ARMONK, NY and CULVER CITY, CA: For nearly two years, IBM scientists have been working on a highly advanced Question Answering (QA) system, codenamed “Watson.” The scientists believe that their computing system will be able to understand complex questions and answer with enough precision and speed to compete on Jeopardy!, a US quiz show. The Jeopardy! game demands knowledge and quick recall. Its questions cover a broad range of topics such as history, literature, politics, film, pop culture and science.
Officials from Jeopardy! have embraced IBM’s challenge and now plan to produce a human vs. machine competition on the renowned show. A date for the competition has not yet been announced. The series is the top quiz show in syndication with more than 10 million daily viewers and the first syndicated program to be broadcast in high-definition. Reports are that negotiations are under way between the Jeopardy! producers and IBM as to format, rules and contestants. It has been suggested that Ken Jennings, the Jeopardy! contestant who won 74 consecutive times and collected $2.52 million in 2004 should be invited to take on Watson as the ultimate test.
Jeopardy! 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 CEO. “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.”
Watson is being 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 expressions 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.
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. The goal of business intelligence, analytics and information management in the corporate world is to help companies separate 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, Google search for example, Watson is expected to leap ahead to interpret the user’s query as a true question and to determine precisely what the user needs to know. Watson’s massively parallel processing aims to help the system 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. Progress on the underlying QA technologies enabling Watson will be important in the quest to understand and build ‘intelligent computing systems’ capable of cooperating with humans in language-related tasks previously out of reach for computers.”
Watch a video about Watson and its technical abilities at www.youtube.com/watch?v=3e22ufcqfTs.