Analyst Chris Miller argues China's core challenge is manufacturing, as it lacks the advanced lithography tools monopolized by ASML. The US and Taiwan are projected to produce 30 times more quality-adjusted AI chips, a gap unlikely to close soon.

Reports of China building a working EUV lithography machine are misleading. The effort appears to be an assembly of smuggled components from ASML's existing supply chain, not a story of domestic innovation. This frames the primary challenge as one of export control evasion rather than a rapid technological leap by China.

China cannot overcome its semiconductor disadvantage by simply applying more energy to its lagging-edge chips. No frontier AI model has been trained on hardware older than 5nm, suggesting leading-edge nodes provide an essential, non-linear advantage in training efficiency that cannot be compensated for with sheer power, a major hurdle for China's AGI ambitions.

The primary constraint on AI scaling isn't just semiconductor fabrication capacity. It's a series of dependent bottlenecks, from TSMC's fabs to the limited number of EUV machines from ASML, and even further down to ASML's own specialized suppliers for components like lenses and glass.

China's semiconductor strategy is not merely to reverse-engineer Western technology like ASML's. It's a well-funded "primacy race" to develop novel, AI-driven lithography systems. This approach aims to create superior, not just parallel, manufacturing capabilities to gain global economic leverage.

The effectiveness of US export controls on advanced AI chips stems from a deep technological gap. According to China's own projections, it won't be able to domestically produce chips as powerful as those the US is restricting until 2028, creating a significant and lasting strategic advantage for democracies.

The manufacturing requirements for AI compute are staggering. Producing the advanced logic and memory wafers for just one gigawatt of data center capacity requires the output of approximately three and a half EUV lithography machines from ASML, representing over $1.2 billion in capital equipment.

The long-term ability to scale AI compute is not constrained by power or data centers, but by the production of advanced semiconductors. The ultimate chokepoint is ASML, the world's only manufacturer of EUV lithography tools, which can only produce just over 100 units annually by 2030.

While energy is a concern, the highly consolidated semiconductor supply chain, with TSMC controlling 90% of advanced nodes and relying on a single EUV machine supplier (ASML), creates a more immediate and inelastic bottleneck for AI hardware expansion than energy production.