I don’t think it’s going to be a “winter”, but there are definitely some bubbles to burst. Especially when LLMs become half-assed products and the general public’s heightened expectations are not met.
Years ago so many ‘machine learning’ startups failed because their predictions were 90% accurate but 99.99% was needed for businesses to pay for them. These old scars seem to be missing in LLM mania - why will businesses pay for them now when the previous non hallucinating ML models weren’t reliable enough.
I think the biggest bubble that needs to burst is probably the whole "AGI" thing.
The definition of it isn't clear but from what I gather it's basically an aggregate of emergent capabilities that work together to produce a singularity.
Maybe with enough resources it's possible but I highly doubt it'll be economically feasible given how much has gone into it so far and how far we really are away from something like that with current models.
In my opinion you could make an LLM 100x bigger and it would only get better at generating the next token in a sentence. And everyone knows that the best sentences are not constructed by the most intelligent people with the most accurate world model, but by the people who are best at constructing sentences. It's a dead end in terms of real intelligence and reasoning imo.
People that make the best sentences don't necessarily make the world go round.
In most scenario's, a barely adequate sentence is enough to keep the world turning..
AGI, in the sense you mention, is an imagined/hoped-for supreme-power that will save/destroy us all (or maybe just the "worthy"/"unworthy" ones).
In an age of such hopelessness about the future, this looks a lot like an emotional crutch wrapped in the veil of rationality - just the thing an anxious materialist needs to make sense of the world.
Like many cults and religions it mistakes the plausible for possible and possible for probable.
The problem with religious beliefs like these is that they don't just disappear with evidence or sufficient reasoning.
I don't think that particular bubble is bursting anytime soon.
If that's the goal then perhaps we already surpassed it and I personally am not impressed.
It's useful but basically every method of quality control requires a human.
I've found that components of general intelligence specialized beyond human capability are much more useful than a model that can mimic a human.
I think an LLM is just trying to do too much at once, all of the individual NLP algorithms most of them are made of are very useful to us, but an LLM is just not specialized enough to be any more useful than a human without specialization.
Which isn't to say they're _useless_, but obviously not as useful as a specialist (in special contexts, denoted by whatever kind of specialist they are)
ETA: as an aside, I'd like to contextualize my presumption that AGI is about AI singularity with the fact that Sam Altman casually stated that he doesn't care if it takes $50 billion to reach AGI.
In the real world, with 50 billion dollars, you can do something much more useful than trying to build a product that's basically contradictory by definition.
An AGI is (presumably) a general intelligence model but it's implicitly touted as being extremely useful for specialized tasks (because, humans can specialize), but once you specialize, I would argue your general intelligence tends to weaken. (For example I wouldn't expect a Harvard PhD to be 100% up to date with modern slang terms, but I'd be shocked if I went to a local bar and met someone who didn't know what rizz means).
This is basically just trying to squeeze two opposite ends of a spectrum together, which sounds kind of like a singularity to me.
Some of the reasons people like Altman get excited are that if AI is as good as humans all round then you can replace the workforce. Also given the way of these things it will get better each year. We'll see.
> people like Altman get excited are that if AI is as good as humans all round then you can replace the workforce.
I get that. I guess my point is this already seems to exist. We could combine AI with machinery to replace almost everything humans can do already, someone just has to build for that solution (e.g. train some models).
AGI just sounds like a sort of automation of that process. And I don't think a bigger LLM will accomplish that task. I think more developers will.
Which I wager would be cheaper and arguably more fortuitous to the human race than $50 billion thrown into one pot