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Mathematicians Voice Unease as OpenAI Says AI Solved Millennium Prize Problem

OpenAI reported that its latest model, using 10,000 autonomous AI agents at an estimated cost of $15m, resolved a decades-old mathematical puzzle, prompting mixed reactions from the mathematics community, according to The Guardian.

· 2 min read · language: en
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The Guardian — Business

OpenAI has announced that its latest artificial intelligence model solved a Millennium Prize Problem, a category of mathematical puzzles carrying a $1m reward that had remained unsolved for decades, according to a report by The Guardian.

The report described the achievement as unlike typical breakthroughs in mathematics, noting that OpenAI, a company valued at nearly a trillion dollars, deployed 10,000 AI agents—autonomous systems capable of carrying out tasks without direct human guidance—to work on the problem. The Guardian reported the effort was estimated to have cost around $15m.

According to the report, the announcement came amid a series of recent instances in which artificial intelligence tools have contributed to advances in mathematics, leaving some mathematicians describing themselves as shocked at the pace of change in the field.

The Guardian's report also noted that the announcement drew a mixed and, in some cases, skeptical response from mathematicians, with the article's headline citing characterizations of the achievement as "immature playground boasting." The report did not provide further detail on the specific individuals making such characterizations or the full basis for their criticism.

The source material reviewed did not specify which of the seven Millennium Prize Problems, designated by the Clay Mathematics Institute, was reportedly addressed, nor did it include independent verification of OpenAI's claim from mathematical authorities.

OpenAI has not been quoted directly in the available material regarding the methodology used or whether the claimed solution has undergone formal peer review.

Sources

EGazette summarizes reporting from multiple sources; follow the links for the originals.

Also available in: ARFR

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