In 1997, IBM's Deep Blue computer beat reigning World Chess Champion Garry Kasparov in a classic machine-vs.-human competition. In a similar step, IBM now is having its "Watson" system compete with human contestants on the game show "Jeopardy." IBM researchers have worked for two years to create a system that can understand and respond to open-ended, natural-language questions. The goal is to create systems with enough intelligence to understand such questions, figure out exactly what the person is asking for and then find the answers quickly.
In something that sounds like it was cooked up by the writers at
"Saturday Night Live," IBM is building a computer that will compete
with human contestants on the game show "Jeopardy."
IBM researchers have spent two years creating a QA (question
answering) system-code-named "Watson"-that they say will be a
significant step forward in giving businesses the ability to quickly
find the information they need.
The Jeopardy arena will
be a key test for the system, given that it will have to be able to
handle questions that have subtle meanings, riddles, puns and the like,
then sort through the information in its database, to come up with the
answer within a second or two in order to beat its human counterparts,
the researchers said.
"The essence of making decisions is recognizing patterns in vast
amounts of data, sorting through choices and options, and responding
quickly and accurately," IBM President and CEO Sam Palmisano said in a
statement. "With advanced computing power and deep analytics, we can
infuse business and societal systems with intelligence."
IBM already has some experience in this computer-vs.-human field. In
1997, an IBM computer called Deep Blue beat chess champion Garry
Kasparov. IBM researchers said Deep Blue could calculate 200 million
chess moves per second based on a fixed problem.
However, that differs from what IBM is trying to do with Watson,
which is to create a system powered by dynamic and intelligent software
that can handle open-ended questions as normally presented by humans.
That means Watson-using massively parallel processing to instantly
understand complex questions-will have to figure out the subtext to the
question, what the person is actually looking for, and then find the
answer.
"The challenge is to build a system that, unlike systems before it,
can rival the human mind's ability to determine precise answers to
natural-language questions and to compute accurate confidences in the
answers," David Ferrucci, the leader of IBM's Watson team, said in a
statement. "This confidence processing ability is key. It greatly
distinguishes the IBM approach from conventional search, and is
critical to implementing useful business applications of [question
answering]."
And for Jeopardy, Watson will have to give the answer in the form of a question.
Email
Print
