In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed what is now known as the Turing test in artificial intelligence. The idea is that if you are unable to discriminate between a computer and a human who is answering your questions via a keyboard and screen, then the computer is intelligent.
There are many problems with this idea, but despite these problems, it still remains a compelling benchmark, and one that has yet to be reached. But think of the following variation: rather than have your computer and human team answer any old question, the questions have to be similar to what you would expect on the quiz TV show Jeopardy! – clues about trivia in the form of answers to a question that you must come up with.
Even this greatly restricted version of the Turing test is very challenging, but I.B.M.’s machine called “Watson” has recently made intriguing steps toward passing it. Watson takes any Jeopardy-type question and gives a response. It was not developed as a new type of intelligence test, but instead as a grand challenge to beat a human at a language-based task, like a Deep Blue of language (IBM’s Deep Blue chess playing computer beat the world chess champion in 1997). You can challenge it yourself here. It currently uses a fixed set of a large number (in the millions) of documents and a sophisticated parallelized statistical algorithm running on a supercomputer. By being parallelized, the algorithm can try a large number of possible interpretations of the question out at once, and pick the most likely interpretation.