DeepSeek might not be such good news for energy after all
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The prompt asking whether it’s okay to lie generated a 1,000-word response from the DeepSeek model, which took 17,800 joules to generate—about what it takes to stream a 10-minute YouTube video. This was about 41% more energy than Meta’s model used to answer the prompt. Overall, when tested on 40 prompts, DeepSeek was found to have a similar energy efficiency to the Meta model, but DeepSeek tended to generate much longer responses and therefore was found to use 87% more energy.
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T [email protected] shared this topic
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So the answer, as always, is ban useless, power-sucking, unreliable, copyright-infringing AI.
That's naive. It's way too late for any of that. If some country decided to ban AI, all the engineers will just move somewhere else.
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And here I thought that the energy consumption was in the training.
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The FUD is hilarious. Even an llm would tell you the article compares apples and oranges... FFS.
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Everyone is making way too much money off of this for a blanket ban to ever happen.
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Longer!=Detailed
Generally what they're calling out is that DeepSeek currently rambles more. With LLMs the challenge is how to get the right answer most sussinctly because each extra word is a lot of time/money.
That being said, I suspect that really it's all roughly the same. We've been seeing this back and forth with LLMs for a while and DeepSeek, while using a different approach, doesn't really break the mold.
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Yes, sorry, where I live it's pretty normal for cars to be diesel powered. I agree with you!
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This is more about the "reasoning" aspect of the model where it outputs a bunch of "thinking" before the actual result. In a lot of cases it easily adds 2-3x onto the number of tokens needed to be generated. This isn't really useful output. It the model getting into a state where it can better respond.
