Final Jeopardy (Alexandra Cooper Mysteries) - Linda Fairstein [28]
But what was simple for us involved hard work for a Q-A computer. It had to comb through the structure of the question, picking out the subjects, objects, and prepositions. Then it had to consult exhaustive reference lists that had been built up in the industry over decades, laying out hundreds of thousands of places, things, and actions and the web of relationships among them. These were known as “ontologies.” Think of them as cheat sheets for computers. If a finger was a subject, for example, it fell into human anatomy and was related to the hand and the thumb and to verbs such as “to point” and “to pluck.” (Conversely, when “the finger” turned up as the object of the verb “to give,” a sophisticated ontology might steer the computer toward the neighborhood of insults, gestures, and obscenities.)
In any case, Fan needed both a type system and a knowledge base to understand questions and hunt for answers. He didn’t have either, so he took a hacker’s shortcut and used Google and Wikipedia. (While the true Jeopardy computer would have to store its knowledge in its “head,” prototypes like Fan’s were free to search the Web.) From time to time, Fan found, if he typed a clue into Google, it led him to a Wikipedia page—and the subject of the page turned out to be the answer. The following clue, for example, would confound even the most linguistically adept computer. In the category The Author Twitters, it reads: “Czech out my short story ‘A Hunger Artist’! Tweet done. Max Brod, pls burn my laptop.” A good human Jeopardy player would see past the crazy syntax, quickly recognizing the short story as one written by Franz Kafka, along with a reference to Kafka’s Czech nationality and his longtime associate Max Brod.
In the same way, a search engine would zero in on those helpful key words and pay scant attention to the sentence surrounding them. When Fan typed the clue into Google, the first Wikipedia page that popped up was “Franz Kafka,” the correct answer. This was a primitive method. And Fan knew that a computer relying on it would botch the great majority of Jeopardy clues. It would be crashing and burning in the game against even ignorant humans, let alone Ken Jennings. But one or two times out of ten, it worked. For Fan, it was a start.
The month passed. Fan added more features to Basement Baseline. But at the end, the system was still missing vital components. Most important, it had no mechanism for gauging its level of confidence in its answers. “I didn’t have time to build one,” Fan said. This meant the computer didn’t know what it knew. In a game, it wouldn’t have any idea when to buzz. Fan could conceivably have programmed it with simple rules. It could be instructed to buzz all the time—a serious money loser, considering it flubbed two clues for every one it got right. Or he could have programmed it to buzz in every category in which it got the first clue right. That would signal that it was oriented to the category. But his machine didn’t have any way to learn that its response was right or wrong. It lacked a feedback loop. In the end, Fan blew off game strategy entirely and focused simply on building a machine that could answer Jeopardy clues.
It soon became clear that the bake-off, beyond a test of technologies, also amounted to a theater production staged by David Ferrucci. It was tied to inside politics. Ferrucci didn’t believe that the Piquant platform could ever be adapted to Jeopardy. It wasn’t big or robust enough. Yet there were expectations within the company that Piquant, which represented more than twenty researcher years, would play an important role. To build the far bigger machine he envisioned, Ferrucci needed to free himself, and the project, from the old guard’s legacy. For this, Piquant had to fail. He didn’t spell this out. But he certainly didn’t give