Summary
Cyc (pronounced ˈsaɪk ) is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge that other AI platforms may take for granted. This is contrasted with facts one might find somewhere on the internet or retrieve via a search engine or Wikipedia. Cyc enables semantic reasoners to perform human-like reasoning and be less "brittle" when confronted with novel situations. Douglas Lenat began the project in July 1984 at MCC, where he was Principal Scientist 1984–1994, and then, since January 1995, has been under active development by the Cycorp company, where he is the CEO. The need for a massive symbolic artificial intelligence project of this kind was born in the early 1980s. Early AI researchers had ample experience over the previous 25 years with AI programs that would generate encouraging early results but then fail to "scale up"—move beyond the 'training set' to tackle a broader range of cases. Douglas Lenat and Alan Kay publicized this need, and they organized a meeting at Stanford in 1983 to address the problem. The back-of-the-envelope calculations by Lenat, Kay, and their colleagues (including Marvin Minsky, Allen Newell, Edward Feigenbaum, and John McCarthy) indicated that that effort would require between 1000 and 3000 person-years of effort, far beyond the standard academic project model. However, events within a year of that meeting enabled an effort of that scale to get underway. The project began in July 1984 as the flagship project of the 400-person Microelectronics and Computer Technology Corporation (MCC), a research consortium started by two dozen large United States based corporations "to counter a then ominous Japanese effort in AI, the so-called "fifth-generation" project.
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