Earlier quoted context omitted.
If constrained by existing human knowledge to come up with an answer, won’t it fundamentally be unable to push human knowledge forward?
Reasoning is essentially the creation of new knowledge from existing knowledge. The better the model can reason the less constrained it is to existing knowledge. The challenge is how to figure out if a model is genuinely reasoning
Knowledge creation comes from collecting data from the real world, and cleaning it up somehow, and brainstorming creative models to explain it.
NN/LLM's version of model building is frustrating because it is quite good, but not highly "explainable". Human models have higher explainability, while machine models have high predictive value on test examples due to an impenetrable mountain of algebra.