searchguy

zulip for one, is not encrypted at rest.

I've certainly thought about this problem a lot, and knowledge graphs invariably come up as a solution. I've built something that automatically extracts facts/RDF triples from documents and interactions, and indexed them into a vector DB. The quality and utility of the facts can vary though.

do you have references to

> TTT, cannon layers, and titans

I'm a little confused by your statement that "Meilisearch decided to use hybrid search and avoid fusion ranking" when your website [1] says "Hybrid search re-ranking: The final step involves re-ranking results from both retrieval methods using the Reciprocal Rank Fusion (RRF) algorithm."

Can you clarify what you mean by "fusion ranking"?

All hybrid search requires a method to blend keyword and vector search results. RRF is one approach, and cross-encoder-based rerankers is another.

[1]: https://www.meilisearch.com/blog/hybrid-search

Hey, thanks for unpacking what you did at ecodash.ai.

Did you manually curate the queries that you did LLM query expansion on (generating a large number of diverse queries), or did you simply use the query log?