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These NVIDIA GPUs aren't general purpose in the way that you think. They can't even run games. Nvidia blackwell is probably slightly more efficient than TPUs for training. Do you really expect a 4 trillion company with the majority of its revenue being AI for some years now, not to have built its flagship product fully around AI? The GPU name stuck around, but they are pretty terrible at graphics.

The real efficiency win in these chips is that they are made for inference only. You can throw away the vast majority of a chip if you only need a few ops, a single precision (like INT8 or FP8) and don't need ultra fast interconnects.

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That ... wasn't the kerfuffle
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She wrote the stochastic parrots paper.

Google’s internal review blocked it from publication. Stated reasons were about paper quality. You can speculate whether that was the real reason.

Gebru issued an ultimatum email and said she would resign if some list of conditions weren’t met.

Google said “thanks, we accept your resignation”.

She claims it is retaliation, but it seems more like an own-goal if you ask me. She basically handed Google the solution to their problem.

Practical lesson: don’t tell your employer you might quit before you’re ok with leaving.

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It kind of was. I really hate gaslighting, but GP is not inaccurate. Google claimed it did not meet their bar for publication because it ignored recent research on how to reduce the environmental and bias-related risks of LLMs. On the other hand, a large org is unlikely to subsidize high-profile research that makes it look bad. And Gebru was critical of Google’s internal culture and diversity efforts…
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I haven't read any of these papers, but given the environmental impact of LLMs in 2026, it seems like Timnit Gebru has been thoroughly vindicated...
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