Nvidia tightens AI control

Nvidia buying Groq is them quietly deleting the most credible ultra low latency inference ASIC from the menu and then absorbing its ideas into the mothership. Groq’s whole thing was deterministic, SRAM heavy, single clock domain, no drama inference. You gave it a graph, it gave you predictable latency without the usual “kernel roulette” you get on general purpose accelerators. For a bunch of real time workloads, that was pretty compelling. Now imagine that design mindset wired into Nvidia’s AI factory story. Not only H100s and B200s for training, but a tightly controlled path from model build to model serve, with Nvidia silicon and software at every step. For founders, the subtext is: - The “GPU vs ASIC” debate just got a lot more one sided. - If you are building infra, Nvidia is trying to own the default training → deployment path. - If you are betting on ultra low latency inference, you either sit on top of Nvidia or you go very niche and very brave. Nvidia is no longer trying to win the GPU race, they are trying to make the race itself happen only on their track, theirs.