Do you have an example of a public university censoring research papers that passed peer review because that university believed the paper cast "an innacurate negative light"... on what, exactly?
My rejoinder was that if it's inaccurately critical of Google, like hyping carbon impact without mentioning a decades-long carbon mitigation program, I get a lot more sympathetic to Google's position. Why should they pay someone to spread falsehoods about them?
I don't really care about the process minutiae.
"Large language models can have an outsized carbon emissions impact, but not Google's, those are carbon neutral".
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.
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.
* 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
The Gebru paper makes a lot of hay about carbon impact, but Google's put a ton of effort into mitigating that, they've been carbon neutral on paper since 2007: https://blog.google/outreach-initiatives/sustainability/our-...