IBM unveiled details of an advanced computing system that will be able to compete with humans on Jeopardy!, America’s favorite quiz show. Officials from Jeopardy! announced plans to produce a human vs. machine competition on the renowned show.
For nearly two years, IBM scientists have been working on a highly advanced Question Answering (QA) system, codenamed “Watson.” The scientists believe that the computing system will be able to understand complex questions and answer with enough precision and speed to compete on Jeopardy!
Produced by Sony Pictures Television and distributed by CBS Television Distribution, Jeopardy! is a game demanding knowledge and quick recall, covering a broad range of topics, such as history, literature, politics, film, pop culture, and science. It poses a grand challenge for a computing system due to the variety of subject matter, the speed at which contestants must provide accurate responses, and because the clues given to contestants involve analyzing subtle meaning, irony, riddles, and other complexities at which humans excel and computers traditionally do not. Watson will incorporate massively parallel analytical capabilities and, just like human competitors, Watson will not be connected to the Internet or have any other outside assistance.
“The essence of making decisions is recognizing patterns in vast amounts of data, sorting through choices and options, and responding quickly and accurately,” said Samuel J. Palmisano, IBM Chairman, President and Chief Executive Officer. “Watson is a compelling example of how the planet – companies, industries, cities – is becoming smarter. With advanced computing power and deep analytics, we can infuse business and societal systems with intelligence. This project is the latest example of IBM’s longstanding commitment to fundamental research and to overcoming ‘grand challenges’ in science and technology.”
The research underlying Watson is expected to elevate computer intelligence and human-to-computer communication to unprecedented levels. IBM intends to apply the unique technological capabilities being developed for Watson to help clients across a wide variety of industries answer business questions quickly and accurately.
Watson will be designed to deftly handle semantics – the meanings behind words – which will enable it to answer questions that require the identification of relevant and irrelevant content, the interpretation of ambiguous expression and puns, the decomposition of questions into sub-questions, and the logical synthesis of final answers. In addition, Watson will compute a statistical confidence in the responses it provides. Watson will be designed to do all of this in a matter of seconds, which will enable it to compete against humans, who have the ability to know what they know in less than a second.
IBM’s effort to create Watson is aimed at exploring the future of business intelligence, analytics and information management, so that the company can continue to provide its clients with cutting-edge capabilities for finding the information they need from the mountains of data they produce.
In 1997, an IBM computer called Deep Blue defeated World Chess Champion Garry Kasparov in a famous battle of human versus machine. To compete at chess, IBM built an extremely fast computer that could calculate 200 million chess moves per second based on a fixed problem. IBM’s Watson system, on the other hand, is seeking to solve an open-ended problem that requires an entirely new approach – mainly through dynamic, intelligent software – to even come close to competing with the human mind. Despite their massive computational capabilities, today’s computers cannot consistently analyze and comprehend sentences, much less understand cryptic clues and find answers in the same way the human brain can.
Unlike conventional computing technologies designed to return documents containing the user’s keywords or semantic entities, Watson is expected to leap ahead to interpret the user’s query as a true question and to determine precisely what the user is asking for. Watson uses massively parallel processing to simultaneously and instantly understand complex questions – questions that require the system to consider huge volumes and varieties of natural language text to gather and then deeply analyze and score supporting or refuting evidence. The system then decides how confident it is in the answer. This approach marries advanced machine learning and statistical techniques with the latest in natural language processing to result in human-like precision and speed, huge breadth and accurate confidence determination.
“The challenge is to build a system that, unlike systems before it, can rival the human mind’s ability to determine precise answers to natural language questions and to compute accurate confidences in the answers,” said Dr. David Ferrucci, leader of the IBM Watson project team. “This confidence processing ability is key. It greatly distinguishes the IBM approach from conventional search, and is critical to implementing useful business applications of Question Answering.”
In 2008, IBM and Carnegie Mellon University, working with other universities, pioneered the Open Advancement of Question Answering (OAQA) initiative. OAQA aims to provide an architectural and methodological foundation for accelerating research collaboration in automatic question answering. IBM intends to invite universities to collaborate on Watson and other driving challenge problems to help demonstrate how a wide range of independently developed algorithms can be integrated and generalized.