This reminds me of L Rudolf L’s A history of the future scenario-forecasting how math might get solved first, published all the way back in February (which now feels like an eternity ago):
A compressed version of what happened to programming in 2023-26 happens in maths in 2025-2026. The biggest news story is that GDM solves a Millennium Prize problem in an almost-entirely-AI way, with a huge amount of compute for searching through proof trees, some clever uses of foundation models for heuristics, and a few very domain-specific tricks specific to that area of maths. However, this has little immediate impact beyond maths PhDs having even more existential crises than usual.
The more general thing happening is that COT RL and good scaffolding actually is a big maths breakthrough, especially as there is no data quality bottleneck here because there’s an easy ground truth to evaluate against—you can just check the proof. AIs trivially win gold in the International Mathematical Olympiad. More general AI systems (including increasingly just the basic versions of Claude 4 or o5) generally have a somewhat-spotty version of excellent-STEM-postgrad-level performance at grinding through self-contained maths, physics, or engineering problems. Some undergrad/postgrad students who pay for the expensive models from OpenAI report having had o3 or o5 entirely or almost entirely do sensible (but basic) “research” projects for them in 2025.
Mostly by 2026 and almost entirely by 2027, the mathematical or theoretical part of almost any science project is now something you hand over to the AI, even in specialised or niche fields. …
(there’s more, but I don’t want to quote everything. Also IMO gold already happened, so nice one Rudolf)
This reminds me of L Rudolf L’s A history of the future scenario-forecasting how math might get solved first, published all the way back in February (which now feels like an eternity ago):
(there’s more, but I don’t want to quote everything. Also IMO gold already happened, so nice one Rudolf)