AI news Sep 11, 2026

Today · published September 10

A company that builds inference chips, and gets filed under "Nvidia challenger," just plugged its next-generation silicon into Nvidia's rack standard.

d-Matrix builds chips specialized for AI inference — the stage after training, when a model actually answers questions. It announced that its next-generation Raptor custom accelerators will use Nvidia's NVLink Fusion, connecting its own silicon directly into Nvidia's rack and networking architecture (Nvidia blog, 2026-09-10). NVLink Fusion is the high-bandwidth interface Nvidia opens to other people's chips, letting non-Nvidia processors slot into the standard racks Nvidia has already deployed at scale, with the supply chain and liquid cooling that come with them. Cofounder and chief executive Sid Sheth gave his reason word for word: "Demand for inference is soaring, but capital, time and energy remain finite." Why this one is worth reading: designing your own custom accelerator has been sold as the road away from depending on Nvidia, and this item shows the last mile of that road curving back into Nvidia's racks and networking standard. The design work is what you save; the deployment is what you do not. ⚠️ This is Nvidia's own blog announcement. There is no third-party reading, no shipping schedule, no pricing, and no named-customer adoption — so we take the direction and infer nothing about magnitude.