Quality of output does not mean that the process is genuine. A well-produced movie with good actors may depict a war better than footage of an actual war, but that is not evidence of an actual war happening. Statistical LLMs are trying really hard at "acting" to produce output that looks like there is genuine understanding, but there is no understanding going on, regardless of how good the output looks.
This is Searle's Chinese Room posit though right? The argument that there's no abstraction or internal modelling going on. Wish I could find the post I read recently that demonstrated some fairly clear evidence though that there IS some level of internal abstraction/reasoning going on in LLMs.
Do we allow for a matter of degree, rather than a binary, of "zero" vs" "complete" understanding?
At what point does abstraction and reasoning turn into "sentient understanding"? How do you express that as the thing doing the abstracting? Even humans struggle at that kind of task because there's a metaphysical assumption of first principles that these models seem to be challenging (or else this thread would not have started).
Processes such as back propagation are still not understood very well in the human brain. The brain certainly uses electrical impulses in order to transfer signals, much like the 1s and 0s in your computer or phone. The gap between us and intelligent machines is probably not as well understood or clear as most people in the software industry think it is.
> At what point does abstraction and reasoning turn into "sentient understanding"?
This is a loaded question, you're assuming that abstraction and reasoning can somehow magically "turn into" sentience, whereas I posit that those two things are completely different. You can have sentience without reasoning (i.e. pure non-judgemental awareness that is the goal of Buddhist meditation), and vice-versa.
