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The liftoff scenario that terrifies AI doomsayers

"Recursive self-improvement" is the idea that artificial intelligence could learn to build and train itself, creating exponential new progress – and risk.

The Star Malaysia查看原文 ↗
令人工智能末日预言家们恐惧的发射场景

Jeff Clune, a computer scientist and co-founder of Recursive Superintelligence, one of the start-ups chasing “recursive self-improvement,” in Vancouver. — ALANA PATERSON/The New York Times

SAN FRANCISCO : In December, Edward Hughes and Louis Kirsch, two of the world’s leading artificial intelligence (AI) researchers, left Google. Their goal: to build an AI system smart enough to build a better AI system.

At their new London startup, Inherent, they now spend their days working alongside a prototype called Faraday. Named for 19th-century English physicist Michael Faraday, it gathers mountains of data capturing the daily activities of Hughes, Kirsch and Inherent’s other researchers: emails, instant messages, meeting transcripts and their ongoing chats with Faraday itself. The company then uses this data to build a better version of Faraday.

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