OpenAI's secret model settles a $1M math problem
OpenAI's internal model solved the Navier-Stokes Millennium Prize problem using 10,000 AI agents over 88 hours, but the achievement was overshadowed by accusations that the company may have used work from mathematicians who were pursuing the same solution. Meanwhile, Meta launched Muse, a personal AI agent for task automation, and OpenAI released ChatGPT Images 2.5 with significantly faster generation times.
Summary
OpenAI announced that an unreleased internal model "significantly more capable" than the publicly-released GPT-6 Astra solved Navier-Stokes, one of seven $1M Millennium Prize problems. The company ran approximately 10,000 AI agents simultaneously for 88 hours to generate the proof, with Sam Altman calling it "one of the most amazing moments for OpenAI history." However, the achievement has been marred by controversy: NYU mathematician Tristan Buckmaster and Anthropic's Levent Alpöge claimed they spent a year on a similar approach, posted partial results the night before OpenAI's announcement, and questioned whether OpenAI accessed their Codex drafts. OpenAI denied seeing their work and stated no specific user data was accessed, but acknowledged it cannot rule out that usage data may have informed the model. The compute cost for solving the problem was estimated at millions of dollars.
In other developments, Meta introduced Muse, an always-on personal AI agent with a text messaging interface capable of handling tasks like booking reservations, sending emails, and shopping. Muse integrates with apps including Gmail, Spotify, and OpenTable, and can code its own integrations for unsupported services. The agent operates through its own app or WhatsApp and navigates websites using a virtual machine. Meta emphasized privacy features including a secure cloud environment, Stripe-enabled payments, and approval workflows. The service will offer limited free usage followed by paid tiers of $20 or $100 monthly, initially available only in the U.S.
OpenAI also released ChatGPT Images 2.5, reducing generation time by up to 50% compared to Images 2.0 with improved editing capabilities. Two new models, Sunburst and Flare, rank first and second on Arena AI's Image leaderboards. New features include sketch-to-image generation (via @Sketch), templates, shared images, and comment-based granular editing.
The newsletter also highlighted additional AI developments: Google DeepMind's AlphaGenome Atlas mapping 9 billion DNA mutations, Cognition's $2B funding round at a $48B valuation with revenue nearly doubling to $900M, Inception Labs' Mercury 2.5 achieving Haiku 4.5-level quality at 1,100+ tokens per second, and Mistral AI raising €3B to value the company at over $24B.
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Key Insights
- OpenAI solved a $1M Millennium Prize problem using a model significantly more capable than publicly-released GPT-6 Astra, suggesting the company's frontier capabilities are substantially ahead of what consumers have access to.
- OpenAI acknowledged it cannot definitively rule out that usage data from competitors' work may have informed its model training, creating ambiguity about the independence of its breakthrough despite denying direct access to specific work.
- The competitive pressure around solving Navier-Stokes resulted in two independent groups pursuing nearly identical mathematical approaches simultaneously, with OpenAI's vastly greater computational resources enabling it to reach the solution first.
- OpenAI is demonstrating a shipping velocity that increasingly allows it to compete primarily against its own previous models, as Images 2.5 replaced Images 2.0 at the top of benchmarks despite the predecessor model's recent dominance.
- Personal AI agents from multiple companies (Meta, OpenAI, Anthropic) are proliferating in the market, yet frontier labs may soon bypass these middlemen by integrating web navigation and agent capabilities directly into their core models.
Topics
Transcript
Good morning, {{ first_name | AI enthusiasts }}, and welcome to our 3,327 new readers. GPT-6 Astra hasn’t even been out a week, and OpenAI is already using an internal model “significantly more capable” to knock out one of math’s hardest open problems. The company says the model solved Navier-Stokes, a $1M Millennium problem, with 10,000 AI agents grinding for 88 hours. But in typical OpenAI fashion, the win came with a fight attached — this time with two mathematicians who spent a year on the same path. Reminder: Our next live workshop is today at 2 PM EST — join and learn how to build and run an ad creative strategy from Rishi Lalwani, The Rundown’s Head of Growth.…
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