this post was submitted on 26 Aug 2024
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I'd like all ai service to publish the energy used in training the model and performing inference.
"Queries uses an average of X kWh of power. A model training run requires X MWh, and the development of this model over the years required X TWh of power."
Then we could judge companies by that metric. Off course, rich people would look for the most power-draining model for the sake of it.
That's already something that Meta is doing for their Llama models:
You can extrapolate openai models consumption from these I guess
ok, but
Is it still bad if they use renewables? in which case, it's not horrendous, is it?
what about the rest of their servers?
Fuck facebook
If we are abundant in renewable energy no but if we are still at a level where available renewable energy can be used to replace non-renewable, then AI tech needs to justify its use cases too.
and servers yes, social media related data center energy consumption should be put under heavy scrutiny too. Especially considering some energy hungry social media platforms like facebook are lately causing more harm than good (on other fronts such as political propaganda and racism). I doubt any of these are gonna happen soon though since many governments are heavily invested in using social media and LLM chatbots for propaganda and surveillance.
We already have a way for society to decide what is and isn't worth spending power and effort on and it's called money.
Increase carbon taxes to incentivize clean fuel sources and ban predatory advertising and data tracking behaviour because it's problematic.
We do not need to setup a separate shadow economy to gatekeep what is and isn't worth spending eoectricity on.
This part is kind of hard to measure. When do you start counting? From the first work that informed the research direction eventually leading to this model? From the point where the concept of this final model first came about? Do you split the energy usage between multiple models that came from the same work?