The primary competitive arena for AI is no longer just about creating the best algorithm. It has evolved into a geopolitical contest for control over the entire technology stack, including the infrastructure, supply chains, standards, and energy systems required to deploy AI models at a national scale.

The primary constraint on US AI leadership relative to China isn't the ability to build models, but the slow pace of developing necessary compute and energy infrastructure. China faces fewer regulatory barriers, allowing it to scale these critical inputs more rapidly.

A global AI safety regime should learn from nuclear arms control by focusing on the physical infrastructure that enables strategic capabilities. Instead of just seeking promises, it should aim to control access to chokepoints like advanced chip manufacturing and the massive data centers required for frontier models.

The primary constraint on AI development is not software or algorithms but the physical infrastructure required to support it: power, data centers, and supply chains. Policy will focus on this area regardless of election outcomes, though the specific approach may differ.

Unlike social media, which scaled without physical impediments, AI's progress depends on massive, resource-intensive data centers. This physical footprint makes the industry vulnerable to local political opposition, regulations, and even violence, creating a new bottleneck for growth that pure software companies never faced.

The common analogy between regulating AI and nuclear weapons is flawed. Nuclear development requires physically trackable, interceptable materials and facilities like enrichment plants. In contrast, AI models are software and weights, which are diffuse and far more difficult to monitor and control, presenting a fundamentally different and harder regulatory challenge.

Instead of an outright ban on models like China's Kimi K3, the US government is more likely to use "soft law" tactics. This involves pressuring chokepoints like US-based data centers and hyperscalers to restrict the hosting and deployment of these foreign models.

The pursuit of 'Sovereign AI' transforms AI infrastructure into a strategic national asset. Governments are increasingly intervening to decide where AI infrastructure is built, how it's financed, and which countries get access, mirroring national policies for critical resources like energy and transportation.

The abstract race for AI superiority is now grounded in physical reality. Control over electricity grids, cooling, and land for data centers has become as strategically important as semiconductor supply chains, shaping who can scale frontier AI.