The US is missing a critical piece of infrastructure common in other leading tech ecosystems: an institution like Belgium's IMEC. These public-private entities focus on the pre-competitive phase between academic research and commercial development, de-risking technology and shortening cycle times—a crucial gap in the US quantum strategy.

Counterintuitively, the "move fast and break things" mantra fails in hardware. Mock Industries achieved a 71-day aircraft development cycle not by rushing tests, but by investing heavily in software and hardware-in-the-loop simulation to run thousands of virtual cases before the first physical flight.

Unlike AI, where software learnings diffuse rapidly, quantum progress is a 'hardware sport.' Tacit knowledge is deeply embedded in physical systems, making iteration times longer and knowledge transfer more difficult. This creates more defensible moats for companies and nations that achieve breakthroughs.

True co-design between AI models and chips is currently impossible due to an "asymmetric design cycle." AI models evolve much faster than chips can be designed. By using AI to drastically speed up chip design, it becomes possible to create a virtuous cycle of co-evolution.

To accelerate progress and maintain a competitive lead over China, John Martinis's new company is partnering with Applied Materials. They are leveraging modern, 300mm semiconductor fabrication tools—which are restricted from China—to build next-generation quantum devices with higher quality and scalability.

Unlike semiconductors, where the U.S. has a substantial lead, quantum is a new field where the competitive moat is small. This creates a thin margin for error in industrial policy and R&D strategy, demanding a higher degree of precision from the outset.

America's competitive AI advantage over China is not uniform. While the lead in AI models is narrow (approx. 6 months), it widens significantly at lower levels of the tech stack—to about two years for chips and as much as five years for the critical semiconductor manufacturing equipment.

The current 2-3 year chip design cycle is a major bottleneck for AI progress, as hardware is always chasing outdated software needs. By using AI to slash this timeline, companies can enable a massive expansion of custom chips, optimizing performance for many at-scale software workloads.

The US-China AI race is a 'game of inches.' While America leads in conceptual breakthroughs, China excels at rapid implementation and scaling. This dynamic reduces any American advantage to a matter of months, requiring constant, fast-paced innovation to maintain leadership.