Meet Watsons Successors
This is not the first time an IBM supercomputer beat a human being in a game. IBM's Deep Blue supercomputer defeated Gary Kasparov, the grandmaster of chess, in a match in 1997. While many of the most powerful supercomputers in the world are "sons and grandsons" of Deep Blue, the technology remained in very specialized applications, Katharine Fase, vice president of industry solutions and emerging business at IBM Research, told eWEEK. Watson is different in this regard, as the company has been looking at more common applications of the deep Q&A technology. IBM has been pushing health care applications of Watson in various interviews. The company will announce on Feb. 17 a collaboration with Columbia University and the University of Maryland to create a physician's assistant service where doctors will be able to query a cybernetic assistant, according to the New York Times. IBM will also work with Nuance Communications to add voice recognition to the service, which may be available in as few as 18 months, the Times said.Watson can speedily match parts of speech with information it finds, and then picks the most likely answer. Racr, on the other hand, would pull together interrelated facts to understand the context and derive the most likely answer back on background knowledge. Researchers at IBM and various universities will begin developing machines that can begin to teach themselves, Hovy said in the WSJ. The company is also in discussions with a "major consumer electronics retailer" for a version of Watson that could interact with consumers to help make buying decisions or offer technical support, IBM executives told the Times. As Jennings wrote on his Final Jeopardy slate, "I for one welcome our new computer overlords."
IBM has already begun working with computer scientists from around the country on Watson's successor, known as Racr. It stands for either "reading and contextual reasoning" or "reading and contextual reasoner" (researchers haven't settled on which name to use), according to the Wall Street Journal. Racr goes a step further beyond what Watson can do, as it would use its database of information to come up with reasoned responses, Eduard Hovy, director of the Information Sciences Institute at the University of Southern California, told The Wall Street Journal. A Racr model with the ability to learn background knowledge on given topics and then do "reasoning about that" could be reality in five years, Hovy said in the article.