Final Jeopardy (Alexandra Cooper Mysteries) - Linda Fairstein [95]
Craig had a different story. In the thirty seconds he had to mull Final Jeopardy, thoughts about a prayer service featuring a swami in Chicago never entered his mind. But his analysis, usually so disciplined, was derailed by an all-too-human foible. He fell to suggestion, one nourished by his environment. Just a short drive north of his home in Delaware, the ice hockey team in Philadelphia, the Flyers, had recently battled to the finals of the Stanley Cup. This awakened hockey fever in the metropolitan area and an onslaught of media coverage, along with endless chatter and speculation. Hockey hadn’t been on people’s minds to this degree since the glory years of the franchise, when the “Broad Street Bullies” won back-to-back cups in the mid-1970s. The Flyers ultimately lost to the Chicago Black Hawks, a team that hadn’t won in forty-nine years (six years longer than the Saints). So even though Craig was a “huge football fan” who hadn’t missed watching a Super Bowl since his childhood, he had hockey in his head when he saw the Final Jeopardy clue. Much like the psychology test subjects who mistook Moses for the animal keeper on the ark, Craig focused on a forty-something-year championship drought—and looked right past the crucial February date. The hockey final, after all, had been in June. “I blew it,” he said. So did Watson. But despite their virtuoso talents and similar techniques, in this one example of failure they each remained true to their kind. One was dumb as only a machine can be, the other human to a fault.
During the sparring sessions in the spring, Watson had relied on simple heuristics to guide its strategy. Ferrucci at one point called it brain dead, and David Gondek, who had written the rules, had to agree. You might say that such heuristics are “brain-dead by definition,” he said, since they replace analysis with rules. But what a waste it was to equip Watson, a machine that could carry out billions of calculations per second, with such a rudimentary set of instructions.
There was no reason, of course, for Watson’s strategy to be guided by a handful of simple rules. The machine had plenty of processing power, enough to run a trillion-dollar trading portfolio or to manage all of the air traffic in North America or even the world. Figuring out bets for a single game of Jeopardy was well within its range. But before the machine could become a strategic whiz, Gondek and his team had to turn thousands of Jeopardy games into a crazy quilt of statistical probabilities. Then they had to teach Watson—or help it teach itself—how best to play the game. This took time.
The goal was to have Watson analyze a dizzying assortment of variables, from its track record on anagrams or geography puzzlers to its opponents’ ever-changing scores. Then it would come up with the ideal betting strategy for each point of the game and for each clue. This promised to be much simpler for Watson than the rest of its work. English, after all, was foreign to the machine, and Jeopardy clues, even after years of work, remained challenging. Game strategy, with its statistical crunching of probabilities, played to Watson’s strengths.
To tutor Watson in the art of strategy, Gondek brought in one of IBM’s gaming masters, an intense computer scientist named Gerald Tesauro. Short, dark, and neatly dressed, his polo shirt tucked cleanly into dark slacks, Tesauro was one of the more competitive members of the Jeopardy team. He took pride, for example, in his ability to beat Watson to the