If AI scaling slows, repurposed central GPUs will cannibalize edge data centers
Dr. Ben Lee · Will inference move to the edge? · Dec 18, 2025 · at 32:52
Dr. Ben Lee discusses how diminishing returns in frontier model training could redirect centralized hyperscale GPU capacity toward inference instead of distributed edge facilities.
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“And if it turns out that maybe there are diminishing returns from training larger and larger models, or maybe we run out of data because we've exhausted all the data that's available on the internet. When those things happen, it may be that demand for these GPUs in these largest data centers will flatten out and we're going to have spare capacity. At which point, as you say, they will be used to repurposed To serve and inference. And then it will be hard to make the case we're building yet more data centers, smaller ones with GPUs closer to the users.”
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