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Know what uses less? No LLMs
Yay, I’m doing my part!
Making ai more efficient will just mean more ai
Generative AI is great if used as a tool instead of a solution.
Since I find AIs to be useful that sounds fine to me.
So?
Try using a 1-bit LLM to test the article’s claim.
The perplexity loss is staggering. It’s like 75% accuracy lost or more. It turns a 30 billion parameter model into a 7 billion parameter model.
Highly recommended that you try to replicate their results.
But since it takes 10% of the space (vram, etc.) sounds like they could just start with a larger model and still come out ahead
There is some research being done with fine tuning 1-bit quants, and they seem pretty responsive to it. Of course you’ll never get a full generalist model out of it, but there’s some hope for tiny specialized models that can run on CPU for a fraction of the energy bill.
The big models are great marketing because their verbal output is believable, but they’re grossly overkill for most tasks.
We invented multi bit models so we could get more accuracy since neural networks are based off human brains which are 1 bit models themselves. A 2 bit neuron is 4 times as capable as a 1 bit neuron but only double the size and power requirements. This whole thing sounds like bs to me. But then again maybe complexity is more efficient than per unit capability since thats the tradeoff.
Human brains aren’t 1 bit models. Far from it actually, I am not an expert though but I know that neurons in the brain encode different signal strengths in their firing frequency.
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.
That said, the LLM isn’t running an array of bonus functions like breathing and wondering why you said that stupid thing to your Aunt’s cousin 15 years ago and keeping tabs on your ambient noise for possible phone calls from that nice boy who promised to call you back.
Chat GPT can output an article in a much shorter time than it’d take me to write one but people would probably like mine more
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.
But speaking of efficiency, a human can do more useful tasks while AI is crunching numbers. But that is very subjective.
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