Executive Summary A recent remark by Groq founder Jonathan Ross raises an important question. If models begin to improve the quality of their own learning signals, then the AI growth logic we have become familiar with may no longer follow the same path of diminishing returns. This article does not ask whether Ross’s claim should be accepted at face value. It asks whether the idea behind it is already supported by a set of meaningful
Executive Summary At first glance, NVIDIA’s move to incorporate the Groq-based NVIDIA Groq 3 LPX into the Vera Rubin platform may look like a new approach to inference workload allocation. But the real focus of this article is not the technical detail itself. It is whether this move suggests that NVIDIA’s moat may be deeper than it previously appeared. The argument here is that NVIDIA’s competitive strength may not rest only on chip performance, the
Executive Summary NVIDIA’s licensing agreement with Groq is worth watching not only because the technology itself is extreme, but because it may signal that AI compute architecture is being reconsidered. Even after GPUs have become the dominant platform for AI training and inference, NVIDIA is still willing to engage seriously with an execution model that runs almost counter to the mainstream path. That suggests the demands of the inference era may be making determinism important