Demand for AI infrastructure is at an all-time high. Global accelerator shortages mean engineering teams can rarely get all the compute they need from just one data center — capacity comes a cluster here, a cluster there, often an ocean apart. At the same time, workloads are getting hungrier: Today’s long-running agentic workloads often have context windows of 100k to 800k+ tokens, which consume accelerator memory faster than any previous generation of AI traffic.