What exactly do you want me to state up front? A general intelligence can solve general problems when those problems are formally specified. Sudoku is a good example of a formally specified problem that can be solved by most people but not by LLMs. This is because LLMs and all neural networks are simply DAGs of function which do not support recursion or backtracking.
Adding recursion to neural networks has been tried a few times but no one actually knows how to stabilize their dynamics so the industry has settled on feed forward networks with constrained function blocks which have stable dynamics with respect to back propagation of errors.
Exactly what was in your comment that I told you to state up front.
Most people in a discussion about AI and replacing people are working with a definition of general intelligence that includes humans to a large degree.
> This is because LLMs and all neural networks are simply DAGs of function which do not support recursion or backtracking.
Without adding external state I can't solve a sudoku puzzle.
Ok great, next time I run into you I'll make sure to remind you that large language models are not intelligent as I conceive of the word "intelligent".
