If you figure it out - please let me know 😆

A wins a win 😆

For the most part! Though we're finding that for memory its far more accurate to be represented using a knowledge graph vs a vector db.

I'm not sure if this one will be recorded, its going to be at a conference. I'll most likely do a version of it for my AI User Group which I will record :)

Thanks! This one will be on memory management of LLMs. Specifically methods to not only capture memory but the different facets of what should be captured and stored for a better experience using AI

Revamping our onboarding guides, fixed a gap in my testing suite, and started outlining a talk I’m giving in March.

This kind of thing can make all the difference in helping keep a users attention!

Just finished up the V1 designs for Stylo Scorecard! It’s a monthly scorecard where people can sign up to see how well their Knowledge Base is set up to be used as a context source for AI.

I think what I need to build is a tool to essentially identify these issues up front and score the KB on qualitative metrics. Could be important for RAG quality as well

- Overfitting (not a problem in my use case, but could be for general model builders)

- Interlinked content ( also an issue for RAG)