Next week, Jeopardy! champions Ken Jennings and Brad Rutter will square off against IBM’s Watson supercomputer in a contest that could alter way humans view their place in the world. Watson will challenge human beings’ superiority in knowledge and reasoning, something that wasn’t really on the line when IBM’s Deep Blue eked out a controversial victory against chess grandmaster Garry Kasparov in 1997. Not only can Watson likely determine the answer to randomly selected questions on the Jeopardy! board, but it can do so incredibly fast. However, developing the complex Question Answering (QA) algorithms necessary to carry out such determinations wasn’t easy, and IBM didn’t operate alone.
IBM announced eight universities Friday — Massachusetts Institute of Technology, University of Texas, University of Southern California, Rensselaer Polytechnic Institute, University at Albany (NY), University of Trento (Italy), University of Massachusetts, and Carnegie Mellon University — that have contributed to Watson thus far. Their efforts range from MIT’s work on START, an “online natural language question answering system … which has the ability to answer questions with high precision using information from semi-structured and structured information repositories,” to RPI’s work on “a visualization component to visually explain to external audiences the massively parallel analytics skills it takes for the Watson computing system to break down a question and formulate a rapid and accurate response to rival a human brain.” It’s all high technology, though, and it helps Watson figure out where to look for information, how to learn from previous questions and, ultimately, to decide whether it’s confident enough to buzz in.
I got a taste of Watson in August when I toured IBM’s Industry Solutions lab in Hawthorne, N.Y., and I have to say it was impressive. Without giving away any of the secrets behind Watson — or any of its potential weaknesses — Principal Investigator for DeepQA David Ferucci gave a sampling of just how deep Watson goes to determine possible answers then pare them down to a final one. It was impressive, and I wasn’t surprised when Watson came out of January practice around ahead of its human competition. As someone who once drove to Los Angeles to try out for Jeopardy, I appreciate how difficult it is for humans to make these types of judgments, and how difficult it must have been to program a computer to do the same.
The techie in me wants Watson to win so the world gets an understanding of what’s possible with algorithms, even beyond the customized experience of browsing Amazon.com, but the human in me wants to cling to that last thread of hope that human judgment can prevail against artificial intelligence. The realist in me knows that Watson will prevail, though, and AI guru Ray Kurzweil agrees. I guess we can all take solace knowing that it takes humans like those who worked on Watson to write such complex software and build such complex systems — for now, at least.
Image courtesy of IBM.
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