GPT-5.6 solves 30-year convex optimization gap with a single prompt
A 30-year-old math problem cracked by an AI prompt.
Deep Dive
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Key Points
- GPT-5.6 solved a 30-year-old open problem in convex optimization using a single natural language prompt.
- The derived algorithm matches the theoretical lower bounds for both smooth and non-smooth optimization, which was previously believed impossible.
- The solution was verified by independent experts and has immediate applications in training large-scale ML models and financial optimization.
Why It Matters
First AI to solve a decades-old math problem, proving LLMs can generate original research.