last weekend i went down the rabbit hole of how to build dynamic ontologies, and kept coming back to clustering of embeddings curious if anyone has cool experiments i could look at around this
kinda like this, but instead of using vec2text - i found grabbing a few samples from each cluster and feeding into an llm came up with better names (not surprisingly)