Doug B. Lenat
is one of the world's leading computer scientists, and is both the Founder of the CYC¨ project and president of Cycorp in Austin, Texas. He has been Professor of Computer Science at Carnegie-Mellon and Stanford. He is a prolific author, whose hundreds of publications include the books "Knowledge Based Systems in Artificial Intelligence" (1982), "Knowledge Representation" (1988), and "Building Large Knowledge Based Systems" (1989). His 1976 Stanford thesis earned him the bi-annual IJCAI Computers and Thought Award in 1977. He was one of the original Fellows of the American Association for Artificial Intelligence. http://www.cyc.com CYC: Getting a Computer to Extract Meaning from Information Human beings extract meaning from information. They don't just "push it around." Once the meaning is extracted, it can be used to, e.g., infer new conclusions which were not explicitly stated anywhere; or to decide who might want or need to see a particular document. Computers today are, in stark contrast to this, merely idiot-savants. They may manage bits flawlessly and very rapidly, but they have no understanding of what those bits signify. And they have poor models of themselves and of the human beings they serve and represent. The net result of this is that software today is "brittle". We see this when we search the Internet and experience vast amounts of false positives and false negatives. We see this when we make a typing mistake in a spreadsheet and it doesn't complain that we've entered an absurd number. We see this when our speech understanding programs produce silly transcriptions of our spoken sentences. To break that "brittleness bottleneck", we will need a new software layer that contains the millions of things the average person knows about the world. Some of this is factual, such as who's the current President of the US. But most of the needed content is more like rules of thumb, such as why you should carry a glass of water open-end up. In terms of a newspaper or book, we are talking about codifying the whitespace - the things the authors don't need to bother saying (e.g., the White House is in Washington, D.C.; tables have flat horizontal tops; appliances stop working during a power failure.) Since 1984, my team has spent the 4 person-centuries necessary to build that artifact. In this talk, I'll describe what we did, and why, and some of the lessons we learned about representing commonsense knowledge, and doing reasoning in huge knowledge-based systems. I'll discuss some current and future commercial applications of our technology (cyc). One of the major improvements in the last few years in Cyc has come from the introduction of context mechanism, and I will talk some about it here. Contexts have historically been either ignored completely or else treated as indivisible atoms. As part of our work on building Cyc, our group began to study and harness the internal structure of that "atom". Each context was said to have assumptions and content; there was a theory of importing assertions across contexts; contexts were fully reified first-class terms in the CycL representation language; they were partially ordered by specialization to control visibility and access to content; and so on. Over the last few years, we've identified a finer internal structure to a context: a dozen dimensions along which contexts vary; conversely, each region of that 12-dimensional space implicitly defines a context. In effect that space is the space of assumptions, and each assertion can be thought to hold true in some region of that space. A more advanced calculus of contexts is required to handle those 12-dimensional constructs, but it enables a much more efficient, much more focused sort of "virtual lifting" of assertions from one context to another, and - by providing a superstructure that can serve as a principled guide to orient the working KB builder or peruser - makes it easier to specify the proper context in which an assertion (or question) should be stated. The talk will be accompanied by demonstrations including: (a) browsing through the Cyc knowledge base, examining some of the contexts; (b) having Cyc use general and specific knowledge to analyze Middle East crises; (c) using common sense to improve Web search results and follow-up queries. See schedule.	program BILL BUXTON ANDY CAMERON MATTHEW CHALMERS DANIEL DÖGL BILL GAVER NEIL GERSHENFELD ANDREW GLASSNER PAUL HAEBERLI TOM HEWETT BREWSTER KAHLE PANU KORHONEN DOUG LENAT JO LERNOUT RALPH MERKLE THEODOR H. NELSON CELIA PEARCE MARK PESCE HANI RASHID BILL SCHILIT DAVID SMALL MARCO SUSANI JOHN THACKARA MICHAEL FREEDMAN TURNER WHITTED ANTON ZEILINGER
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