The author introduces the concept of RAG (Retrieval-Augmented Generation), a method to include helpful information in LLM prompts for AI-based products. The author highlights that setting up a RAG pipeline adds complexity to AI systems but mentions that data warehouse providers now offer tools to simplify the process. A unique aspect is the use of text embeddings for multimodal searches across text and images to improve RAG pipelines. The author advises against implementing RAG too early and provides detailed steps on how to build and test a successful RAG pipeline. The article also discusses the challenges and improvements made in implementing RAG using BigQuery, avoiding the need for additional services like Pinecone.
https://www.rainforestqa.com/blog/your-data-warehouse-can-rag