People are going to keep saying this about autoregressive models, how small errors accumulate and can't be corrected, while we literally watch reasoning models say things like "oh that's not right, let me try a different approach".
To me, this is like people saying "well NAND gates clearly can't sort things so I don't see how a computer could".
Large transformers can clearly learn very complex behavior, and the limits of that are not obvious from their low level building blocks or training paradigms.
People are going to keep saying this about autoregressive models, how small errors accumulate and can't be corrected, while we literally watch reasoning models say things like "oh that's not right, let me try a different approach".
To me, this is like people saying "well NAND gates clearly can't sort things so I don't see how a computer could".
Large transformers can clearly learn very complex behavior, and the limits of that are not obvious from their low level building blocks or training paradigms.