In an historic event in February 2011, IBM's Watson computer competed on Jeopardy! against the TV quiz show's two biggest all-time champions. Watson is a computer running software called Deep QA, developed by IBM Research. While the grand challenge driving the project was to win on Jeopardy!, the broader goal of Watson was to create a new generation of technology that can find answers in unstructured data more effectively than standard search technology.
Computer systems that can directly and accurately answer peoples' questions over a broad domain of human knowledge have been envisioned by scientists and writers since the advent of computers themselves. Open domain question answering holds tremendous promise for facilitating informed decision making over vast volumes of natural language content. Applications in business intelligence, healthcare, customer support, enterprise knowledge management, social computing, science and government could all benefit from computer systems capable of deeper language understanding. The DeepQA project is aimed at exploring how advancing and integrating Natural Language Processing (NLP), Information Retrieval (IR), Machine Learning (ML), Knowledge Representation and Reasoning (KR&R) and massively parallel computation can greatly advance the science and application of automatic Question Answering.
Dr. Ferrucci is an IBM Fellow and Watson Principal Investigator for IBM Research. Richard Waters is the West Coast Editor for the Financial Times. Join them for a fascinating exploration of how the Watson project began, its ancestry, the epic Jeopardy! win, and the ways Watson technology can improve human decision-making.