this post was submitted on 01 Jun 2024
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[–] tal@lemmy.today 19 points 5 months ago* (last edited 5 months ago) (8 children)

So, first, that's just a reduction. But set that aside, and let's talk big picture here.

My GPU can use something like 400 watts.

A human is about 100 watts constant power consumption.

So even setting aside all other costs of a human and only paying attention to direct energy costs, if an LLM running on my GPU can do something in under a quarter the time I can, then it's more energy-efficient.

I won't say that that's true for all things, but there are definitely things that Stable Diffusion or the like can do today in a whole lot less than a quarter the time it would take me.

[–] wischi@programming.dev 4 points 5 months ago (5 children)

The problem is that using those tools no matter how energy efficient will add to the total amount of energy humans use, because even if an AI generates an image faster than a human could, the human still needs 100W constantly.

This doesn't mean, that we shouldn't make it more efficient but let's be honest, more energy efficient AI just means that we would use even more AI everywhere.

[–] derpgon@programming.dev 2 points 5 months ago (1 children)

But speaking of efficiency, a human can do more useful tasks while AI is crunching numbers. But that is very subjective.

[–] wischi@programming.dev 2 points 5 months ago* (last edited 5 months ago) (1 children)

It depends what you mean by useful. Most humans are (at least at the moment) more versatile than even the most advanced AI we have. But you have to keep in mind that there are jobs with pretty mundane tasks where you don't really need the intelligence and versatility of a human.

[–] derpgon@programming.dev 1 points 5 months ago

Thats what I meant, keep the tasks separated, and let both what they do better than the other half.

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