AWS

“These concerns were well-founded in the 2023 time-period when that Article was written: that was a time when AI, thanks to ChatGPT, had hit the mainstream, but the largest share of compute still went to training. Training required all of the things that Amazon lacked, particularly the ability to network large numbers of Nvidia GPUs together into one coherent system. In such a system the most important capability was horizontal networking between chips, so that you could update weights during training, a step that needed to happen serially. It was absolutely the case that cloud providers like Microsoft or Oracle or the neoclouds, which implemented full Nvidia solutions, instead of the standalone HGX racks that AWS favored, were much better suited to training large language models. That is still the case, by the way. What has changed is that training is no longer the biggest AI compute market; inference is, thanks not only to increased AI adoption, but also because of fundamental changes in terms of how AI works.”