Back in my NEC days, some of the AI folks there wrote a similar program for the game show Who Wants to be a Millionaire, although the program was never considered for use on the real show. Unlike Jeopardy, Millionaire had multiple choice answers and their program basically did keyword matching on Google searches. Their program did quite well on the very specific high-dollar questions. But their program often stumbled on the low-dollar easy questions which relied on basic knowledge.
This Jeopardy computer experiment still seems to me comparing apples to oranges. Humans have little trouble interpreting the meaning of the "answers" in Jeopardy, they are being tested on their knowledge of that material. The computer has access to all that knowledge but doesn't know how to match it up to simple English sentences. I suspect the computer will win this fight for it has the ultimate Jeopardy advantage: it can buzz in faster.
Obama vows investment in science
ReplyDeletehttp://news.bbc.co.uk/2/hi/science/nature/8020930.stm
Link to the "NEC days" paper (thanks Lance): Shyong K. Lam, David M. Pennock, Dan Cosley, and Steve Lawrence. 1 Billion Pages = 1 Million Dollars? Mining the Web to Play "Who Wants to be a Millionaire?", Conference on Uncertainty in Artificial Intelligence, pp. 337-345, 2003.
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