Semantic Search Optimization
RAG (Retrieval-Augmented Generation) is a method that combines information retrieval and text generation to improve the quality and accuracy of the answers generated by language models. The simplest way to understand RAG is to imagine chatting with ChatGPT; it almost answers all the questions you ask because it has been trained on many data sources. This is both an advantage and a disadvantage: the advantage is that it knows everything; the disadvantage is that sometimes it doesn't know specific details, providing vague answers. RAG, on the other hand, limits the amount of knowledge the language models learn, or only learns and answers questions based on a limited dataset we provide. It sounds simple, but the reality is quite complex.
🕝4 months ago