I definitely have that question too. I view us as big LLMs.

But, even if we drop that interesting edge case i suspect we can make something very useful with the primitive that LLMs offer.. in the calculator example. ChainLang and co seem a really interesting tool for LLMs.

And additionally, whether our memory and long term learning - and even our goal-choosing - is fundamentally different from an indexed storage of strings of tokens that can be brought back into short-term context when “triggered” by their embedding-similarity to the current context.