Retrieval-Augmented Generation

Retrieval-Augmented Generation is a technique using prior data and/or content, ingesting that data into a specialized Database , most likely a Vector Databases or a Multi Modal Databases , and then feeding it into an AI Model , such as an LLM . RAG promises to solve for the issue that most people and organizations are trying to work with AI in a way that is specific.

Building Production-Ready RAG Applications: Jerry Liu

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Building RAG with enterprise open source AI infrastructure from Canonical

The BEST Way to Chunk Text for RAG

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2025, February 2. [You HAVE to Try Agentic RAG with DeepSeek R1 (Insane Results)](https://youtu.be/uWDocIoiaXE?si=hACxzxH4qNI6Ez6z). Cole Medin. [[Deepseek]]

! Agentic RAG#When Agentic AI AI Agents use RAG techniques, it's called Agentic RAG

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