They mostly aren't. The lack of transparency around how many parameters frontier models have and how long they're trained is a big obstacle when it comes to est

They mostly aren't. The lack of transparency around how many parameters frontier models have and how long they're trained is a big obstacle when it comes to estimating the energy impact of training very large models. A group at Stanford has been benchmarking model providers by transparency here: https://crfm.stanford.edu/fmti/May-2024/index.html https://crfm.stanford.edu/fmti/May-2024/index.html I think a great way to create positive change in the world is to pressure OpenAI, Anthropic, Google, XAI, and Meta to all share details about the energy cost of training and inference for their models. If every major provider provided this transparency, it would be less valuable to keep that info secret from a "keep your competitors in the dark" perspective. It would also allow customers to make decisions based on more than just performance and cost.