RAG With The Right Embedding
Today’s post is inspired by Anton Troynikov’s talk at this year’s AI Engineer Conference.
There are many things that can be improved in our RAG(Retrieval Augmented Generation) pipeline. We can enrich our datasets, optimize our embedding, or use advanced retrieval methods. Ultimately, we aim to achieve the goal of returning more of the most relevant info…
Keep reading with a 7-day free trial
Subscribe to The MLnotes Newsletter to keep reading this post and get 7 days of free access to the full post archives.