Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 01 Apr 24
- Retrieval-Augmented Generation (RAG) uses contextual learning to improve responses and reduce errors, making it useful for Generative AI.
- RAG systems are easier to maintain and less technical, which helps keep them updated with changing needs.
- However, RAG can have shortcomings like poor retrieval strategies and issues with data privacy, leading to incomplete or incorrect answers.