Tao has written in public about AI and mathematics this year; the September 6 brief carries his post on solving problems "by purely AI-powered methods". A question worth bringing: which of the six ideas does he think a model handles least well, and why. A second, from the guest essays: the book is about what mathematics is for a reader who will not prove anything, which is the question forty-six mathematicians just answered on his blog for the people who do.

The talk is about a book of six ideas. The six months before it were about something else. Until September the blog was the usual mix: papers, "digestions" of results other people had found (unit distances, the Jacobian conjecture counterexample, the HRT counterexample, Sendov's conjecture), and small visualizers he built with coding agents. The August Kakeya post is the popular article the ICM asked him to write for Hong Wang, one of the four 2026 Fields medallists.

From 10 September most posts are guest essays, forty-six in under six weeks, most of them on what AI means for mathematics: from Fields medallists (Gowers, Hairer), a department chair, the Hodge conjecture's specialists, an open-letter coalition and an advisory group. His own posts in the same weeks are reading lists, statements, competitions and formal-proof infrastructure (SAIR's Open Math Model and Open Math OS, How to Formalize All of Mathematics). The research did not stop: the Euler blowup paper, and notes for his graduate course 247A.

The news around it ran the same way. Labs announced results in batches and withdrew some, the Clay Institute issued a Navier–Stokes announcement, and the field argued in public about credit, standards and what a theorem is for.

Notes pending.