[empath-nirvana]

I'll give you an example of something i did with a vector database.

I was playing around with making my own UI for interfacing with chatgpt. I saved the chat transcripts in a normal postgres DB, along with the open AI embeddings for each message in a vector db, with a pointer to the message id in postgres in the vector DB metadata.

Then as you chatted, i had chatgpt continuously creating a summary of the current conversation you were having in the background and doing a search in the vector db for previous messages about whatever we're talking about, and it would inject that into the chat context invisibly. So you can do something like say: "Hey do you remember when we talked about baseball" and it would find a previous conversation where you talked about so and so hitting a home run into the context and the bot would have access to that, even though you never mentioned the word "baseball" in the previous conversation -- home run is semantically similar enough that it finds it.

If you're using openai embeddings as your vectors, it's _extremely_ impressive how well it finds similar topics, even when the actual words used are completely different.