Von Ahn, who grew up in Guatemala City, believes that A.I. will eventually make computers better teachers than humans.
In the fall of 2000, as the first dotcom bubble was bursting, the Guatemalan computer scientist Luis von Ahn attended a talk, at Carnegie Mellon, about ten problems that Yahoo couldn’t solve. Von Ahn, who had just begun his Ph.D., liked solving problems. He had planned to study math until he realized that many mathematicians were still toiling away over questions that had proved unanswerable for centuries. “I talked to some computer-science professors and they would say, ‘Oh, yeah, I solved an open problem last week,’” he told me recently. “That seemed just a lot more interesting.”
At the talk, one particular problem caught his attention: millions of bots were registering for Yahoo accounts because the company couldn’t distinguish them from human beings. What the company needed was a rudimentary variation on the Turing Test, which the English mathematician Alan Turing had proposed, in 1950, as a way of determining whether machines could credibly imitate human beings. In the most familiar version of the test, a person poses questions to two figures he cannot see: one human, one machine. The machine passes the test if the evaluator can’t reliably decide which is which. Back in 2000, no computer had ever succeeded.
Bu hikaye The New Yorker dergisinin April 24 - May 01, 2023 (Double Issue) sayısından alınmıştır.
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Bu hikaye The New Yorker dergisinin April 24 - May 01, 2023 (Double Issue) sayısından alınmıştır.
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