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.

An often overlooked indicator of national competitiveness in quantum is 'cycle time'—the duration from idea to testable prototype. While the US excels at research, long fabrication lead times (e.g., 18 months for a photonic circuit) create a major disadvantage compared to regions where it takes weeks, hindering the rate of innovation.

While the race for quantum computing hardware is underway, a major blind spot is the software. Quantum software doesn't exist yet, and current software giants are not prepared. The U.S. needs a strategic public-private effort to build this ecosystem from scratch to capitalize on future hardware breakthroughs.

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.

New chip fab ventures face immense hurdles because fabrication is less like following a manual and more like mastering a recipe through decades of trial and error. This accumulated, non-transferable knowledge, likened to "cooking," creates a significant moat for incumbents like TSMC.

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.

The defensibility of complex hard tech companies doesn't rely on a single patent or technology. Instead, their moat is "novel in the aggregate"—the difficult-to-replicate integration of dozens of complex systems across design, manufacturing, supply chain, and regulation. This holistic execution is the true barrier to entry.

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 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.