Industrial and academic AI labs differ sharply in compute access. We document how this divide coincides with reduced representation of academic-only teams in compute‑intensive topics (e.g., foundation models) and argue academia may play a smaller role in advancing techniques, scrutiny, and diffusion. We recommend expanding academic access (e.g., national compute, open science), plus structured access and auditing to enable measured external evaluation of industry systems.