Everyone in AI is talking about GPUs. Almost no one is talking about storage. At NVIDIA GTC, I sat down with Greg Matson from Solidigm, and this gap became very clear. Because behind every model, every training run, every inference pipeline… there is data. And how you store, move, and access that data changes everything. We talked about what companies are missing when they say they are “all in on AI.”

Most are focused on compute. Very few are rethinking their data and storage strategy. And that creates problems later.

Slower pipelines

Higher costs

Bottlenecks that no GPU can fix

One insight that stood out. The companies building serious AI infrastructure today are making storage decisions early. Everyone else is going to feel it later. We also touched on a bigger question. Are we heading toward a point where GPUs keep getting faster, but the data layer cannot keep up? Because if that happens, storage becomes the real limiter of AI progress. This is one of the most overlooked parts of the AI stack.

But it might be the most important. More conversations coming from GTC.

#data #ai #solidigm #NVIDIAGTC #theravitshow