Google DeepMind Finds a Fundamental Bug in RAG: Embedding Limits Break Retrieval at Scale | Insights by Willow Ventures
Understanding the Limitations of Retrieval-Augmented Generation Systems Retrieval-Augmented Generation (RAG) systems heavily utilize dense embedding models that translate queries and documents into fixed-dimensional vector spaces. This technique has become standard in many AI applications. However, recent research from Google DeepMind has highlighted a fundamental architectural limitation in these systems that cannot be addressed simply through […]