DeepMind exposes a hard mathematical ceiling in vector search
Google DeepMind researchers just proved that single-vector embeddings have a fundamental geometric limit that breaks advanced RAG setups. On their new LIMIT stress test, top embedding models from Google and Snowflake saw recall drop below 20%, while old-school BM25 excelled. Why it matters: simply scaling models won't fix retrieval.