If anything you'd think that the neurosymbolic people would be pleased that the LLMs do in fact reason by learning circuits representing boolean logic and truth tables. In a way they were right, it's just that starting with logic and then feeding in knowledge grounded in that logic (like Cyc) seems less scalable than feeding in knowledge and letting the model infer the underlying logic.
Right, that’s my point. LLMs are doing pattern abstraction and in this way can mimic logic. They are not trained explicitly to do just truth tables even thought truth tables are fundamental.
