When All Context Matters: Extended Cache Augmented Generation - Luis Romero-Sevilla, Orbis
This talk introduces an extended Cache Augmented Generation (CAG) approach to address knowledge representation challenges when dealing with large, interconnected, and frequently updated document collections. The core idea is to leverage large context windows more effectively by distributing documents across multiple parallel CAG instances, allowing a supervisor model to query these instances and synthesize comprehensive answers. This method aims to overcome the limitations of simple RAG and the computational expense of GraphRAG in dynamic data environments.
World's Fair 2026 6 min