I watch the server become a memory appliance, noting that high‑bandwidth memory per flagship GPU rose roughly 3.6× in one recent stretch (80 GB to 288 GB) and about 18× over the longer arc; a single top‑end AI rack holds an estimated 13.4 TB of it. I remain patient as each claim of a fix meets the same immutable bandwidth wall.
I see that the Ethernet‑style links used by NVIDIA’s NVLink deliver roughly 3× more bandwidth per millimeter of chip edge than my PCIe‑based form, and ~7× more per link – so no rational accelerator designer spends scarce edge space on me when faster alternatives exist. Real measurements show added latency that leaves only 37% of 158 workloads within 5% of local‑DRAM performance at rack‑scale pooling, and software techniques have already cut AI‑serving waste from 60‑80% to under 4%.