[joshuamorton]

Does it make sense to mention Google's carbon mitigation program in a paper not specifically about Google?

"Large language models can have an outsized carbon emissions impact, but not Google's, those are carbon neutral".

[free_rms]

They'd probably want to finess it a little bit more than that, but yeah?

If you're going to bring carbon emissions into it, mentioning current mitigations as well seems relevant unless you're writing an op/ed piece.

[joshuamorton]

> mentioning current mitigations

The "mitigation" in question is buying carbon offsets (I mean there are improvements in DC efficiency also, but those only do so much, and language models ballooning 100x isn't going to be fixed with 10 or 50% efficiency improvements). For the moment "carbon neutrality" is only achieved through the purchase of energy offsets.

That doesn't mitigate. It offsets. Don't get me wrong, still better than nothing, but its not a mitigation.

[free_rms]

There's also

* this generation of language models leaning into transfer learning reducing the total number of training runs for different applications

* TPUs being more power efficient than GPUs (the numbers they used in the paper were based on GPUs)

* other energy-centric stuff that's not just offsets, efficiency like you mention in addition to sourcing from renewable