I feel my comment tracks extremely well with the sections you cite and that it takes some mental gymnastics to read exactly the link you provided and then act like my comments somehow don’t track. The original criticisms were about failure of source data for large models (eg reddit for GPT) to account for fast shifts in social activism language specifically.

The other major problematic section is on energy use and unqualified comparison of units of large model training with carbon emissions of other activities (with no attempt to account for societal value of ML model research or training, nor economies of scale as training technology democratizes it and makes it cheaper). It is similar to the incredibly specious diatribes from Stephen Diehl lately balking at the raw energy numbers of Bitcoin mining, as if those numbers mean anything or relate to any conclusions on their own.

I wrote up a lot more of my thoughts on Gebru’s bad article when it was first leaked. Here’s that comment:

- https://news.ycombinator.com/item?id=25314824

I also feel you are very commonly involved in lengthy downvote / flagging threads with disingenuous takes on others’ comments and deliberate unwillingness to apply charitable takes or avoid taking things out of context. I am sure from your POV you don’t feel that way and I’m not asking anyone to agree with my assessment; I have zero goal of citing things to back it up. I am just going to preemptively drop off from replying to you any further.