> We used the figure of 0.34 watt-hours that OpenAI’s Sam Altman stated in a blog post without supporting evidence.
what do you think the odds of this being accurate are?
zero?
what do you think the odds of this being accurate are?
zero?
I also wouldn't be surprised if Aramco and Rosneft gave similar estimates on global warming and oil's role in it.
The prompt energy question is something that companies can both actively measure and need to actively measure in order to plan their budgets. It's their job to know the answer.
Those other questions, sadly, fall more into the category of it's their job not to know the answer.
GPT-5 came out on 7th August.
Assuming the 0.34 value was accurate in the GPT-4o era, is the number today still in the same ballpark or is it wildly different?
if I was altman then I'd release a few small numbers to try and get influencers talking about "how little energy chatgpt uses"
and he can never be accused of lying, as without any methodology as to how it was calculated it's unverifiable and completely meaningless
win-win!
...but then Sora came out.
a) training is where the bulk of an AI system's energy usage goes (based on a report released by Mistral)
b) video generation is very likely a few orders of magnitude more expensive than text generation.
That said, I still believe that data centres in general - including AI ones - don't consume a significant amount of energy compared with everything else we do, especially heating and cooling and transport.
Pre-LLM data centres consume about 1% of the world's electricity. AI data centres may bump that up to 2%
I don't think it shows that training uses more energy than inference over the lifetime of the model - they don't appear to share that ratio.
The amount of energy is insane.
At the end of the day green energy is perfect for AI and AI workloads.
Ok, but heating and cooling are largely not negotiable. We need those technologies to make places liveable
LLMs are not remotely as crucial to our lives