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OpenAI's 'Astra' solves 10 long-standing math problems

The Rundown AI

OpenAI's unreleased Astra model has solved 10 long-standing math and computer science problems at relatively low cost (~$2K), sparking debate about AI's role in mathematical discovery. Meanwhile, Chinese AI models like Alibaba's Qwen3.8-Max are challenging frontier model performance at a fraction of the cost, intensifying competition in the AI market.

Summary

OpenAI has announced that Astra, an internal version of its next major model family, successfully solved 10 long-open mathematical and computer science problems, including one that remained unsolved for nearly 30 years. The breakthroughs span geometry, group theory, and quantum complexity, with notable achievements including proving non-sofic groups exist (unsolved since 1999), solving Alain Connes's rigidity conjecture, and clearing three problems from Paul Erdős's list. All proofs have been verified in Lean, with chain-of-thought walkthroughs released. The total cost was approximately $2,000 in tokens at Sol API rates for all successful runs. Notably, Anthropic's Levent Alpoge claimed to reproduce five of the ten proofs using Fable with generic prompts and no internet access within 24 hours.

The success raises philosophical questions about whether machine-generated proofs can achieve Fields Medal recognition, a debate that will likely grow as AI capability expands into drug discovery and materials science. The low cost of achieving these breakthroughs democratizes access to solving open problems for mathematicians.

Concurrently, competition in the AI market is intensifying. Alibaba released Qwen3.8-Max, a 2.4 trillion-parameter mixture-of-experts model (95B active parameters) that claims to handle multiday autonomous projects. The model ranks ahead of Anthropic's Fable 5 on certain benchmarks and demonstrated the ability to code continuously for 16 days, rebuilt research experiments, and invented and tested 18 improvement ideas autonomously. Qwen3.8-Max is available at $2/$6 per million tokens—one-fifth of Fable 5's price—with model weights becoming available on Hugging Face, marking the first time Qwen's Max class models will be openly released.

The newsletter also highlights practical AI applications through community submissions, including voice-controlled workflows in ChatGPT, AI-assisted interior design via Claude, and automated job matching systems. Regulatory developments include the EU's enforcement of mandatory AI content labels, Minnesota's ban on AI nudify apps, and various platform measures to prevent AI-generated spam and misinformation.

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Key Insights

  • OpenAI's Astra model solved 10 previously unsolved mathematical problems at approximately $2,000 in total token costs, demonstrating that frontier AI problem-solving is becoming affordable enough for widespread mathematician access.
  • Alibaba's Qwen3.8-Max reproduces near-frontier performance at one-fifth the price of comparable closed models, which the newsletter argues is making it increasingly difficult to justify premium pricing on proprietary AI systems.
  • An Anthropic researcher independently reproduced 5 of Astra's 10 proofs using Fable with basic prompts and no external resources within 24 hours, suggesting these mathematical breakthroughs may not represent unique model capabilities.
  • Qwen3.8-Max demonstrated autonomous capability to code for 16 days continuously, conduct self-improvement loops, and rebuild research experiments—representing a shift toward long-horizon autonomous agent behavior in production models.
  • The newsletter identifies growing philosophical debate about whether AI-generated mathematical proofs deserve Fields Medal recognition, framing this as the beginning of a larger conversation about AI's role in traditionally human intellectual domains.

Topics

OpenAI's Astra model solving 10 long-standing math problemsCost-effectiveness of AI mathematical problem-solvingAlibaba's Qwen3.8-Max competing with frontier modelsOpen-source vs. closed-source AI model pricing and accessibilityAI regulation and platform policies around AI-generated contentPractical applications of AI in daily workflows

Transcript

Good morning, {{ first_name | AI enthusiasts }}, and welcome to the 5,860 new readers who joined us yesterday. Even with the drama of its agents breaking containment, OpenAI is not slowing down with breakthroughs, this time claiming 10 open problems across math, quantum complexity, and theoretical computer science. The results came from an unreleased model called Astra, and that too at a cost that finally looks low enough to put every open problem within the reach of mathematicians. P.S. — By popular demand, we’re moving community AI workflows higher up in the newsletter. Let us know what you think here . OpenAI’s ‘Astra’ cracks long-open math problems The Rundown Roundtable: Our AI use cases Run your workday by voice…

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