp, Inc. of Austin, Texas, and has been a prominent researcher[1] in artificial intelligence.[2] Lenat was awarded the biannual IJCAI Computers and Thought Award in 1976 for creating the machine-learning program AM. He has worked on (symbolic, not statistical) machine learning (with his AM and Eurisko programs), knowledge representation,[3] "cognitive economy",[4] blackboard systems, and what he dubbed in 1984 "ontological engineering"[5] (with his Cyc program at MCC and, since 1994, at Cycorp). He has also worked in military simulations,[6] and numerous projects for US government, military, intelligence, and scientific organizations. In 1980, he published a critique of conventional random-mutation Darwinism.[7][8] He authored a series of articles[9][10][11][12] in the Journal of Artificial Intelligence exploring the nature of heuristic rules.

Douglas Lenat
BornSeptember 13, 1950
Philadelphia, Pennsylvania
NationalityAmerican
EducationUniversity of Pennsylvania, Stanford University (Ph.D.)
OccupationComputer scientist
EmployerCycorp, Inc.
Known forLisp programming language, CEO of Cycorp, Inc., AM, Eurisko, Cyc
Awards1977 IJCAI Computers and Thought Award

Lenat was one of the original Fellows of the AAAI, and is the only individual to have served on the Scientific Advisory Boards of both Microsoft and Apple. He is a Fellow of the AAAS, AAAI, and Cognitive Science Society, and an editor of the J. Automated Reasoning, J. Learning Sciences, and J. Applied Ontology. He was one of the founders of TTI/Vanguard in 1991 and remains a member of its advisory board still in 2017. He was named one of the Wired 25.[13]

Background and education

Lenat was born in Philadelphia, Pennsylvania, on September 13, 1950, and grew up there and, from ages 5–15, in Wilmington, Delaware. He attended Cheltenham High School, in Wyncote PA, where his after-school job at the neighboring Beaver College was cleaning rat cages and then goose pens, which motivated him to learn to program as a path to a very different after-school and summer job, and eventually career.

While attending the University of Pennsylvania, Lenat supported himself through programming, notably designing and developing a natural language interface to a U.S. Navy database question–answering system serving as an early online shipboard operations manual used on US aircraft carriers. He received his bachelor's degree in Mathematics and Physics, and his master's degree in Applied Mathematics, all in 1972, from the University of Pennsylvania.

For his senior thesis, advised in part by Dennis Gabor, was to bounce acoustic waves in the 40 mHz range off real-world objects, record their interference patterns on a 2-meter square plot, photo-reduce those to a 10-mm square film image, shine a laser through the film, and thus project the three-dimensional imaged object—i.e., the first known acoustic hologram. To settle an argument with Dr. Gabor, Lenat computer-generated a five-dimensional hologram, by photo-reducing computer printout of the interference pattern of a globe rotating and expanding over time, reducing the large two-dimensional paper printout to a moderately large 5-cm square film surface through which a conventional laser beam was then able to project a three-dimensional image, which changed in two independent ways (rotating and changing in size) as the film was moved up-down or left-right.

Lenat was a Ph.D. student in Computer Science at Stanford University, where his published research included automatic program synthesis from input/output pairs and from natural language clarification dialogues.[14]

Research

He received his Ph.D. in Computer Science from Stanford University (published as Knowledge-based systems in artificial intelligence,[15] along with the Ph.D. thesis of Randall Davis, McGraw-Hill, 1982) in 1976. His thesis advisor was Professor Cordell Green, and his thesis/oral committee included Professors Edward Feigenbaum, Joshua Lederberg, Paul Cohen, Allen Newell, Herbert Simon, Bruce Buchanan, John McCarthy, and Donald Knuth.

His thesis, AM (Automated Mathematician) was one of the first computer programs that attempted to make discoveries, i.e., to be a theorem proposer rather than a theorem prover. Experimenting with the program fueled a cycle of criticism and improvement, leading to a slightly deeper understanding of human creativity. Many issues had to be dealt with in constructing such a program: how to represent knowledge formally, expressively, and concretely, how to program hundreds of heuristic "interestingness" rules to judge the worth of new discoveries, heuristics for when to reason symbolically and inductively (and slowly) versus when to reason statistically from frequency data (and hence, quickly), what the architecture—the design constraints—of such reasoning programs might be, why heuristics work (in sum, because the future is a continuous function of the past), and what their "inner structure'' might be. AM was one of the first halting steps toward a science of learning by discovery, toward de-mystifying the creative process and demonstrating that computer programs can make novel and creative discoveries.[16]

In 1976 Lenat started teaching as an assistant professor of Computer Science at Carnegie Mellon and commenced his work on the AI program Eurisko. The limitation with AM was that it was locked into following a fixed set of interestingness heuristics; Eurisko, by contrast, represented its heuristic rules as first class objects and hence it could explore, manipulate, and discover new heuristics just as it (and AM) explored, manipulated, and discovered new domain concepts.

Lenat returned to Stanford as an assistant professor of Computer Science in 1978 and continued his research building the Eurisko automated discovery and heuristic-discovery program. Eurisko made many interesting discoveries and enjoyed significant acclaim, with Lenat's paper "Heuretics: Theoretical and Experimental Study of Heuristic Rules"[17] winning the Best Paper award at the 1982 AAAI conference.

A call for "common sense"

Unlike the vast preponderance of published scientific results, Lenat (working with John Seely Brown at Xerox PARC) published in 1984 a thorough and frank analysis of what were the limitations of his AM and Eurisko lines of research.[18] It concluded that progress toward real, general, symbolic AI would require a vast knowledge base of "common sense", suitably formalized and represented, and an inference engine capable of finding tens- or hundreds-deep conclusions and arguments that followed from the application of that knowledge base to specific questions and applications.[19]

The successes, and frank analysis of the limitations, of this AM and Eurisko approach to AI, and the concluding plea for the massive (multi-thousand-person-year, decades-long) R&D effort would be required to break that bottleneck to AI, led to attention in 1982 from Admiral Bob Inman and the then-forming MCC research consortium in Austin, Texas, culminating in Lenat's becoming Principal Scientist of MCC from 1984–1994, though he continued even after this period to return to Stanford to teach approximately one course per year. At the 400-person MCC, Lenat was able to have several dozen researchers work on that common sense knowledge base, rather than just a few graduate students.

Cycorp

The fruits of the first decade of R&D on Cyc[20] were spun out of MCC into a company, Cycorp, at the end of 1994. In 1986, he estimated the effort to complete Cyc would be at least 250,000 rules and 1,000 person-years of effort,[21] probably twice that, and by 2017, he and his team had spent about 2,000 person-years of effort building Cyc, creating approximately 24 million rules and assertions (not counting "facts"). Lenat emphasizes that he and his 60-person R&D team strive to keep those numbers as small as possible; even the number of one-step inferences in Cyc's deductive closure is in the hundreds of trillions.

As of 2018, Lenat continues his work on Cyc as CEO of Cycorp. While the first decade of work on Cyc (1984–1994) was funded by large American companies pooling long-term research funds to compete with the Japanese Fifth Generation Computer Project, and the second decade (1995-2006) of work on Cyc was funded by US government agencies' research contracts, the third decade up through the present (2007–present) has been largely supported through commercial applications of Cyc, including in the financial services, energy, and healthcare areas.[22]

Among the recent[when?] Cyc applications, one unusual one, MathCraft, involves helping middle-school students more deeply understand math.[23] Most people have had the experience where we thought we understood something, but only really understood it when we had to explain or teach it to someone else. Despite that, almost all AI-aided instruction has the AI play the role of the teacher. In contrast, Mathcraft has the AI, Cyc, play the role of a fellow student who is always very slightly more confused than you, the user, are. As you give MathCraft good advice, it allows that avatar to make fewer mistakes of that kind, and from the point of the user it seems as though they have taught it something. This sort of Learning by Teaching paradigm may have broad applications in future domains where training is involved.

Quotes

 
Doug Lenat in his office at Cycorp
  • "Intelligence is ten million rules."[24] This refers to the prior and tacit knowledge that authors presume their readers all possess (such as "if person x knows person y, then x's date of death can't be earlier than y's date of birth") not counting the vastly larger number of "facts" such as one might find in Wikipedia or by Googling.
  • "The time may come when a greatly expanded Cyc will underlie countless software applications. But reaching that goal could easily take another two decades."[25]
  • "Once you have a truly massive amount of information integrated as knowledge, then the human-software system will be superhuman, in the same sense that mankind with writing (or language itself) is superhuman compared to mankind before writing (or language itself). We look back on pre-linguistic cavemen and think 'they weren't quite human, were they?' In much the same way, our descendants will look back on pre-AI homo sapiens with exactly that mixture of otherness and pity."[This quote needs a citation]
  • "Sometimes the veneer of intelligence is not enough."[26]
  • “If computers were human, they’d present themselves as autistic, schizophrenic, or otherwise brittle. It would be unwise or dangerous for that person to take care of children and cook meals, but it’s on the horizon for home robots. That’s like saying, ‘We have an important job to do, but we’re going to hire dogs and cats to do it.'”[27]

Writings

  • "Why AM and Eurisko Appear to Work," (Lenat and John Seely Brown), Proceedings of National Conference on AI (AAAI–83), Washington, DC, August 1983.
  • Davis, Randall; Lenat, Douglas B. (1982). Knowledge-Based Systems in Artificial Intelligence. New York: McGraw-Hill International Book Co. ISBN 978-0-07-015557-2.
  • Hayes-Roth, Frederick; Waterman, Donald Arthur; Lenat, Douglas B., eds. (1983). Building Expert Systems. Reading, Mass: Addison-Wesley Pub. Co. ISBN 978-0-201-10686-2.
  • Lenat, Douglas B. "Computer Software for Intelligent Systems: An Underview of AI," in Scientific American, September 1984.
  • Lenat, Douglas B.; Clarkson, Albert; Kircmidjian, Garo (1983). "An Expert System for Indications & Warning Analysis". Proceedings of the Eighth International Joint Conference on Artificial Intelligence - Volume 1. IJCAI'83. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.: 259–262.[28]
  • Lenat, Douglas B.; Feigenbaum, Edward A. (February 1991). "On the Thresholds of Knowledge". Artif. Intell. 47 (1-3): 185–250. doi:10.1016/0004-3702(91)90055-O. ISSN 0004-3702.[29]
  • Lenat, Douglas B.; Guha, R. V. (1990-01-01). Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Reading, Mass.: Addison-Wesley. ISBN 9780201517521.[30]
  • Lenat, Douglas B. From 2001 to 2001: Common Sense and the Mind of HAL[31]
  • Lenat, Douglas B. (2008-07-10). "The Voice of the Turtle: Whatever Happened to AI?". AI Magazine. 29(2). doi:10.1609/aimag.v29i2.2106. ISSN 0738-4602[32]
  • Blackstone E.H., Lenat, D.B. and Ishwaran H. Infrastructure required to learn which care is best: methods that need to be developed, in (Olsen L., Grossman, C., and McGinnis, M., eds.) Learning What Works: Infrastructure Required for Comparative Effectiveness Research. Institute of Medicine Learning Health System Series, The National Academies Press, pp. 123–144, 2011.
  • Lenat DB, Durlach P. “Reinforcing Math Knowledge by Immersing Students in a Simulated Learning-By-Teaching Experience.” J. International Journal of Artificial Intelligence in Education., 2014
  • Lenat, Douglas B. (2016-04-13). "WWTS (What Would Turing Say?)". AI Magazine. 37 (1): 97–101. doi:10.1609/aimag.v37i1.2644. ISSN 0738-4602[33]
  • See also many of the References, below.

References

  1. ^ Out of their Minds - The Lives and Discoveries of 15 Great Computer Scientists | Dennis Shasha | Springer. Copernicus. Copernicus. 1998. ISBN 9780387982694.
  2. ^ Lenat, Douglas B. (1995). "Artificial Intelligence". Scientific American. 273 (3): 80–82. JSTOR 24981725.
  3. ^ Lenat, Douglas and Greiner, Russell (1980). "RLL: A Representation Language Language". Proceedings of the First AAAI Conference. 1.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  4. ^ Lenat, Douglas B.; Hayes-Roth, Frederick; Klahr, Philip (1979). Cognitive Economy in Artificial Intelligence Systems. Proceedings of the 6th International Joint Conference on Artificial Intelligence - Volume 1. IJCAI'79. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. pp. 531–536. ISBN 978-0934613477.
  5. ^ Lenat, D. B. (March 1989). "Ontological versus knowledge engineering". IEEE Transactions on Knowledge and Data Engineering. 1 (1): 84–88. doi:10.1109/69.43405. ISSN 1041-4347.
  6. ^ Lenat DB, Fishwick PA, Modjeski RB, Oresky CM, Clarkson A, Kaisler S (1991). "STRADS: A Strategic Automatic Discovery System". Knowledge-based Simulation: Methodology and Application.
  7. ^ Lenat, Douglas. "The Heuristics of Nature: The Plausible Mutation of DNA." Stanford Heuristic Programming Project, 1980, technical report HPP-80-27.
  8. ^ Lenat, Douglas B. (1983). "The Role of Heuristics in Learning by Discovery: Three Case Studies". Machine Learning. Symbolic Computation. Springer, Berlin, Heidelberg. pp. 243–306. doi:10.1007/978-3-662-12405-5_9. ISBN 9783662124079.
  9. ^ Lenat, Douglas (1982). "The Nature of Heuristics". Journal of Artificial Intelligence. 19.
  10. ^ Lenat, Douglas (1983). "The Nature of Heuristics II: Theory formation by heuristic search". Journal of Artificial Intelligence. 20.
  11. ^ Lenat, Douglas (1983). "The Nature of Heuristics III: Eurisko". Journal of Artificial Intelligence. 20.
  12. ^ Lenat, Douglas (1984). "The Nature of Heuristics IV: Why AM and Eurisko Appear to Work". Journal of Artificial Intelligence. 23.
  13. ^ Wired Staff. "The Wired 25". WIRED. Retrieved 2017-11-29.
  14. ^ “Progress Report on Program Understanding Systems.” C. Cordell Green, Richard J. Waldinger, David R. Barstow, Robert Elschlager, Douglas B. Lenat, Brian P. McCune, David E. Shaw, and Louis I. Steinberg. Memo AIM-240, Report STAN-CS-74-444, Artificial Intelligence Laboratory, Computer Science Department, Stanford University, Stanford, California, August 1974
  15. ^ Davis, Randall; Lenat, Douglas B. (1982). Knowledge-Based Systems in Artificial Intelligence: 2 Case Studies. New York, NY, USA: McGraw-Hill, Inc. ISBN 978-0070155572.
  16. ^ B., Lenat, Douglas; Gregory, Harris (1977). "Designing a rule system that searches for scientific discoveries". {{cite journal}}: Cite journal requires |journal= (help)
  17. ^ "Heuretics: Theoretical and Experimental Study of Heuristic Rules". www.aaai.org. Retrieved 2017-11-06.
  18. ^ Lenat, Douglas B.; Brown, John Seely (1984-08-01). "Why am and eurisko appear to work". Artificial Intelligence. 23 (3): 269–294. CiteSeerX 10.1.1.565.8830. doi:10.1016/0004-3702(84)90016-X.
  19. ^ Lenat, Douglas B.; Borning, Alan; McDonald, David; Taylor, Craig; Weyer, Steven (1983). "Knoesphere: Building Expert Systems with Encyclopedic Knowledge". Proceedings of the Eighth International Joint Conference on Artificial Intelligence - Volume 1. IJCAI'83: 167–169.
  20. ^ Lenat, Douglas. . Cycorp, Inc. Archived from the original on 2006-10-06. Retrieved 2006-09-26.
  21. ^ The Editors of Time-Life Books (1986). Understanding Computers: Artificial Intelligence. Amsterdam: Time-Life Books. p. 84. ISBN 978-0-7054-0915-5. {{cite book}}: |last= has generic name (help)
  22. ^ Lenat, Douglas; Witbrock, Michael; Baxter, David; Blackstone, Eugene; Deaton, Chris; Schneider, Dave; Scott, Jerry; Shepard, Blake (2010-07-28). "Harnessing Cyc to Answer Clinical Researchers' Ad Hoc Queries". AI Magazine. 31 (3): 13–32. doi:10.1609/aimag.v31i3.2299. ISSN 0738-4602.
  23. ^ Lenat, Douglas B.; Durlach, Paula J. (2014-09-01). "Reinforcing Math Knowledge by Immersing Students in a Simulated Learning-By-Teaching Experience". International Journal of Artificial Intelligence in Education. 24 (3): 216–250. doi:10.1007/s40593-014-0016-x. ISSN 1560-4292. S2CID 72571.
  24. ^ Lenat, Douglas (1988). "The Case for Inelegance". Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications, Tokyo, May 1988.
  25. ^ Wood, Lamont. Cycorp: The Cost of Common Sense, Technology Review, March 2005
  26. ^ "Sometimes the Veneer of Intelligence is Not Enough | CogWorld". cognitiveworld.com. Retrieved 2017-11-29.
  27. ^ Love, Dylan (July 2, 2014). "The Most Ambitious Artificial Intelligence Project In The World Has Been Operating In Near Secrecy For 30 Years". Business Insider. Retrieved October 7, 2020.
  28. ^ Lenat, Douglas B.; Clarkson, Albert; Kircmidjian, Garo (1983). "An Expert System for Indications & Warning Analysis". Proceedings of the Eighth International Joint Conference on Artificial Intelligence - Volume 1. IJCAI'83: 259–262.
  29. ^ Lenat, Douglas B.; Feigenbaum, Edward A. (February 1991). "On the Thresholds of Knowledge". Artif. Intell. 47 (1–3): 185–250. doi:10.1016/0004-3702(91)90055-O. ISSN 0004-3702.
  30. ^ Lenat, Douglas B.; Guha, R. V. (1990-01-01). Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project. Reading, Mass.: Addison-Wesley. ISBN 9780201517521.
  31. ^ Clarke, Arthur C. (1998-02-06). Stork, David G. (ed.). HAL's Legacy: 2001's Computer as Dream and Reality (Reprint ed.). Cambridge, Mass.: The MIT Press. ISBN 9780262692113.
  32. ^ Lenat, Douglas B. (2008-07-10). "The Voice of the Turtle: Whatever Happened to AI?". AI Magazine. 29 (2). doi:10.1609/aimag.v29i2.2106. ISSN 0738-4602.
  33. ^ Lenat, Douglas B. (2016-04-13). "WWTS (What Would Turing Say?)". AI Magazine. 37 (1): 97–101. doi:10.1609/aimag.v37i1.2644. ISSN 0738-4602.

External links

  • Douglas Lenat bio page at Cyc.com 2015-05-23 at the Wayback Machine
  • "Beyond the Semantic Web" video lecture at NIPS 2008.
  • "How David Beats Goliath" article at The New Yorker.


March 04, 2023
douglas, lenat, this, article, contains, content, that, written, like, advertisement, please, help, improve, removing, promotional, content, inappropriate, external, links, adding, encyclopedic, content, written, from, neutral, point, view, january, 2023, lear. This article contains content that is written like an advertisement Please help improve it by removing promotional content and inappropriate external links and by adding encyclopedic content written from a neutral point of view January 2023 Learn how and when to remove this template message Douglas Bruce Lenat born 1950 is the CEO of Cycorp Inc of Austin Texas and has been a prominent researcher 1 in artificial intelligence 2 Lenat was awarded the biannual IJCAI Computers and Thought Award in 1976 for creating the machine learning program AM He has worked on symbolic not statistical machine learning with his AM and Eurisko programs knowledge representation 3 cognitive economy 4 blackboard systems and what he dubbed in 1984 ontological engineering 5 with his Cyc program at MCC and since 1994 at Cycorp He has also worked in military simulations 6 and numerous projects for US government military intelligence and scientific organizations In 1980 he published a critique of conventional random mutation Darwinism 7 8 He authored a series of articles 9 10 11 12 in the Journal of Artificial Intelligence exploring the nature of heuristic rules Douglas LenatBornSeptember 13 1950Philadelphia PennsylvaniaNationalityAmericanEducationUniversity of Pennsylvania Stanford University Ph D OccupationComputer scientistEmployerCycorp Inc Known forLisp programming language CEO of Cycorp Inc AM Eurisko CycAwards1977 IJCAI Computers and Thought AwardLenat was one of the original Fellows of the AAAI and is the only individual to have served on the Scientific Advisory Boards of both Microsoft and Apple He is a Fellow of the AAAS AAAI and Cognitive Science Society and an editor of the J Automated Reasoning J Learning Sciences and J Applied Ontology He was one of the founders of TTI Vanguard in 1991 and remains a member of its advisory board still in 2017 He was named one of the Wired 25 13 Contents 1 Background and education 2 Research 3 A call for common sense 4 Cycorp 5 Quotes 6 Writings 7 References 8 External linksBackground and education EditLenat was born in Philadelphia Pennsylvania on September 13 1950 and grew up there and from ages 5 15 in Wilmington Delaware He attended Cheltenham High School in Wyncote PA where his after school job at the neighboring Beaver College was cleaning rat cages and then goose pens which motivated him to learn to program as a path to a very different after school and summer job and eventually career While attending the University of Pennsylvania Lenat supported himself through programming notably designing and developing a natural language interface to a U S Navy database question answering system serving as an early online shipboard operations manual used on US aircraft carriers He received his bachelor s degree in Mathematics and Physics and his master s degree in Applied Mathematics all in 1972 from the University of Pennsylvania For his senior thesis advised in part by Dennis Gabor was to bounce acoustic waves in the 40 mHz range off real world objects record their interference patterns on a 2 meter square plot photo reduce those to a 10 mm square film image shine a laser through the film and thus project the three dimensional imaged object i e the first known acoustic hologram To settle an argument with Dr Gabor Lenat computer generated a five dimensional hologram by photo reducing computer printout of the interference pattern of a globe rotating and expanding over time reducing the large two dimensional paper printout to a moderately large 5 cm square film surface through which a conventional laser beam was then able to project a three dimensional image which changed in two independent ways rotating and changing in size as the film was moved up down or left right Lenat was a Ph D student in Computer Science at Stanford University where his published research included automatic program synthesis from input output pairs and from natural language clarification dialogues 14 Research EditHe received his Ph D in Computer Science from Stanford University published as Knowledge based systems in artificial intelligence 15 along with the Ph D thesis of Randall Davis McGraw Hill 1982 in 1976 His thesis advisor was Professor Cordell Green and his thesis oral committee included Professors Edward Feigenbaum Joshua Lederberg Paul Cohen Allen Newell Herbert Simon Bruce Buchanan John McCarthy and Donald Knuth His thesis AM Automated Mathematician was one of the first computer programs that attempted to make discoveries i e to be a theorem proposer rather than a theorem prover Experimenting with the program fueled a cycle of criticism and improvement leading to a slightly deeper understanding of human creativity Many issues had to be dealt with in constructing such a program how to represent knowledge formally expressively and concretely how to program hundreds of heuristic interestingness rules to judge the worth of new discoveries heuristics for when to reason symbolically and inductively and slowly versus when to reason statistically from frequency data and hence quickly what the architecture the design constraints of such reasoning programs might be why heuristics work in sum because the future is a continuous function of the past and what their inner structure might be AM was one of the first halting steps toward a science of learning by discovery toward de mystifying the creative process and demonstrating that computer programs can make novel and creative discoveries 16 In 1976 Lenat started teaching as an assistant professor of Computer Science at Carnegie Mellon and commenced his work on the AI program Eurisko The limitation with AM was that it was locked into following a fixed set of interestingness heuristics Eurisko by contrast represented its heuristic rules as first class objects and hence it could explore manipulate and discover new heuristics just as it and AM explored manipulated and discovered new domain concepts Lenat returned to Stanford as an assistant professor of Computer Science in 1978 and continued his research building the Eurisko automated discovery and heuristic discovery program Eurisko made many interesting discoveries and enjoyed significant acclaim with Lenat s paper Heuretics Theoretical and Experimental Study of Heuristic Rules 17 winning the Best Paper award at the 1982 AAAI conference A call for common sense EditUnlike the vast preponderance of published scientific results Lenat working with John Seely Brown at Xerox PARC published in 1984 a thorough and frank analysis of what were the limitations of his AM and Eurisko lines of research 18 It concluded that progress toward real general symbolic AI would require a vast knowledge base of common sense suitably formalized and represented and an inference engine capable of finding tens or hundreds deep conclusions and arguments that followed from the application of that knowledge base to specific questions and applications 19 The successes and frank analysis of the limitations of this AM and Eurisko approach to AI and the concluding plea for the massive multi thousand person year decades long R amp D effort would be required to break that bottleneck to AI led to attention in 1982 from Admiral Bob Inman and the then forming MCC research consortium in Austin Texas culminating in Lenat s becoming Principal Scientist of MCC from 1984 1994 though he continued even after this period to return to Stanford to teach approximately one course per year At the 400 person MCC Lenat was able to have several dozen researchers work on that common sense knowledge base rather than just a few graduate students Cycorp EditThe fruits of the first decade of R amp D on Cyc 20 were spun out of MCC into a company Cycorp at the end of 1994 In 1986 he estimated the effort to complete Cyc would be at least 250 000 rules and 1 000 person years of effort 21 probably twice that and by 2017 he and his team had spent about 2 000 person years of effort building Cyc creating approximately 24 million rules and assertions not counting facts Lenat emphasizes that he and his 60 person R amp D team strive to keep those numbers as small as possible even the number of one step inferences in Cyc s deductive closure is in the hundreds of trillions As of 2018 update Lenat continues his work on Cyc as CEO of Cycorp While the first decade of work on Cyc 1984 1994 was funded by large American companies pooling long term research funds to compete with the Japanese Fifth Generation Computer Project and the second decade 1995 2006 of work on Cyc was funded by US government agencies research contracts the third decade up through the present 2007 present has been largely supported through commercial applications of Cyc including in the financial services energy and healthcare areas 22 Among the recent when Cyc applications one unusual one MathCraft involves helping middle school students more deeply understand math 23 Most people have had the experience where we thought we understood something but only really understood it when we had to explain or teach it to someone else Despite that almost all AI aided instruction has the AI play the role of the teacher In contrast Mathcraft has the AI Cyc play the role of a fellow student who is always very slightly more confused than you the user are As you give MathCraft good advice it allows that avatar to make fewer mistakes of that kind and from the point of the user it seems as though they have taught it something This sort of Learning by Teaching paradigm may have broad applications in future domains where training is involved Quotes Edit Doug Lenat in his office at Cycorp Intelligence is ten million rules 24 This refers to the prior and tacit knowledge that authors presume their readers all possess such as if person x knows person y then x s date of death can t be earlier than y s date of birth not counting the vastly larger number of facts such as one might find in Wikipedia or by Googling The time may come when a greatly expanded Cyc will underlie countless software applications But reaching that goal could easily take another two decades 25 Once you have a truly massive amount of information integrated as knowledge then the human software system will be superhuman in the same sense that mankind with writing or language itself is superhuman compared to mankind before writing or language itself We look back on pre linguistic cavemen and think they weren t quite human were they In much the same way our descendants will look back on pre AI homo sapiens with exactly that mixture of otherness and pity This quote needs a citation Sometimes the veneer of intelligence is not enough 26 If computers were human they d present themselves as autistic schizophrenic or otherwise brittle It would be unwise or dangerous for that person to take care of children and cook meals but it s on the horizon for home robots That s like saying We have an important job to do but we re going to hire dogs and cats to do it 27 Writings Edit Why AM and Eurisko Appear to Work Lenat and John Seely Brown Proceedings of National Conference on AI AAAI 83 Washington DC August 1983 Davis Randall Lenat Douglas B 1982 Knowledge Based Systems in Artificial Intelligence New York McGraw Hill International Book Co ISBN 978 0 07 015557 2 Hayes Roth Frederick Waterman Donald Arthur Lenat Douglas B eds 1983 Building Expert Systems Reading Mass Addison Wesley Pub Co ISBN 978 0 201 10686 2 Lenat Douglas B Computer Software for Intelligent Systems An Underview of AI in Scientific American September 1984 Lenat Douglas B Clarkson Albert Kircmidjian Garo 1983 An Expert System for Indications amp Warning Analysis Proceedings of the Eighth International Joint Conference on Artificial Intelligence Volume 1 IJCAI 83 San Francisco CA USA Morgan Kaufmann Publishers Inc 259 262 28 Lenat Douglas B Feigenbaum Edward A February 1991 On the Thresholds of Knowledge Artif Intell 47 1 3 185 250 doi 10 1016 0004 3702 91 90055 O ISSN 0004 3702 29 Lenat Douglas B Guha R V 1990 01 01 Building Large Knowledge Based Systems Representation and Inference in the Cyc Project Reading Mass Addison Wesley ISBN 9780201517521 30 Lenat Douglas B From 2001 to 2001 Common Sense and the Mind of HAL 31 Lenat Douglas B 2008 07 10 The Voice of the Turtle Whatever Happened to AI AI Magazine 29 2 doi 10 1609 aimag v29i2 2106 ISSN 0738 4602 32 Blackstone E H Lenat D B and Ishwaran H Infrastructure required to learn which care is best methods that need to be developed in Olsen L Grossman C and McGinnis M eds Learning What Works Infrastructure Required for Comparative Effectiveness Research Institute of Medicine Learning Health System Series The National Academies Press pp 123 144 2011 Lenat DB Durlach P Reinforcing Math Knowledge by Immersing Students in a Simulated Learning By Teaching Experience J International Journal of Artificial Intelligence in Education 2014 Lenat Douglas B 2016 04 13 WWTS What Would Turing Say AI Magazine 37 1 97 101 doi 10 1609 aimag v37i1 2644 ISSN 0738 4602 33 See also many of the References below References Edit Out of their Minds The Lives and Discoveries of 15 Great Computer Scientists Dennis Shasha Springer Copernicus Copernicus 1998 ISBN 9780387982694 Lenat Douglas B 1995 Artificial Intelligence Scientific American 273 3 80 82 JSTOR 24981725 Lenat Douglas and Greiner Russell 1980 RLL A Representation Language Language Proceedings of the First AAAI Conference 1 a href Template Cite journal html title Template Cite journal cite journal a CS1 maint multiple names authors list link Lenat Douglas B Hayes Roth Frederick Klahr Philip 1979 Cognitive Economy in Artificial Intelligence Systems Proceedings of the 6th International Joint Conference on Artificial Intelligence Volume 1 IJCAI 79 San Francisco CA USA Morgan Kaufmann Publishers Inc pp 531 536 ISBN 978 0934613477 Lenat D B March 1989 Ontological versus knowledge engineering IEEE Transactions on Knowledge and Data Engineering 1 1 84 88 doi 10 1109 69 43405 ISSN 1041 4347 Lenat DB Fishwick PA Modjeski RB Oresky CM Clarkson A Kaisler S 1991 STRADS A Strategic Automatic Discovery System Knowledge based Simulation Methodology and Application Lenat Douglas The Heuristics of Nature The Plausible Mutation of DNA Stanford Heuristic Programming Project 1980 technical report HPP 80 27 Lenat Douglas B 1983 The Role of Heuristics in Learning by Discovery Three Case Studies Machine Learning Symbolic Computation Springer Berlin Heidelberg pp 243 306 doi 10 1007 978 3 662 12405 5 9 ISBN 9783662124079 Lenat Douglas 1982 The Nature of Heuristics Journal of Artificial Intelligence 19 Lenat Douglas 1983 The Nature of Heuristics II Theory formation by heuristic search Journal of Artificial Intelligence 20 Lenat Douglas 1983 The Nature of Heuristics III Eurisko Journal of Artificial Intelligence 20 Lenat Douglas 1984 The Nature of Heuristics IV Why AM and Eurisko Appear to Work Journal of Artificial Intelligence 23 Wired Staff The Wired 25 WIRED Retrieved 2017 11 29 Progress Report on Program Understanding Systems C Cordell Green Richard J Waldinger David R Barstow Robert Elschlager Douglas B Lenat Brian P McCune David E Shaw and Louis I Steinberg Memo AIM 240 Report STAN CS 74 444 Artificial Intelligence Laboratory Computer Science Department Stanford University Stanford California August 1974 Davis Randall Lenat Douglas B 1982 Knowledge Based Systems in Artificial Intelligence 2 Case Studies New York NY USA McGraw Hill Inc ISBN 978 0070155572 B Lenat Douglas Gregory Harris 1977 Designing a rule system that searches for scientific discoveries a href Template Cite journal html title Template Cite journal cite journal a Cite journal requires journal help Heuretics Theoretical and Experimental Study of Heuristic Rules www aaai org Retrieved 2017 11 06 Lenat Douglas B Brown John Seely 1984 08 01 Why am and eurisko appear to work Artificial Intelligence 23 3 269 294 CiteSeerX 10 1 1 565 8830 doi 10 1016 0004 3702 84 90016 X Lenat Douglas B Borning Alan McDonald David Taylor Craig Weyer Steven 1983 Knoesphere Building Expert Systems with Encyclopedic Knowledge Proceedings of the Eighth International Joint Conference on Artificial Intelligence Volume 1 IJCAI 83 167 169 Lenat Douglas Hal s Legacy 2001 s Computer as Dream and Reality From 2001 to 2001 Common Sense and the Mind of HAL Cycorp Inc Archived from the original on 2006 10 06 Retrieved 2006 09 26 The Editors of Time Life Books 1986 Understanding Computers Artificial Intelligence Amsterdam Time Life Books p 84 ISBN 978 0 7054 0915 5 a href Template Cite book html title Template Cite book cite book a last has generic name help Lenat Douglas Witbrock Michael Baxter David Blackstone Eugene Deaton Chris Schneider Dave Scott Jerry Shepard Blake 2010 07 28 Harnessing Cyc to Answer Clinical Researchers Ad Hoc Queries AI Magazine 31 3 13 32 doi 10 1609 aimag v31i3 2299 ISSN 0738 4602 Lenat Douglas B Durlach Paula J 2014 09 01 Reinforcing Math Knowledge by Immersing Students in a Simulated Learning By Teaching Experience International Journal of Artificial Intelligence in Education 24 3 216 250 doi 10 1007 s40593 014 0016 x ISSN 1560 4292 S2CID 72571 Lenat Douglas 1988 The Case for Inelegance Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications Tokyo May 1988 Wood Lamont Cycorp The Cost of Common Sense Technology Review March 2005 Sometimes the Veneer of Intelligence is Not Enough CogWorld cognitiveworld com Retrieved 2017 11 29 Love Dylan July 2 2014 The Most Ambitious Artificial Intelligence Project In The World Has Been Operating In Near Secrecy For 30 Years Business Insider Retrieved October 7 2020 Lenat Douglas B Clarkson Albert Kircmidjian Garo 1983 An Expert System for Indications amp Warning Analysis Proceedings of the Eighth International Joint Conference on Artificial Intelligence Volume 1 IJCAI 83 259 262 Lenat Douglas B Feigenbaum Edward A February 1991 On the Thresholds of Knowledge Artif Intell 47 1 3 185 250 doi 10 1016 0004 3702 91 90055 O ISSN 0004 3702 Lenat Douglas B Guha R V 1990 01 01 Building Large Knowledge Based Systems Representation and Inference in the Cyc Project Reading Mass Addison Wesley ISBN 9780201517521 Clarke Arthur C 1998 02 06 Stork David G ed HAL s Legacy 2001 s Computer as Dream and Reality Reprint ed Cambridge Mass The MIT Press ISBN 9780262692113 Lenat Douglas B 2008 07 10 The Voice of the Turtle Whatever Happened to AI AI Magazine 29 2 doi 10 1609 aimag v29i2 2106 ISSN 0738 4602 Lenat Douglas B 2016 04 13 WWTS What Would Turing Say AI Magazine 37 1 97 101 doi 10 1609 aimag v37i1 2644 ISSN 0738 4602 External links EditDouglas Lenat bio page at Cyc com Archived 2015 05 23 at the Wayback Machine Beyond the Semantic Web video lecture at NIPS 2008 How David Beats Goliath article at The New Yorker Retrieved from https en wikipedia org w index php title Douglas Lenat amp oldid 1136495229, wikipedia, wiki, book, books, library,

article

, read, download, free, free download, mp3, video, mp4, 3gp, jpg, jpeg, gif, png, picture, music, song, movie, book, game, games.