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Last year, a question-answering system built at IBM, named Watson, won the game show Jeopardy! The system combines a large database of knowledge with natural language processing abilities. IBM researchers are now investigating how to use Watson in specialized domains, including health care. On November 9, Alfio Gliozzo, a member of the research staff at the IBM T.J. Watson Research Center, gave a talk at ICSI about the future of Watson. We have now made the slides available. Below is the abstract and Gliozzo's bio.

Abstract

Watson is a computer system built to answer rich natural language questions over a broad open domain with confidence, precision, and speed. IBM demonstrated Watson's capabilities in a historic exhibition match on the television quiz show Jeopardy!, where Watson triumphed over the best Jeopardy! players of all time. The new challenge for IBM is to adapt Watson to important business problems and to make this process scalable while requiring minimal effort. In this talk I describe the DeepQA framework implemented by Watson, focusing on the adaptation methodology and presenting new research directions, with emphasis on unsupervised learning technology for distributional semantics linking text to knowledge bases.

Speaker Bio

Alfio Gliozzo is a research staff member at the IBM T.J. Watson Research Center. He is currently a technical leader on the DeepQA team, coordinating a research team focused on unsupervised learning from text. At the same time, he is a key contributor of the Watson core technology for domain adaptation. He has been involved in both academic research and industry for 12 years, achieving a significant track record in delivering semantic technologies across different applications, patents and scientific publications.

View the slides from the talk.