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By Root 344 0

it had been right. But that was its only feedback. Watson was senseless to all of the signals its human competitors displayed—the smiles, the gasps, the confident tapping of fingers, the halting speech and darting eyes spelling panic. More important, it lost out on game intelligence. If a human answered a clue incorrectly, Watson was liable to buzz on what was known as the rebound and deliver the very same incorrect answer. What was worse, Watson had a far harder time orienting itself to the categories. How would it understand the Hair-y Situation category without hearing the other contestants’ correct answers? During these weeks, Ferrucci’s team was talking with the Jeopardy executives about giving Watson an electronic feed with the text of the correct answer after each clue. But for the time being, the machine was learning nothing. So why not start each category with the priciest clues? The high bets might spook the humans. What’s more, IBM’s statistical analysis indicated that Watson was likely to land more Daily Doubles in those pricier realms.

Watson started off with Capital Cities, an apparently straightforward category that seemed to promise the machine’s favorite type of answer: factoids. It jumped straight to the $1,000 clue: “The Rideau Canal separates this North American capital into upper and lower regions.” Todd Crain read the clue, and Lewis, in the control room, hit the button to turn on the light around the clue, opening it up for buzzes. Within milliseconds Watson had the clue all to itself.

“Watson?” Crain said.

“What is Ottawa?” Watson answered. With that, it raced through the entire category, with each correct answer reinforcing its confidence that it would know the others. Crain read each clue, the humans squeezed the button, and Watson beat them to it. It had no trouble with the South American city founded in 1535 by Pizarro (“What is Lima?”) or the capital that fell to British troops in 1917 and to U.S. troops on April 9, 2003 (“What is Baghdad?”). These were factoids, each one wrapped in the most helpful data for Watson: hard facts unencumbered by humor, slang, or the cultural references that could tie a cognitive engine into knots. No, this category delivered a steady stream of dates, distances, specific names and numbers. For a Jeopardy computer, it was comfort food.

“Very good, Watson!” Crain said.

But after that promising start, Watson started to falter. Certain categories were simply hard for it to figure out. One was called I’ll Take the Country from Here, Thanks. When Watson processed the $400 clue, “Nicolas Sarkozy from Jacques Chirac,” it didn’t know how to answer. In a few milliseconds it could establish that both names corresponded to presidents of France. But it did not understand the category well enough to build up confidence in an answer (“What is France?”). And it was not getting any orientation from the action of the game. Humans owned that category. Watson sat it out.

Then, in the category Collegiate Rhyme Time, Watson showed its stuff, but not enough to win. One asked for the smell of the document you receive upon graduating. Watson understood the clue perfectly and searched for synonyms for “document,” then attempted to match them with words related to “smell.” The best it could come up with was “What is bill feel?” (“What is diploma aroma?”).

The real problems started when Watson found itself facing Greg Lindsay, a journalist and a two-time Jeopardy champion. Lindsay, thirty-two, had spent much of his time at the University of Illinois on the Quiz Bowl circuit, where he occasionally ran into Ken Jennings. In order to spar with Watson, Lindsay had to sign David Shepler’s nondisclosure agreement. IBM wanted to keep Harry Friedman and his minions in the dark, as much as possible, about Watson’s strengths and vulnerabilities. And Friedman didn’t want the clues escaping onto the Internet before they aired on television. This meant that even if Lindsay defeated Watson, he wouldn’t be able to brag about it to the Quiz Bowl community. For his crowd, this would be the equivalent