DeepSeek might not be such good news for energy after all
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The original claims of energy efficiency came from mixing up the energy usage of their much smaller model with their big model I think.
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This article is comparing apples to oranges here. The deepseek R1 model is a mixture of experts, reasoning model with 600 billion parameters, and the meta model is a dense 70 billion parameter model without reasoning which preforms much worse.
They should be comparing deepseek to reasoning models such as openai's O1. They are comparable with results, but O1 cost significantly more to run. It's impossible to know how much energy it uses because it's a closed source model and openai doesn't publish that information, but they charge a lot for it on their API.
Tldr: It's a bad faith comparison. Like comparing a train to a car and complaining about how much more diesel the train used on a 3 mile trip between stations.
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So the answer, as always, is ban useless, power-sucking, unreliable, copyright-infringing AI.
Why do I feel that this will never happen? That we will continue to use this horrible technology to the end of our days with people constantly making excuses for its existence? Ugh.
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That’s kind of a weird benchmark. Wouldn’t you want a more detailed reply? How is quality measured? I thought the biggest technical feats here were ability to run reasonably well in a constrained memory settings and lower cost to train (and less energy used there).
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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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It's more like comparing them while they use the same fuel (as the article directly compares them in joules): Let's say the train also uses gasoline. The car is a far more "independent", controllable, and "doesn't waste fuel driving to places you don't want to go" and thus seen as "better" and more appealing, but that wide appeal and thus wide usage creates far more demand for gasoline, dries up the planet, and clogs up the streets, wasting fuel idling at traffic stops.
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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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Yeah, I was thinking diesel powered trains
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The AI models use the same fuel for energy.
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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.
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A bit flawed. What if the same prompts are used but both models are required to keep their responses equally brief?
