How Vector Databases Efficiently Find Matches For RAG
SMRTR summary
Vector databases improve RAG systems by quickly matching queries to document embeddings using algorithms like HNSW, creating graph structures for fast navigation and enabling LLMs to incorporate external knowledge efficiently.
SMRTR provides this summary for quick context. The original article belongs to Medium.
Read the original article