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On February 14-15, 2011, the world watched IBM’s super computer, Watson, win the question answering gameshow Jeopardy! by soundly defeating two of the show’s greatest champions, Brad Rutter and Ken Jennings. In the defeat, Watson earned three times more money than the nearest human competitor (AP news). If the loss of the world champion chess player, Gary Kasparov, in 1997 to IBM’s super computer Deep Blue hailed the first triumph of computer over man, the Jeopardy! win by Watson clearly marked the second major milestone. People watched in amazement as the computer would listen to the questions being read and answer them in its not exactly human voice.
Watson was built as a question answering computer specifically to compete on Jeopardy!. Behind the voice and logo, visible to the public on the gameshow, IBM computer scientists had built a very complex and powerful computer. Watson represents an important step in the development of artificial intelligence because of the way that it works. Watson is not a single computer program that runs on a machine. Rather, Watson uses many different computer programs to achieve the correct answers it produces. Watson has programs to analyze the written word in books, dictionaries, newspapers, on the web such as Wikipedia, and through other electronic records. It also has programs to recognize and understand the spoken word as well to reply in English for people to understand. Moreover, Watson uses many different programs to generate possible answers to the questions it gets asked. Instead of searching for an answer in a set of known responses, Watson generates many possible answers by breaking the question down into parts and looking for connections in the millions of pages of information it has in its memory. Using different programs running at the same time, Watson generates many possible answers. Next, it identifies the best answers and then ranks these responses against similar answers it knows are correct. Herein lies the power and the limitation of Watson. The part of Watson that has known correct answers was trained by humans. People need to train Watson on what is correct or incorrect. With a good set of known, correct answers, Watson can make very good guesses. Overtime, as Watson develops experience, it can learn from its mistakes as well.
Since the Jeopardy! win, Watson has been used for many question answer type applications. In California, water is a very valuable commodity, especially in agriculture. Watson and the E&J Gallo Winery, teamed up to provide precise vine by vine irrigation to optimize wine quality and water conservation. (IBM) Watson analyzes weather patterns, satellite images, and soil moisture to water just the vines that need it. The result has been better grapes and a 25% reduction in water use. Watson also helps oncologists making treatment decisions for their cancer patients. At the Memorial Sloan Kettering Cancer Center in New York, NY, teams of physicians have worked to train Watson on the best cancer treatments for a patient based on a number of symptoms and clinical information. Watson also consumes thousands of new cancer research papers and clinical studies from around the world (Sloan Kettering). The training from cancer specialists is helping Watson Oncology to become a valuable resource in treatment recommendations. Because Watson needs to be trained, not everything works so well. In a recently publicized move, the MD Anderson Cancer Center in Texas, ended their collaboration with IBM Watson (Forbes) after several years and millions of dollars spent on an attempt to get Watson to help cure cancer. In some cases there are not enough right answers for Watson to work with and it cannot even with its massive computing power make useful recommendations to the scientists trying to cure cancer.
IBM’s question answering super computer Watson wowed the world when it triumphed in Jeopardy! on television. A system of complex computer programs allows Watson to make educated guesses to questions in any topic that it has been trained in such as science or general trivia; however, Watson needs a lot of care and teaching from experts to reach its full potential. It is not all knowing and needs to be pointed in the best directions to help people solve our biggest problems.