Quote · All-In with Chamath, Jason, Sacks & Friedberg
More Trillion Dollar IPOs, Anthropic $3T, Zuck's Price War, China Ends Open Source?, Trump Accounts
Where this was said
CCP considering export controls on Chinese models, is open source ending in China?
At 1:00:11 · chapter starts 54:29
Jason pivots to the week's geopolitical AI story: Reuters, citing anonymous sources, reported that Chinese regulators held meetings with Alibaba, ByteDance, and ZhipuAI to discuss limiting overseas access to China's top AI models — both open and closed. The CCP is simultaneously making AI research leaks a national security offense and tightening control over who can fund Chinese AI labs. Manus, a Chinese agentic AI startup, had employees pulled back from Singapore by the CCP. Sacks walks through why this makes sense: Chinese labs like Alibaba's Qwen and ZhipuAI's GLM went open specifically because they were behind the frontier and needed developer adoption and reinforcement learning from usage. Now that they're catching up, the economic logic shifts toward closing. He draws the explicit parallel to Sam Altman, who took OpenAI from open to closed in exactly the same move. Brad adds a provocative claim: GLM 5.2 contains watermarks from Anthropic's models, suggesting distillation — effectively downloading frontier intelligence built with American capital. He expects the US government to take steps against distillation. Brad also reports from his DC meetings that from the president down, the single unifying principle in Washington is doing everything necessary to stay ahead of China in AI.
The pattern is universal: when you're behind the frontier, go open-source to build a developer community and get utilization-based reinforcement learning. Once you close the gap, shut it down and capture the value. Sam Altman did it, Meta tried it, and now Chinese labs are doing it.
Chamath's team calculated that based on expected load growth through 2050 — just from regular devices, cars, and buildings, not even aggressive AI inference — the US is short three entire Californias' worth of energy. The AI revolution's biggest bottleneck may not be chips or software. It's electrons.
Chamath's team calculated the US faces a load growth shortfall equivalent to three entire Californias' worth of energy between now and 2050, even without heavy AI inference.
Taiwan holds only 2–3 weeks of LNG reserves; a Chinese blockade would immediately cut off the island's energy supply, threatening chip production globally.
