AI race may need global compute oversight, writer warns open models are fragile
scaling01 · x · 2026-07-28
The author says they are sympathetic to open models because they can make models cheaper and reduce concentration of power, but they do not believe a fully open collaborative ecosystem is realistic.
Their argument is that AI development behaves like a prisoners’ dilemma: if everyone cooperates, everyone benefits, but each actor has a strong incentive to race ahead because doing so could confer a decisive capabilities lead. They connect this to the “AI 2040” plan, arguing that a stable regime would require something like “mutually assured compute destruction” plus global oversight of datacenters and chips. The post also stresses that compute, model releases, and frontier progress can look continuous at the macro level while individual scale-ups and releases are still discontinuous, which may make future jumps more dangerous.
Related event: Frontier AI Open-Source vs. Safety: Superalignment and Regulatory Dilemmas(9 posts)→
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