Anthropic · AI Agent · OpenAI · Google · Codex · Germany · Fortune Technology
OpenAI confirms it cracked one of math’s grand challenges
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Key facts
- These are seven complex mathematical challenges that the Clay Mathematics Institute, founded by American mutual fund magnate Landon Clay, selected in the year 2000, offering a $1 million prize — It would prove what CEOs like Microsoft’s Satya Nadella and Palantir’s Alex Karp have been alleging lately—that OpenAI and Anthropic and other frontier AI companies train on their customer’s prompts
- As the rumors about Navier-Stokes swirled over the weekend, Terrence Tao, generally considered one of the world’s greatest living mathematicians, lamented on social media about AI companies using
- Sebastien Bubeck, the OpenAI researcher in charge of the project, denied that OpenAI’s model had any access to Buckmaster’s and Alpöge’s data
Summary
OpenAI claims it made a mathematical breakthrough. Mistral valued at $24.4 billion in new fund raise. Apologies in advance for a long essay today. But there are several important points to be made and the background is, well, complicated. Over the weekend, rumors swirled that Anthropic was on the cusp of announcing that one of its AI models had cracked one of the Millennium Prize Problems. These are seven complex mathematical challenges that the Clay Mathematics Institute, founded by American mutual fund magnate Landon Clay, selected in the year 2000, offering a $1 million prize for the first correct solution to each problem.
Buckmaster says that he and Alpöge took a concept for tackling the Navier-Stokes problem that had been pioneered by two other mathematicians, Diego Cordoba and Luis Martinez-Zoroa, and then used Anthropic’s Claude and OpenAI’s Codex powered by the GPT-5.6 Sol model, to push Cordoba and Martinez-Zoroa’s lines of attack through to completion. (Buckmaster said they also used OpenAI’s new Astra model to help them audit and write up their results but not for the actual mathematical reasoning and calculations.) Buckmaster says that he and Alpöge worked for most of a year, making only slow progress, but that with help from several AI models, they made rapid progress from mid-August onwards.