You missed the core of my point: humans operate, including in the real world, on much less training data. Give a human a shopping cart and ask them to push it backwards, and they'll figure it out in a few minutes even if they've never done it before.
This is the bit that's missing that LLMs do approximate amazingly well through sheer training set size, but in my opinion, it puts a cap on what novel things they can achieve in comparison with humans.
To me, I've thought about a related "invention space" before: with us creating software to solve many problems people are facing, why are there not any perfect solutions for any problem (running a cafe? a CNC machine? ...), and we always need more software built to cover one small (novel?) change for a particular owner?
The world space is just so large that you need whatever this intelligence is humans (and animals) have to navigate it successfully — but LLMs do not intrinsically.
Whether they can be so large that it does not matter in 99.99% of cases is to be seen.
This is the bit that's missing that LLMs do approximate amazingly well through sheer training set size, but in my opinion, it puts a cap on what novel things they can achieve in comparison with humans.
To me, I've thought about a related "invention space" before: with us creating software to solve many problems people are facing, why are there not any perfect solutions for any problem (running a cafe? a CNC machine? ...), and we always need more software built to cover one small (novel?) change for a particular owner?
The world space is just so large that you need whatever this intelligence is humans (and animals) have to navigate it successfully — but LLMs do not intrinsically.
Whether they can be so large that it does not matter in 99.99% of cases is to be seen.