Choosing a Vector Index: HNSW, IVF, and the Trade-Offs

Generative AI Development · part of The Exam Room The situation A knowledge-base assistant on Amazon Bedrock retrieves passages to ground its answers. The embeddings live in a vector store, and at launch the corpus was 40,000 chunks Chunking Splitting documents into retrievable pieces before embedding them – small enough to match precisely, big enough to still make sense. . Queries came back in a…