Retrieval augmented generation (RAG) is probably the most referenced acronym in generative AI, aside from LLM. The reason for this is simple. RAG makes LLM-enabled knowledge assistants more accurate by grounding them in a specific dataset. Generative AI is a knowledge assistance revolution. It is unlocking access to information in our vast stores of text data. Multimodal models indeed handle more than text. However, textual data has been nearly impenetrable for machines to make sense of at scale. LLMs have changed that situation.
https://synthedia.substack.com/p/no-code-rag-and-the-generative-ai
