This article addresses the knowledge decay problem in retrieval-augmented generation (RAG) systems, highlighting how outdated information can undermine their effectiveness. It emphasizes the need for real-time updates and staleness metrics to maintain data freshness and reliability as knowledge bases grow.

A search engine performs two main tasks: retrieval, which involves finding documents that satisfy a query, and ranking, which determines the best matches. This article focuses on retrieval, explaining the use of forward and inverted indexes for efficient document searching and the concept of set intersection as a fundamental operation in retrieval processes.