We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.

OpenAI has found new internal optimizations capable of cutting the cost of serving existing models by more than half. In other words, 50% cheaper inference or more, without swapping the model for a weaker one. On top of that, the engineers are developing the new chip, which also represents some incredible leaps in engineering. All of this will start being implemented over the next few months. So we have a new family of models: Astra. We have a massive pretraining run with supposedly more than 10T parameters: Bel. And we have interesting, cheap technology behind all of it, making it possible for users to do twice as much, three times as much, or even more, for the same cost. Meanwhile, I’m not seeing advancements nearly as significant from Anthropic, and even their “Model 2,” which is basically their ace in the hole, isn’t something they plan to release because it’s “too powerful and dangerous” (and also extremely expensive), so they prepared weaker checkpoints instead.

Uploading and logging into everything on OpenAI Finance is a better CPA and financial advisor than any human I’ve ever paid. Ditto contracts and lawyers, and results/scans and doctors. You only interface with humans out of the legacy capture and inertia of the offline world.