While current computers can store and deliver a wealth of digital content created by humans, they are unable to operate over it in human terms. The quest for building a computer system that can do open-domain Question Answering is ultimately driven by a broader vision that sees computers operating more effectively in human terms rather than strictly computer terms. They should function in ways that understand complex information requirements, as people would express them, for example, in natural language questions or interactive dialogs. Computers should deliver precise, meaningful responses, and synthesize, integrate, and rapidly reason over the breadth of human knowledge as it is most rapidly and naturally produced -- in natural language text.
The possibilities for enriching our global community and accelerating the pace at which we can exploit and expand human knowledge, solve problems and help each other in ways never before imagined, rests on our ability to bring information technology out of the era of operating in computer terms and into the era of operating in human terms.
The DeepQA project at IBM shapes a grand challenge in Computer Science that aims to illustrate how the wide and growing accessibility of natural language content and the integration and advancement of Natural Language Processing, Information Retrieval, Machine Learning, Knowledge Representation and Reasoning, and massively parallel computation can drive open-domain automatic Question Answering technology to a point where it clearly and consistently rivals the best human performance.
A first stop along the way is the Jeopardy! Challenge...
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Play against I.B.M.’s question-answering supercomputer.
