As we scale to GPT-5.2 and beyond, the energy footprint of centralized data centers in the US is becoming a physical limit. I'm theorizing that the next step isn't "bigger models," but smarter routing to specialized, regionally-hosted inference hubs. If we can't shrink the models, we must optimize the path to the user. I'm curious about the community's take on "Inference-at-the-edge" for LLMs. Is the future a single global brain, or a fragmented network of sovereign AI nodes?
[link] [comments]