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All rights reserved. Skip to main content Skip to main navigation menu Skip to site footer. Watson Research Center Aditya A. Kalyanpur IBM T. Watson Research Center J. Abstract IBM Research undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV Quiz show, Jeopardy!
The extent of the challenge includes fielding a real-time automatic contestant on the show, not merely a laboratory exercise. The Jeopardy! Challenge helped us address requirements that led to the design of the DeepQA architecture and the implementation of Watson. After 3 years of intense research and development by a core team of about 20 researches, Watson is performing at human expert-levels in terms of precision, confidence and speed at the Jeopardy!
Quiz show. Our results strongly suggest that DeepQA is an effective and extensible architecture that may be used as a foundation for combining, deploying, evaluating and advancing a wide range of algorithmic techniques to rapidly advance the field of QA. Nico Schlaefer, Carnegie Mellon University. How to Cite. Ferrucci, D. AI Magazine , 31 3 , Vol 31 No 3: Fall Authors who publish with this journal agree to the following terms:.
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Building Watson: an overview of the DeepQA project
All rights reserved. Skip to main content Skip to main navigation menu Skip to site footer. Watson Research Center Aditya A. Kalyanpur IBM T. Watson Research Center J.
Building Watson: An Overview of the DeepQA Project