> People treat vector search like magic pixie dust but the reality is that it's not that great unless you heavily tune your models to your use cases I believe

> People treat vector search like magic pixie dust but the reality is that it's not that great unless you heavily tune your models to your use cases I believe that what most people miss is that embeddings are the product of the model. Embeddings have been getting so much better with the new models and so embedding-based search improved too. Embeddings are coordinates in a world representation that "organizes" information so that location in that world matters and serve as a way to differentiate meaning. In other worlds, word2vec was a simple and poor world representation. OpenAI embeddings are an astounding world representations coordinates.