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?

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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]