OpenAI Researcher: Large-Scale AI Science Is Costly and Less Efficient Than Serial CoT Scaling
polynoamial · x · 2026-09-09
Responding to Nathan Lambert, an OpenAI researcher shared that results with GPT-5.6 and Astra blogs cover only a small number of agents, that larger-scale science remains very expensive, and that parallel agents are less efficient than scaling serial CoT—though the gap depends on the technique. Useful first-hand context on the economics behind the Navier-Stokes effort.
Related event: OpenAI Researchers See New Scaling Law in Parallel Agents(2 posts)→
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