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“Question Answering” is technology's next grand challenge
IBM has unveiled the details of its plans to build a computing system that can understand complex questions and answer with enough precision and speed to compete on America's favorite quiz show, Jeopardy!.
Produced by Sony Pictures Television and distributed by CBS Television Distribution, Jeopardy! is a game demanding knowledge and quick recall, covering a broad range of topics, such as history, literature, politics, film, pop culture, and science. It poses a grand challenge for a computing system due to the variety of subject matter, the speed at which contestants must provide accurate responses, and because the clues given to contestants involve analyzing subtle meaning, irony, riddles, and other complexities at which humans excel and computers traditionally do not.
IBM's computing system called a Question Answering (QA) system among computer scientists has been under development for nearly two years. With the April 27 announcement, IBM's researchers plan to put it to the test in a machine versus human contest on the gold-standard quiz show. And, officials from Jeopardy! announced plans to produce a human vs. machine contest on the renowned show.
Code-named "Watson," the IBM computing system is being designed to rival the human mind's ability to determine precise answers to natural language questions and to compute accurate confidences in the answers. According to Dr. David Ferrucci, leader of the project team, "The confidence processing ability is key to winning at Jeopardy! and is critical to implementing useful business applications of Question Answering."
Watson will also incorporate massively parallel analytical capabilities and, just like human competitors, Watson will not be connected to the Internet or have any other outside assistance.
Useful business applications are the ultimate goal of the Watson project. Such applications would be able to handle semantics (the meaning behind words) and answer more complex questions that require the identification of relevant and irrelevant content and the interpretation of expressive language along with the logical inference to deliver precise final answers and clear justifications. For it to be useful to people and business, a QA system must perform these functions as quickly or nearly as quickly as a human being can; humans, after all, have the ability to know what they know in less than a second.
