Named after IBM’s first CEO Thomas J. Watson, Watson is a supercomputer able to answer questions posed in natural language. It first became famous in early 2011 for beating a couple of the best players of Jeopardy in a 3 day streak game. He beat Ken Jennings and Brad Rutter, the first had 74 winnings in a row and the second had earned a total of $3.25 million. At the time Watson was about the size of a room. It was hot and very noisy because of the cooling systems. He was represented in the room by a simple avatar. Today, Watson has changed a lot. Now it is more business friendly and has lost a lot of weight. From a Jeopardy winning computer it has become a successful commercialized supercomputer. In the following chapters I will talk
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The task is not to give an answer, but to find an appropriate question. He thought it would take a special computer to do the task. It was Charles Lickel who took on the challenge. He was out one night with his team and there was a game of Jeopardy on TV. It was Ken Jennings with his winning streak. That sparked his interest and he tried to convince the other members of his team. The initial reaction was negative. It seemed like a silly project to them, and also very hard to carry out. Anyway, a team of people willing to work on the project was assembled. Since it was a Grand Challenge, commercialization wasn’t a priority. Instead a demonstration was on the top of the list. The hopes that this project would actually make it were thin. Small-sized the project was funded from the researchers everyday budged. No additional budget was granted and the team was free to operate without pressure. The machine had to take as input Jeopardy’s tricky clues, understand them, and give the correct response, the question.
Working to create Watson(DeepQA)
To carry out the task, DeepQA was developed. It was a huge parallel software architecture build to examine natural language content. It had to examine the clues set by the game and also inside Watson’s own stored data of structured information. The system was made of pluggable components for searching and weighting information. The team of 20 researchers needed 3 years to turn this system