Machine versus man stunt by IBM

By Maggie Shiels
Technology reporter, BBC News, Silicon Valley

One of the challenges of the game is the randomness of topics

The computer company that has in the past taken on the grandmasters of chess is now turning its attention to the famed US trivia quiz show Jeopardy.

In a head-to-head challenge of man versus machine, IBM will pit a supercomputer named Watson against human contestants.

Watson is a new question-answering system based on natural language.

"The aim is to get Watson to think and interact in human terms," IBM's Dr David Ferrucci told BBC News.

"It will try to understand a user's question and intent and understand it at a rudimentary level and provide and accurate and confident answer."

For the past two years scientists have been working on perfecting the system that will drive Watson, named after IBM founder Thomas J Watson Snr.

"The most challenging aspect of this is that Watson has to know what it knows with utmost confidence.

"Otherwise if it buzzes in and gets the answer wrong that is bad on Jeopardy because you lose money and lose the game," explained Dr Ferrucci, an IBM artificial intelligence researcher and team leader on the project.

New approach

IBM is no stranger to such high-profile stunts.

In 1997 a computer called Deep Blue defeated world chess champion Garry Kasparov in another battle of human versus machine.

To compete at chess, the company built an extremely fast computer that could calculate 200 million chess moves per second based on a fixed problem.

This time around, Watson is looking to solve an open-ended problem that requires an entirely new approach.

To win on the show, contestants need a good knowledge across a range of topics and the ability to quickly analyse subtle meaning, irony, riddles and other complexities that humans excel at but computers do not.

The rules of the game will be slightly modified for this battle.

Watson will be given the questions as electronic text while the human contestants will both see the text and hear it spoken by the show's host Alex Trebek.

The computer will answer in a synthesised voice and choose follow-up questions. For the taping of the show, Watson will not be hooked up to the internet but will only be able to draw from what it has "read", or processed and indexed, before the show.

"It requires critical thinking. It requires a whole lot more than knowledge alone," said Jeopardy's executive producer Harry Friedman.

"When people hear about this project, they say isn't this Google on steroids? No, it's not."

IBM and the show's producers are hoping grand champion Ken Jennings will take part. He won Jeopardy 74 consecutive times and collected $2.52m (£1.71m) in 2004.

"Ken is the best and no-one gets close to his achievement. This is just a great test for Watson," said Dr Ferrucci.

Confident decisions

Behind this effort to put Watson on a big stage and have some fun, there is a serious business goal.

"This is about giving enterprise faster access to more precise answers," explained Dr Ferrucci.

"While business might be satisfied with the classic search approach because it gives you plenty to read, the thing that haunts you when you are making a decision is what is out there that I am not reading.

"Watson will look at all the information, including the most remote that might impinge on any answer you might make building more and more confidence into that content to help support your decision."

IBM's director of research John Kelly said: "This represents a new level of communications between computers and human beings.

"What we are doing is creating a system that will be able to be applied to all sorts of applications in the world and essentially cut the time to find answers to very difficult problems."

Dr Ferrucci said that in the past the "human has had to adapt to the computer working with classic search" and that Watson changes everything by "getting the computer to work in human terms".

"Rather than mapping words to words which is easy for a computer to do, it now has to map meaning to meaning and that is a much bigger challenge."