Frontier AI today is increasingly constrained by chokepoints. The binding constraints have shifted away from knowledge and technique toward physical and institutional capacity. At the center of this shift sit frontier AI data centers, where the largest models are trained and where the most demanding inference workloads are anchored. These facilities are where electricity is converted into computation at scale, and their feasibility depends on assembling inputs that are slow to expand, expensive to replicate, and unevenly distributed across the world.
