Google DeepMind Finds a Fundamental Bug in RAG: Embedding Limits Break Retrieval at Scale
Retrieval-Augmented Generation (RAG) techniques typically depend on dense embedding fashions that map queries and paperwork into fixed-dimensional vector areas. While this strategy has change into the default for a lot of AI purposes, a current analysis from Google DeepMind crew explains a basic architectural limitation that can’t be solved by bigger fashions or higher coaching…
