Could the best LLM be able to generate a symbolic AI that is superior to itself, or is there something superior about matrices vs graphs?

Deep neural network AIs have beaten symbolic AIs across the board on many tasks, but is there a chance that symbolic AIs written by DNNs(LLMs), could beat those? And if not, why not? My gut tells me that no, discrete symbolic systems (of ifs/jumps/function calls/abstractions etc), are inferior to fuzzy matrices, but I'm curious if there is a formula or something that explains why (something like Shannon's information paper)? submitted by /u/breck [link] [comments]