Edward A. Feigenbaum Papers SC0340
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University of Navarra Ecclesiastical Faculty of Philosophy
UNIVERSITY OF NAVARRA ECCLESIASTICAL FACULTY OF PHILOSOPHY Mark Telford Georges THE PROBLEM OF STORING COMMON SENSE IN ARTIFICIAL INTELLIGENCE Context in CYC Doctoral dissertation directed by Dr. Jaime Nubiola Pamplona, 2000 1 Table of Contents ABBREVIATIONS ............................................................................................................................. 4 INTRODUCTION............................................................................................................................... 5 CHAPTER I: A SHORT HISTORY OF ARTIFICIAL INTELLIGENCE .................................. 9 1.1. THE ORIGIN AND USE OF THE TERM “ARTIFICIAL INTELLIGENCE”.............................................. 9 1.1.1. Influences in AI................................................................................................................ 10 1.1.2. “Artificial Intelligence” in popular culture..................................................................... 11 1.1.3. “Artificial Intelligence” in Applied AI ............................................................................ 12 1.1.4. Human AI and alien AI....................................................................................................14 1.1.5. “Artificial Intelligence” in Cognitive Science................................................................. 16 1.2. TRENDS IN AI........................................................................................................................... 17 1.2.1. Classical AI .................................................................................................................... -
David Luckham Is the Keynote Speaker at Pen,” He Says
45-iAGEJul-Influ 14/7/04 4:02 pm Page 45 PERSPECTIVE INFLUENCER Man of events or the first year after David vision. As they do so, they will undoubt- Luckham’s book, The Power of Events, edly turn to Luckham’s book for a was published in 2002, it did what grounding in the design principles. F Power of Events most technical books do: disappeared The is based on years of into the academic ether. The publishers, research work at Stanford and two years he says, didn’t promote it at all, and its as CTO of a software start-up working in technical nature put it beyond the reach the field. The book is a technical mani- of most readers. festo for CEP – the ability of systems to As a result, it looked like the ‘event- recognise and respond to complex, inter- driven revolution’, of which the Stanford related events in real time. University Emeritus Professor is the lead- Luckham has spent 22 years as a ing and most passionate advocate, would Professor of Electrical Engineering at be postponed for a few years more. Stanford, and many years before that Stanford University But then, in mid-2003, two important doing ground-breaking work at Emeritus Professor David US technical journals gave the book Harvard, Stanford, UCLA and MIT. But highly positive reviews, and interest his presentations, and the first half of Luckham has spent began to grow. Sales began to rise, at first his book, at least, are in plain English, decades studying event slowly, then dramatically. Luckham star- full of clear examples of why CEP will processing. -
Prominence of Expert System and Case Study- DENDRAL Namita Mirjankar, Shruti Ghatnatti Karnataka, India [email protected],[email protected]
International Journal of Advanced Networking & Applications (IJANA) ISSN: 0975-0282 Prominence of Expert System and Case Study- DENDRAL Namita Mirjankar, Shruti Ghatnatti Karnataka, India [email protected],[email protected] Abstract—Among many applications of Artificial Intelligence, Expert System is the one that exploits human knowledge to solve problems which ordinarily would require human insight. Expert systems are designed to carry the insight and knowledge found in the experts in a particular field and take decisions based on the accumulated knowledge of the knowledge base along with an arrangement of standards and principles of inference engine, and at the same time, justify those decisions with the help of explanation facility. Inference engine is continuously updated as new conclusions are drawn from each new certainty in the knowledge base which triggers extra guidelines, heuristics and rules in the inference engine. This paper explains the basic architecture of Expert System , its first ever success DENDRAL which became a stepping stone in the Artificial Intelligence field, as well as the difficulties faced by the Expert Systems Keywords—Artificial Intelligence; Expert System architecture; knowledge base; inference engine; DENDRAL I INTRODUCTION the main components that remain same are: User Interface, Knowledge Base and Inference Engine. For more than two thousand years, rationalists all over the world have been striving to comprehend and resolve two unavoidable issues of the universe: how does a human mind work, and can non-people have minds? In any case, these inquiries are still unanswered. As humans, we all are blessed with the ability to learn and comprehend, to think about different issues and to decide; but can we design machines to do all these things? Some philosophers are open to the idea that machines will perform all the tasks a human can do. -
Assessing the Impacts of Changes in the Information Technology R&D Ecosystem: Retaining Leadership in an Increasingly Global Environment
This PDF is available from The National Academies Press at http://www.nap.edu/catalog.php?record_id=12174 Assessing the Impacts of Changes in the Information Technology R&D Ecosystem: Retaining Leadership in an Increasingly Global Environment ISBN Committee on Assessing the Impacts of Changes in the Information 978-0-309-11882-8 Technology R & D Ecosystem: Retaining Leadership in an Increasingly Global Environment; National Research Council 204 pages 6 x 9 PAPERBACK (2009) Visit the National Academies Press online and register for... Instant access to free PDF downloads of titles from the NATIONAL ACADEMY OF SCIENCES NATIONAL ACADEMY OF ENGINEERING INSTITUTE OF MEDICINE NATIONAL RESEARCH COUNCIL 10% off print titles Custom notification of new releases in your field of interest Special offers and discounts Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the National Academies Press. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Request reprint permission for this book Copyright © National Academy of Sciences. All rights reserved. Assessing the Impacts of Changes in the Information Technology R&D Ecosystem: Retaining Leadership in an Increasingly Global Environment Committee on Assessing the Impacts of Changes in the Information Technology Research and Development Ecosystem Computer Science and Telecommunications Board Division on Engineering and Physical Sciences Copyright © National Academy of Sciences. All rights reserved. Assessing the Impacts of Changes in the Information Technology R&D Ecosystem: Retaining Leadership in an Increasingly Global Environment THE NATIONAL ACADEMIES PRESS 500 Fifth Street, N.W. Washington, DC 20001 NOTICE: The project that is the subject of this report was approved by the Gov- erning Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engi- neering, and the Institute of Medicine. -
Udc 004.838.2 Irsti 20.19.21 Comparative Analysis Of
Comparative analysis of knowledge bases: ConceptNet vs CYC A. Y. Nuraliyeva, S. S. Daukishov, R.T. Nassyrova UDC 004.838.2 IRSTI 20.19.21 COMPARATIVE ANALYSIS OF KNOWLEDGE BASES: CONCEPTNET VS CYC A. Y. Nuraliyeva1, S. S. Daukishov2, R.T. Nassyrova3 1,2Kazakh-British Technical University, Almaty, Kazakhstan 3IT Analyst, Philip Morris Kazakhstan, Almaty, Kazakhstan [email protected], ORCID 0000-0001-6451-3743 [email protected], ORCID 0000-0002-3784-4456 [email protected], ORCID 0000-0002-7968-3195 Abstract. Data summarization, question answering, text categorization are some of the tasks knowledge bases are used for. A knowledge base (KB) is a computerized compilation of information about the world. They can be useful for complex tasks and problems in NLP and they comprise both entities and relations. We performed an analytical comparison of two knowledge bases which capture a wide variety of common-sense information - ConceptNet and Cyc. Manually curated knowledge base Cyc has invested more than 1,000 man-years over the last two decades building a knowledge base that is meant to capture a wide range of common-sense skills. On the other hand, ConceptNet is a free multilingual knowledge base and crowdsourced knowledge initiative that uses a large number of links to connect commonplace items. When looking for common sense logic and answers to questions, ConceptNet is a great place to start. In this research, two well-known knowledge bases were reviewed - ConceptNet and Cyc - their origin, differences, applications, benefits and disadvantages were covered. The authors hope this paper would be useful for researchers looking for more appropriate knowledge bases for word embedding, word sense disambiguation and natural-language communication. -
November 15, 2019, NIH Record, Vol. LXXI, No. 23
November 15, 2019 Vol. LXXI, No. 23 with a brain-controlled robotic exoskeleton who had been paralyzed for 9 years, “didn’t say, ‘I kicked the ball!’” said Nicolelis. More CLINICAL PROMISE SHOWN importantly, he said, “I felt the ball!” It took a team of 156 scientists from Nicolelis Outlines Progress in 25 countries on 5 continents to reach this Brain-Machine Interfaces moment for which neuroscientist Nicolelis BY RICH MCMANUS had been preparing for 20 years. He recruited the team by dangling field tickets to There is probably no other scientist in the World Cup in front of potential recruits. the world for whom peer review meant “It was a hard way to win a free ticket having his experiment succeed in front of a to the game, but that is the Brazilian way,” stadium full of 75,000 screaming Brazilians, quipped Nicolelis, a native of that country. with another 1.2 billion people watching on Now a professor of neuroscience at live television. Duke University School of Medicine, But at the start of the 2014 World Cup at Nicolelis, who won an NIH Pioneer Award Corinthians Arena in Sao Paulo, Dr. Miguel in 2010 for work he said couldn’t earn a Nicolelis witnessed his patient Juliano Pinto, penny of funding a decade earlier, spoke a paraplegic, not only kick a soccer ball to Oct. 16 at an NIH Director’s Lecture in start the tournament, but also “feel” his foot Masur Auditorium. striking the ball. In the late 1980s, Nicolelis, who has been Duke’s Dr. Miguel Nicolelis discusses his research on brain-machine interfaces. -
Awards and Distinguished Papers
Awards and Distinguished Papers IJCAI-15 Award for Research Excellence search agenda in their area and will have a first-rate profile of influential re- search results. e Research Excellence award is given to a scientist who has carried out a e award is named for John McCarthy (1927-2011), who is widely rec- program of research of consistently high quality throughout an entire career ognized as one of the founders of the field of artificial intelligence. As well as yielding several substantial results. Past recipients of this honor are the most giving the discipline its name, McCarthy made fundamental contributions illustrious group of scientists from the field of artificial intelligence: John of lasting importance to computer science in general and artificial intelli- McCarthy (1985), Allen Newell (1989), Marvin Minsky (1991), Raymond gence in particular, including time-sharing operating systems, the LISP pro- Reiter (1993), Herbert Simon (1995), Aravind Joshi (1997), Judea Pearl (1999), Donald Michie (2001), Nils Nilsson (2003), Geoffrey E. Hinton gramming languages, knowledge representation, commonsense reasoning, (2005), Alan Bundy (2007), Victor Lesser (2009), Robert Anthony Kowalski and the logicist paradigm in artificial intelligence. e award was estab- (2011), and Hector Levesque (2013). lished with the full support and encouragement of the McCarthy family. e winner of the 2015 Award for Research Excellence is Barbara Grosz, e winner of the 2015 inaugural John McCarthy Award is Bart Selman, Higgins Professor of Natural Sciences at the School of Engineering and Nat- professor at the Department of Computer Science, Cornell University. Pro- ural Sciences, Harvard University. Professor Grosz is recognized for her pio- fessor Selman is recognized for expanding our understanding of problem neering research in natural language processing and in theories and applica- complexity and developing new algorithms for efficient inference. -
A Closer Look at the Sorption Behavior of Nonionic Surfactants in Marine Sediment
A closer look at the sorption behavior of nonionic surfactants in marine sediment Steven Droge Droge, S. / A closer look at the sorption behavior of nonionic surfactants in marine sediment. PhD thesis, 2008, Institute for Risk Assessment Sciences (IRAS), Utrecht University, The Netherlands ISBN 978-90-393-4774-4 Printed by Ridderprint Cover picture: The Great Wave off Kanagawa by Hokusai (ca. 1830-32) Design by Martijn Dorresteijn A closer look at the sorption behavior of nonionic surfactants in marine sediment Een nadere beschouwing van het sorptiegedrag van niet-ionogene oppervlakte-aktieve stoffen in marien sediment (met een samenvatting in het Nederlands) Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. J. C. Stoof, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op dinsdag 25 maart 2008 des middags te 4.15 uur door Stefanus Theodorus Johannes Droge geboren op 19 februari 1978 te Alkmaar Promotor: Prof.dr. W. Seinen Co-promotor: Dr. J. L. M. Hermens The research described in this thesis was financially supported by ERASM (Environmental Risk Assessment and Management), a joint platform of the European detergent and surfactants producers [A.I.S.E (Association Internationale de la Savonnerie, de la Détergence et des Produits d’Entretien) and CESIO (Comité Européen des Agents Surface et de leurs Intermédiaires Organiques)] CONTENTS Chapter 1 1 General Introduction Chapter 2 25 Analysis of Freely Dissolved Alcohol Ethoxylate Homologues -
“History of Artificial Intelligence (AI)”
The Privacy Foundation “History Of Artificial Intelligence (AI)” 1308 Catalan poet and theologian Ramon Llull publishes Ars generalis ultima (The Ultimate General Art), further perfecting his method of using paper-based mechanical means to create new knowledge from combinations of concepts. 1666 Mathematician and philosopher Gottfried Leibniz publishes Dissertatio de arte combinatoria (On the Combinatorial Art), following Ramon Llull in proposing an alphabet of human thought and arguing that all ideas are nothing but combinations of a relatively small number of simple concepts. 1763 Thomas Bayes develops a framework for reasoning about the probability of events. Bayesian inference will become a leading approach in machine learning. 1898 At an electrical exhibition in the recently completed Madison Square Garden, Nikola Tesla makes a demonstration of the world’s first radio-controlled vessel. The boat was equipped with, as Tesla described, “a borrowed mind.” 1914 The Spanish engineer Leonardo Torres y Quevedo demonstrates the first chess-playing machine, capable of king and rook against king endgames without any human intervention. 1921 Czech writer Karel Čapek introduces the word "robot" in his play R.U.R. (Rossum's Universal Robots). The word "robot" comes from the word "robota" (work). 1925 Houdina Radio Control releases a radio-controlled driverless car, travelling the streets of New York City. 1927 The science-fiction film Metropolis is released. It features a robot double of a peasant girl, Maria, which unleashes chaos in Berlin of 2026—it was the first robot depicted on film, inspiring the Art Deco look of C-3PO in Star Wars. 1929 Makoto Nishimura designs Gakutensoku, Japanese for "learning from the laws of nature," the first robot built in Japan. -
The Computational Attitude in Music Theory
The Computational Attitude in Music Theory Eamonn Bell Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Eamonn Bell All rights reserved ABSTRACT The Computational Attitude in Music Theory Eamonn Bell Music studies’s turn to computation during the twentieth century has engendered particular habits of thought about music, habits that remain in operation long after the music scholar has stepped away from the computer. The computational attitude is a way of thinking about music that is learned at the computer but can be applied away from it. It may be manifest in actual computer use, or in invocations of computationalism, a theory of mind whose influence on twentieth-century music theory is palpable. It may also be manifest in more informal discussions about music, which make liberal use of computational metaphors. In Chapter 1, I describe this attitude, the stakes for considering the computer as one of its instruments, and the kinds of historical sources and methodologies we might draw on to chart its ascendance. The remainder of this dissertation considers distinct and varied cases from the mid-twentieth century in which computers or computationalist musical ideas were used to pursue new musical objects, to quantify and classify musical scores as data, and to instantiate a generally music-structuralist mode of analysis. I present an account of the decades-long effort to prepare an exhaustive and accurate catalog of the all-interval twelve-tone series (Chapter 2). This problem was first posed in the 1920s but was not solved until 1959, when the composer Hanns Jelinek collaborated with the computer engineer Heinz Zemanek to jointly develop and run a computer program. -
Seinfeld's Recent Comments on Zoom…. Energy
Stanford Data Science Departmental 2/4/2021 Seminar Biomedical AI: Its Roots, Evolution, and Early Days at Stanford Edward H. Shortliffe, MD, PhD Chair Emeritus and Adjunct Professor Department of Biomedical Informatics Columbia University Department of Biomedical Data Science Seminar Stanford Medicine Stanford, California 2:30pm – 4:50pm – February 4, 2021 Seinfeld’s recent comments on Zoom…. Energy, attitude and personality cannot be “remoted” through even the best fiber optic lines Jerry Seinfeld: So You Think New York Is ‘Dead’ (It’s not.) Aug. 24, 2020 © E.H. Shortliffe 1 Stanford Data Science Departmental 2/4/2021 Seminar Disclosures • No conflicts of interest with content of presentation • Offering a historical perspective on medical AI, with an emphasis on US activities in the early days and specific work I know personally • My research career was intense until I became a medical school dean in 2007 • Current research involvement is largely as a textbook author and two decades as editor-in-chief of a peer- reviewed journal (Journal of Biomedical Informatics [Elsevier]) Goals for Today’s Presentation • Show that today’s state of the art in medical AI is part of a 50-year scientific trajectory that is still evolving • Provide some advice to today’s biomedical AI researchers, drawing on that experience • Summarize where we are today in the evolution, with suggestions for future emphasis More details on slides than I can include in talk itself – Full deck available after the talk © E.H. Shortliffe 2 Stanford Data Science Departmental -
Benchmarking Semiconductor Lithography Equipment Development & Sourcing Practices Among Leading-Edge U.S
Benchmarking Semiconductor Lithography Equipment Development & Sourcing Practices Among Leading-Edge U.S. Manufacturers by Charles N. Pieczulewski B.S. Materials Science & Engineering, Northwestern University (1992) Submitted to the Department of Materials Science and Engineering in Partial Fulfillment of the Requirements for the Degrees of Master of Science in Materials Science and Engineering and Master of Science in Technology and Policy at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 1995 © Charles N. Pieczulewski 1995. All rights reserved The author hereby grants to MIT permission to reproduce and to distribute publicly copies of this thesis document in whole or in part. Signature of Author C\ THA I ;-T I May 12, 1995 Certified by Professor Charles H. Fine / A Thesis Supervisor Certified by Professor Joel Clark ialsScience and Engineering chnolpgv and Policy Program Accepted by Pf4ssor Richarae Neufville Chairman, Technologyand Policy Program Accepted by Cal V. Thompson II MASSACHUSETTS INSTITUTE Professor of Electronic Materials OF TECHNOLOGY Chair, Departmental Committee on Graduate Students JUL 201995 LIBRARIES as -1- Benchmarking Semiconductor Lithography Equipment Development & Sourcing Practices Among Leading-Edge U.S. Manufacturers Charles N. Pieczulewski ABSTRACT The semiconductor lithography equipment industry has evolved to where knowledge of technology alone is insufficient to survive in the market. An interdisciplinary set of skills has become necessary to fully comprehend the dynamics of the lithography industry. Understanding the fundamental technology, the management issues in a manufacturing equipment market, and the role of industry-sponsored consortia are all critically important to the lithography industry. A dramatic shift in the semiconductor lithography equipment market occurred in the mid-1980s which sparked a furry among political circles in the United States.