AIagent.at 🤖 AI NewsSearch engines have used BM25 for decades, but it can only match keywords, not meaning. RAG with vector embeddings fills this gap by matching semantic similarity instead. This technical article explains how each works, where each wins, and why modern systems increasingly combine both. https://www.marktechpost.com/2026/03/22/how-bm25-and-rag-retrieve-information-differently/ #AIagent #AI #GenAI #AIInfrastructure
How BM25 and RAG Retrieve Information Differently?
When you type a query into a search engine, something has to decide which documents are actually relevant — and how to rank them. BM25 (Best Matching 25), the algorithm powering search engines like Elasticsearch and Lucene, has been the dominant answer to that question for decades. It scores documents by looking at three things: […]