If you live in the U.S., marginal electricity demand during the day is almost invariably met with solar or wind (solar typically runs at a huge surplus on sunny days). Go forth and AI in peace, marcyb5st.
Thanks! That helps somewhat. However, it feels like that's just part of the story.
If I remember correctly hyperscalers put their green agendas in stasis now that LLMs are around and that makes me believe that there is a CO2 cost associated.
Still, any improvement is a good news and if diffusion models replace autoregressive models we can invest that surplus in energy in something else useful for the environment.
This made me wonder - do any cloud compute systems have an option to time jobs or use physical resources geographically based on surplus power availability to minimise emissions?
I reckon it might incidentally happen if optimising for cost of power depending how correlated that is to carbon intensivity of power generation, which admittedly I haven't thought through.
If I remember correctly hyperscalers put their green agendas in stasis now that LLMs are around and that makes me believe that there is a CO2 cost associated.
Still, any improvement is a good news and if diffusion models replace autoregressive models we can invest that surplus in energy in something else useful for the environment.