Comment by unsupp0rted
16 hours ago
Even if LLMs didn't advance at all from this point onward, there's still loads of productive work that could be optimized / fully automated by them, at no worse output quality than the low-skilled humans we're currently throwing at that work.
inference requires a fraction of the power that training does. According to the Villalobos paper, the median date is 2028. At some point we won't be training bigger and bigger models every month. We will run out of additional material to train on, things will continue commodifying, and then the amount of training happening will significantly decrease unless new avenues open for new types of models. But our current LLMs are much more compute-intensive than any other type of generative or task-specific model
Run out of training data? They’re going to put these things in humanoids (they are weirdly cheap now) and record high resolution video and other sensor data of real world tasks and train huge multimodal Vision Language Action models etc.
The world is more than just text. We can never run out of pixels if we point cameras at the real world and move them around.
I work in robotics and I don’t think people talking about this stuff appreciate that text and internet pictures is just the beginning. Robotics is poised to generate and consume TONS of data from the real world, not just the internet.
Yeah, another source of "unlimited data" is genetics. The human reference genome is about 6.5 GB, but these days, they're moving to pangenomes, wanting to map out not just the genome of one reference individual, but all the genetic variation in a clade. Depending on how ambitious they are about that "all", they can be humongous. And unlike say video data, this is arguably a language. We're completely swimming in unmapped, uninterpreted language data.
Inference leans heavily on GPU RAM and RAM bandwidth for the decode phase where an increasingly greater amount of time is being spent as people find better ways to leverage inference. So NVIDIA users are currently arguably going to demand a different product mix when the market shifts away from the current training-friendly products. I suspect there will be more than enough demand for inference that whatever power we release from a relative slackening of training demand will be more than made up and then some by power demand to drive a large inference market.
It isn’t the panacea some make it out to be, but there is obvious utility here to sell. The real argument is shifting towards the pricing.
> We will run out of additional material to train on
This sounds a bit silly. More training will generally result in better modeling, even for a fixed amount of genuine original data. At current model sizes, it's essentially impossible to overfit to the training data so there's no reason why we should just "stop".
You'd be surprised how quickly improvement of autoregressive language models levels off with epoch count (though, admittedly, one epoch is a LOT). Diffusion language models otoh indeed keep profiting for much longer, fwiw.
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I'm just talking about text generated by human beings. You can keep retraining with more parameters on the same corpus
https://proceedings.mlr.press/v235/villalobos24a.html
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How much of the current usage is productive work that's worth paying for vs personal usage / spam that would just drop off after usage charges come in? I imagine flooding youtube and instagram with slop videos would reduce if users had to pay fair prices to use the models.
The companies might also downgrade the quality of the models to make it more viable to provide as an ad supported service which would again reduce utilisation.
For any "click here and type into a box" job for which you'd hire a low-skilled worker and give them an SOP to follow, you can have an LLM-ish tool do it.
And probably for the slightly more skilled email jobs that have infiltrated nearly all companies too.
Is that productive work? Well if people are getting paid, often a multiple of minimum wage, then it's productive-seeming enough.
Another bozo making fun of other job classes.
Why are there still customer service reps? Shouldn’t they all be gone by now due to this amazing technology?
Ah, tumbleweed.
Who is generating videos for free?