dan wang

China's manufacturing workforce (70M vs 12M US) combined with state-directed credit, vertical integration, and process knowledge accumulated on factory floors enables 3-4x faster product cycles (18 months vs 6 years for new vehicle models). The US has lost the ability to climb 'technological ladders' it once set; China excels at scaling lab inventions into global industries (solar, EVs, drones, batteries).

US holds a decisive lead in AI model training via Nvidia chips, but China is catching up fast on talent (DeepSeek, repatriating researchers) and holds structural advantages for AI deployment: 10x solar additions, 33 nuclear plants under construction vs zero in US, and vast manufacturing process data to train 'better Foxconn' AI for drones, munitions, ships. The next 5 years will determine who deploys AGI more effectively.

Three structural barriers suppress Chinese equity valuations: (1) Cayman VIE structures give only contractual claims, (2) capital controls prevent free portfolio flows, (3) Taiwan conflict would trigger Russia-style sanctions (asset freezes, forced divestment). Until these are resolved, even high-FCF companies like ByteDance trade at 10x discounts to US peers.

China's 'engineering state' prioritizes heavy industry energy security: 500 GW solar additions (10x US), 33 nuclear reactors under construction (vs 0 US), and 50% EV penetration reducing oil imports. This energy surplus is a prerequisite for AI data centers and advanced manufacturing the US cannot currently match.

Chinese EV makers integrate vehicles, batteries, chips, and supply chains end-to-end, supported by 70M manufacturing workers and government infrastructure. Xiaomi's first EV beat Porsche/BMW at Nürburgring; BYD and others replicate Huawei's vertical model. US lacks the manufacturing ecosystem to compete on speed or cost.

China's 'engineering state' builds fast (high-speed rail, subways, factories retooled in days for masks) but risks catastrophic overreach (zero-COVID, one-child policy). US 'lawyerly state' guarantees pluralism but cannot execute (1914 train faster than 2024). The optimal equilibrium is more state capacity than US has, less than China's.

Top-tier AI talent is increasingly Chinese-educated (7 of 11 Meta superintelligence hires). Push factors: US anti-Asian rhetoric, Trump populism, visa uncertainty. Pull factors: Chinese labs offer competitive pay, better research funding, more graduate students. A significant repatriation wave could flip the AI talent balance within 5 years.