This article discusses the importance of real-time access for Retrieval Augmented Generation (RAG) and how Redis can enable this through its real-time vector database, semantic cache, and LLM memory capabilities, leading to faster and more accurate responses in GenAI applications.
Explore how semantic caching, which understands the meaning behind user queries, can boost performance and relevance in AI applications by storing and retrieving data based on intent.
