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CTS co-founder @KonstantinPilz on the first problem with pacing the frontier: nobody can measure the pace, and nobody knows how many chips China has. "How do we know if we have pace? Are we slower now than we have been before? It's actually quite hard to define how we're going to measure AI progress. The best way I know of is the Epoch Capabilities Index. It's not perfect, but at least we know one proxy." "On China, we've really dropped the ball thus far. We don't have good models of China,…
KonstantinPilz@KonstantinPilzSep 10
Brief observations on the US-China AI gap, given renewed calls for pacing AI progress: 1. The most advanced Chinese AI model has been 6.3 months behind the most advanced US AI model on average since 2025.[a] US AI developers have even more powerful models internally, so I estimate the real gap is closer to 8 months.[b] 2. Chinese AI capabilities depend heavily on US AI progress. We have strong evidence of industrial-scale distillation efforts that allow Chinese developers to extract capabilities from more advanced US models they couldn't otherwise access.[c] Chinese companies also benefit from algorithmic advances made by US developers via publications, word of mouth, researcher moves, etc. Additionally, they likely use Claude Code and Codex to speed up their AI R&D. 3. US companies have an enormous lead in compute. Our estimates show that by the end of 2026 leading US AI developers will have 20x more compute than Chinese AI companies. Due to the compute disadvantage, Chinese AI developers can't train competitive models on their own and instead extensively rely on distillation. The US compute lead could be much larger still if USG was serious about strengthening and enforcing export controls. For concrete proposals, see [d]. I agree we can't allow China to lead in AI. But given how far behind China is on compute and how dependent Chinese progress is on US capabilities, pacing AI progress in America would not immediately concede the lead. I estimate the US could comfortably halt progress for at least six months without falling behind China — though I think pacing, not halting, is the wiser approach. Of course, it would be preferable to pace in coordination with China, both so a framework could endure over time and to avoid unfairly disadvantaging US AI companies. In the coming months, we at @techstatecraft will publish several papers with detailed analysis of US and Chinese compute, capabilities, and the factors that determine AI progress in both countries. --- [a] https://t.co/54ZroaFOXt [b] E.g., see the graph here showing the capability difference between OpenAI's most advanced publicly released model and an unreleased internal model: https://t.co/AAwWtr9kaj [c] https://t.co/7FjIVgWxsy; https://t.co/SNQOlbCASr; https://t.co/dM3CsjgjQr [d] https://t.co/aXSIVvGVh1
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