Podbit · All-In with Chamath, Jason, Sacks & Friedberg
Jason Calacanis believes selling expert-curated training data to Chinese labs is unpatriotic and a key driver of their catch-up. David Sacks pushes back: China has its own PhDs, and a blanket ban risks trade war retaliation without a meaningful strategic payoff. Targeted controls — like the EUV lithography ban — are the right model.
Where this was said
At 1:08:00 · chapter starts 1:05:56
The final segment opens with a pointed Forbes exposé: US data labeling startups like Surge AI and Merkur are selling PhD-curated training datasets to China's top AI labs — Tencent, ByteDance, Alibaba, and others — at a combined spend of roughly $500 million per year [1] — Jason Calacanis "The top 6 Chinese AI labs are spending roughly $500 million per year buying PhD-curated training data from the same US startups that supply…" 1:05:30 . These are the same datasets sold to OpenAI, Anthropic, and US federal agencies. Jason argues this is a meaningful driver of China's AI catch-up and questions the patriotism of participating companies, noting the founder of his portfolio company MicroOne explicitly declined to sell to China. David Sacks urges nuance: data labeling is largely a commodity, China has no shortage of its own PhDs, and a blanket export ban risks triggering trade war retaliation without delivering a decisive strategic advantage. His standard for export controls is the EUV lithography machine ban from 2019 — a targeted, high-impact restriction — and he's not convinced this training data meets that bar. Brad Gerstner adds geopolitical context: the US is winning the AI race right now, Xi Jinping is visiting in September for a bilateral summit, and relations are broadly improving — so heavy-handed restrictions seem premature. But he flags that if the gap narrows and American advisors can no longer confidently say 'we're winning,' these data sales will face far more scrutiny. The episode closes with Jason's closing banter, plugging Chamath's white sweater charity drive before the besties sign off.
According to a Forbes investigation, the top 6 Chinese AI labs are spending roughly $500 million per year purchasing expert-curated US training datasets from companies like Surge AI and Merkur.
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