The problems with LLM are numerous but whats really wild to me is that even as they get better at fairly trivial tasks the advertising gets more and more out of hand. These machine dont think, and they dont understand, but people like the CEO of OpenAI allude to them doing just that, obviously so the hype can make them money.
> These machine dont think, and they dont understand But they do solve many tasks correctly, even problems with multiple steps and new tasks for which they got no specific training. They can combine skills in new ways on demand. Call it what you want.
Could they solve tasks? Potentially. But how would we ever know that we could trust them?
With humans we not only have millennia of collective experience when it comes to tasks, judging the result, and finding bullshitters. Also, we can retrain a human on the spot and be confident they won't immediately forget something important over that retraining.
If we ever let a model produce important decisions, I'd imagine we'd want to certify it beforehand. But that excludes improvements and feedback - the certified software should better not change. If course, a feedback loop could involve recertification, but that means that the certification process itself needs to be cheap.
And all that doesn't even take into account the generalized interface: How can we make sure that a model is aware of its narrow purpose and doesn't answer to tasks outside of that purpose?
I think all these problems could eventually be overcome, but I don't see much effort put into such a framework to actually make models solve tasks.