Retrieval Augmented Generation (RAG) – using AI models effectively
What is Retrieval Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is an advanced AI technique in AI language modeling based on the integration of external information sources to improve and augment answer generation. A RAG system combines the comprehensive knowledge capacities of a Large Language Model (LLM) with the ability to obtain specific information from an external knowledge repository. This AI method allows the model to generate answers based not only on its internally trained knowledge, but also on current, specific and extensive external data. Find out more now!
