I definitely think breaking out ChatGPT on its own is too fine-grained. At the very least, one should lump all LLM training and use, or perhaps all deep learning training and use together.
I suspect at a "sensible" breakdown (trying to avoid the "How long is my coastline?" problem), which is presumably something akin to Zipfian, the main uses will actually account for most energy usage.
If anyone can find a breakdown at the level of granularity that "all deep learning" would make sense, let me know: so far my Googling has led primarily to either detailed breakdowns of energy _sources_, or high-level breakdowns of use at the level of "industry", "agriculture", or "residential use".
I suspect at a "sensible" breakdown (trying to avoid the "How long is my coastline?" problem), which is presumably something akin to Zipfian, the main uses will actually account for most energy usage.
If anyone can find a breakdown at the level of granularity that "all deep learning" would make sense, let me know: so far my Googling has led primarily to either detailed breakdowns of energy _sources_, or high-level breakdowns of use at the level of "industry", "agriculture", or "residential use".