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Final Jeopardy (Alexandra Cooper Mysteries) - Linda Fairstein [29]

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the team the guidance, or the time, to overhaul the system. So besides training the machine on five hundred Jeopardy clues and teaching it to answer them in the form of questions, the Piquant team left the system largely unchanged. “You could have guessed from the outset that the success rate was not going to be very high,” said Jennifer Chu-Carroll, a member of the team. Piquant was being led to a public execution.

The bake-off took place on a March morning at the Hawthorne lab. The results, from Ferrucci’s perspective, were ideal. The Piquant system succeeded on only 30 percent of the clues, far below the level needed for Jeopardy. It had high confidence on only 5 percent of them, and of those it got only 47 percent right. Fan’s Basement Baseline fared almost as well by a number of measures but was still woefully short of what was needed. Fan proved that a hacker’s concoction was far from Jeopardy standards—which was a relief. But by nearly matching the company’s state-of-the-art in Q-A technology, he highlighted its inadequacies.

The Jeopardy challenge, it was clear, would require another program, another technology platform, and a far bolder approach. Ferrucci wouldn’t hesitate to lift algorithms and ideas from both Piquant and Basement Baseline, but the project demanded far more than a recasting of IBM technologies. It was too big for a single company, even one as burly as IBM. The Blue J machine, Ferrucci said, would need “the most sophisticated intelligence architecture the world has ever seen.” For this, the Jeopardy team would have to reach out to the universities doing the most exciting work in AI, including MIT, Carnegie Mellon, and the University of Texas. “We needed all the brains we could get behind this project,” he said.

Back in the late ’70s, when he was commuting from the Bronx to his high school in suburban New Rochelle, Ferrucci and his best friend at the time, Tony Marciano, had an idea for a new type of machine. They called it “a reverse-dictionary.” The idea, Ferrucci said, was to build a machine that could find elusive words. “You know how it is when you want to express something, but you can’t think of the right word for it? A dictionary doesn’t help at all, because you don’t know what to look up. We wanted to build the machine that would give you the word.” This was before they’d ever seen a computer. “We were thinking of a mechanical thing.”

It sounded like a thesaurus. But Ferrucci bridled a bit at the suggestion that his dream machine had existed for centuries as a book. “No, you don’t give it the synonyms, just the definition,” he said. “Basically we were scratching this idea that the computer could understand your meaning, your words, your definitions, and could come up with the word.”

Ferrucci was a hot shot at science at Iona Grammar School, a Catholic boys school. He and Marciano—who, according to Ferrucci, “did calculus on his cuff links”—regarded even their own brains as machines. Marciano, for example, had the idea that devoting brain space to memory storage was wasteful. It distracted neurons from the more important work of processing ideas. So when people asked him questions requiring recall, he would respond, “Ask Dave. He’s willing to use memory.”

Ferrucci’s father, Antonio, had come to the United States from Italy after the Second World War. He had studied some law and engineering in the dying days of Mussolini’s regime, but he arrived in New York without a profession and ended up driving trucks and working in construction. He and Ferrucci’s mother, Connie, wanted their son to be a doctor. One summer during high school, Ferrucci had planned just to hang around with his friends and “play.” His father wouldn’t stand for it. “He’d gotten something in the mail about a math and computer course at Iona College. He says, ‘You’ve got the grades, why don’t you sign up for that?’”

At Iona, Ferrucci came face-to-face with his first computer. It featured a hulking cathode ray tube with a black screen and processed data encoded on teletype. He fell for it immediately. “Here was a machine,

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