this post was submitted on 22 Dec 2024
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It's all made from our data, anyway, so it should be ours to use as we want

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[–] [email protected] 9 points 1 day ago* (last edited 1 day ago) (3 children)

The environmental cost of training is a bit of a meme. The details are spread around, but basically, Alibaba trained a GPT-4 level-ish model on a relatively small number of GPUs... probably on par with a steel mill running for a long time, a comparative drop in the bucket compared to industrial processes. OpenAI is extremely inefficient, probably because they don't have much pressure to optimize GPU usage.

Inference cost is more of a concern with crazy stuff like o3, but this could dramatically change if (hopefully when) bitnet models come to frutition.

Still, I 100% agree with this. Closed LLM weights should be public domain, as many good models already are.

[–] [email protected] 2 points 20 hours ago

With current kWh/token it's 100x of a regular google search query. That's where the environmental meme came from. Also, Nvidia plans to manufacture enough chips to require global electricity production to increase by 20-30%.

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[–] [email protected] 0 points 11 hours ago
[–] [email protected] 5 points 23 hours ago (1 children)

Delete them. Wipe their databases. Make the companies start from scratch with new, ethically acquired training data.

[–] [email protected] 2 points 21 hours ago (1 children)

Mmm yes so all that electricity is pure waste

[–] [email protected] 1 points 19 hours ago (2 children)

Genuine question, does anyone know how much of the electricity is used for training the model vs using it to generate responses?

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[–] [email protected] 1 points 17 hours ago
[–] [email protected] 2 points 23 hours ago* (last edited 23 hours ago)

Only if they were trained on public material.

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