Tiny Pickles: Why are AI companies investing so much in math proofs? (blog.chaoticgood.computer)

On September 8, 2026, OpenAI revealed that its fleet of 10,000 AI agents, powered by GPT-6 Astra and an unreleased model, successfully discovered an analytical solution related to the Navier-Stokes equations. This marks a significant moment in the AI/ML community, as it raises questions about the role of human mathematicians and the evolving capabilities of AI in tackling complex mathematical issues. While engineers and fluid dynamics experts noted that the practical impact remained unchanged for day-to-day applications, the mathematical community expressed a mix of astonishment and existential questioning about their relevance in advancing knowledge. This breakthrough coincides with a growing interest in formal proofs within AI development, highlighted by Anthropic's recent exploration into the feasibility of using large language models for formal software verification. The implications are profound: AI not only assists in generating specifications but can also create proofs regarding software security, offering an alternative to traditional testing methods. This dual capability of understanding and formalizing complex systems could redefine the landscape of software development, especially in high-stakes domains like cybersecurity and aviation, where provably secure systems could significantly reduce vulnerabilities.