Google AI Introduces STATIC: A Sparse Matrix Framework Delivering 948x Faster Constrained Decoding for LLM-based Generative Retrieval
Building a Whole RAG System: Successes and Failures
This is one of those times that I just read something and go "Wow! That was interesting! But wtf did any of that mean?" Somehow it is always theory math. Too many sweats in the field. Putting on my serious hat now. This is an interesting idea. The core concept of distinguishing RAG (querying based on vector similarity) from constrained decoding (querying based on an ID I just made up) is another abstraction of AI using AI using AI. That idea, at its core, sounds like something someone at FTX would come up with. But then we get to Google basically starting to back-propagate and train this ID generation so that it is relatively smart, and it works somehow. It's the classic idea of AI algorithms: given some context of the past, I can make an educated guess instead of do ing the hard work. And because we never ACTUALLY do the work, we just have to make sure that the answer we came up with is in the database and matches some filters we set up in the new STATIC framework, and its something like 1000x faster and more energy efficient. Wild.