> As it stands I think that LLMs sort of suck at this.
replyMetaphors are at the core of LLM cognition too via vector embeddings. The distance between embeddings is an inverse measure of their metaphorical attachment. That lets AIs scrape meaning from natural language, which demonstrates that natural language is an encoded sequence of metaphors.
I'm going to need a weekend or two to figure out what this means.
replyHave you played with a vector databases and have them explained yet? The grandparent comment is only explaining that concept.
replyNope! But I'm soaking all of this in and I appreciate these nudges.
replyAnd after some thought I'm curious whether this means that LLMs ought to be adept at forming new metaphors as opposed to handling pre-existing ones.