Large Language Models (LLMs) and ChatGPTs, while incredibly impressive, are far from perfect. Sometimes, LLMs provide made-up responses that are untrue, a phenomenon known as hallucinations. Additionally, there are other drawbacks such as staleness and a lack of customization.
Retrieval Augmented Generation (RAG) integrates databases with AI to solve these issues. RAG combines text generation with data retrieval from specified sources, reducing hallucinations, addressing staleness by updating information, and providing external sources for verification.
It's like an LLM taking an open-book test!
Watch this video for more!
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