> When you're dealing with ten notes, it's trivial to dump them into an LLM and generate connections. With a hundred notes, it's still manageable. But what happens when you hit 10,000 notes? Or a million? We quickly run into the limitations of context windows and processing capacity. Vector search helps narrow things down, but it's prone to missing important connections that a human mind might naturally make. I run i…
Author here. Glad I'm not the only one with this problem! What I'm experimenting with is building a graph out of "entities", which I'm calling people, places and things found in each card. The point I guess is to allow the LLMs to make connections between cards, but this won't be replacing user made connections. This lets me pick up all cards that reference something like, I don't know, "factories" as a concept, whic…
It's good for bridging the gaps between LLMs, ontologies, traditional structured data, and logic programming.