The lead
GPT-5.6 reportedly closes a decades-old gap on a convex-optimization problem
It extends Sebastien Bubeck's 2025 demonstration that GPT-5-Pro could beat a published convex bound. Commenters stress these are narrow single-problem wins, verified but not a general leap.
Mathematicians report that GPT-5.6, when prompted, improved on a published bound in a convex-optimization problem that had stood for roughly three decades, days after a separate claim that the model disproved a long-open statistics conjecture. In each case the result was checked by the researcher who posed the problem.
CONVOAmmunition for the next senior AI-in-business conversation: when someone says these models only remix what exists, a frontier model produced a checkable improvement on a decades-old math result, confirmed by the paper's own authors. Add the caveat so you sound calibrated, not credulous.