LLMs · RAG Fundamentals
RAG: what it is and how it actually works
What retrieval-augmented generation is, the indexing and answering pipelines step by step, a worked example with real similarity scores, and where RAG breaks.
What retrieval-augmented generation is, the indexing and answering pipelines step by step, a worked example with real similarity scores, and where RAG breaks.
How an embedding model turns text into a vector, how it learns similarity, how vectors are searched at scale, and how semantic chunking decides what gets a vector.