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Network World - If you have seen any of the video of its preliminary bouts on "Jeopardy!" you know that IBM's Watson computer is pretty amazing. One of the main reasons it turns out is that IBM enlisted the intelligence of eight of the country's top universities to make sure Watson has superb question answering ability.
Technology research from the schools -- MIT, University of Texas, University of Southern California (USC), Rensselaer Polytechnic Institute (RPI), University at Albany (UAlbany), University of Trento, University of Massachusetts and Carnegie Mellon University -- will help advance Watson's ability to understand all kinds of industries, such as health care, banking, government and more, IBM said.
Watson, named after IBM founder Thomas J. Watson, is programmed to rival the human ability to answer questions posed in natural language with speed and accuracy, IBM stated. Watson's software is runs on IBM POWER7 servers optimized to handle the massive number of tasks it must perform at rapid speeds to analyze complex language and deliver correct responses to "Jeopardy!" clues.
"Applying QA technology to the real-time 'Jeopardy!' problem is an important challenge for the field because it requires a system to respond more quickly and with a level of confidence that has not been possible to-date," says Professor Eric Nyberg of CMU in a statement. "'Jeopardy!' requires forms of reasoning that are quite sophisticated, using metaphors, puns, and puzzles that go beyond basic understanding of the language. As a challenge problem, 'Jeopardy!' will stretch the state of the art." (For an interesting look at the engineering behind Watson, check out this Mashable story.)
According to IBM, the following universities and what they are contributing include:
Carnegie Mellon University: Assisted IBM in the development of the Open Advancement of Question-Answering Initiative (OAQA) architecture and methodology. CMU also made two direct contributions to Watson: a source expansion algorithm which identifies the best text resources for answering questions about given topic, and an answer-scoring algorithm which improves Watson's ability to recognize when a candidate answer is likely to be correct.
MIT: Pioneered an online natural language question answering system called START, which has the ability to answer questions with high precision using information from semi-structured and structured information repositories. The underlying contribution to the Watson system is the ability to break down the question into simple sub-questions for responses to be quickly collected and then fused back together to come up with an answer. The Watson system architecture also took advantage of the object-property-value data model pioneered by MIT, which enables the information in semi-structured data sources to be effectively retrieved in response to natural language questions.
University of Southern California: Focused on large-scale Information Extraction, Parsing, and knowledge inference technologies with the goal of converting large amounts of international source materials into the general knowledge resources of the system, and reasoning with this knowledge to find inconsistencies and gaps.