DRAM shortage throttles AI hyperscalers, capping large‑language‑model speed. Samuel K. Moore explains that high‑bandwidth memory (HBM) is the bottleneck, with supply lagging behind demand. The crunch forces firms to redesign pipelines or wait for new chips. Practitioners must plan for slower inference or invest in alternative memory solutions in the near term.