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Mathematicians just answered the machine — and it's the best model yet for what AI does to a profession
At the International Congress of Mathematicians, Terence Tao argued the discipline faces proof overload rather than obsolescence: when results become abundant, the scarce work moves to curation and verification. Over 3,000 have signed the Leiden Declaration demanding mandatory AI disclosure in papers. The response is neither rejection nor capitulation.
Read story →A record eight Pulitzer entries disclosed AI — and most of it wasn't generative AI at all
Five 2026 Pulitzer winners and three finalists disclosed using AI, the most since the disclosure requirement began in 2024. Two details invert the obvious reading: the tools were mostly pre-LLM machine learning, and the disclosures went to the judges rather than to readers.
Read story →AI just did original mathematics twice in one week — and the difference between the two cases is the whole lesson
OpenAI's unreleased Astra model produced results for ten problems open for a decade or more, and shipped machine-checkable Lean 4 certificates for every one. Days earlier, two research teams used GPT-5.6 Sol on the same quantum cryptography problem and filed papers three hours apart. One of these you can verify without trusting anybody. The other you cannot.
Read story →Google's ATLAS report: AI reaches 68% of jobs but fully automates under 10% of tasks — the data says collaborator, not replacer
Google published its first AI & Economy ATLAS report on July 23 — an analysis of 15 million de-identified Gemini interactions across 150 countries, 800 occupations, and 4,000 tasks. The headline: AI now touches 68% of occupations (about 90% of US employment), but fully automates under 10% of tasks. People use it mostly to collaborate — research, draft, iterate, troubleshoot, learn — not to hand off whole jobs. And higher earners use it more. Here's what the data actually shows, what it doesn't, and what it means for your work.
Read story →OpenAI's internal reasoning model disproves an 80-year-old Erdős conjecture
OpenAI announced May 20, 2026 that an internal general-purpose reasoning model autonomously disproved Paul Erdős's 1946 planar unit-distance conjecture — finding constructions that beat the long-assumed-optimal square grid. Companion paper co-authored by four named mathematicians including Fields medalist Tim Gowers, who called it 'a milestone in AI mathematics.' Not yet peer-reviewed by a journal, but verified by independent mathematicians including the researcher who exposed an earlier OpenAI false claim.
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