From the course: Agentic AI Design Patterns for GenAI and Predictive AI
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Autonomous self-RAG
From the course: Agentic AI Design Patterns for GenAI and Predictive AI
Autonomous self-RAG
- When it comes to using generative AI systems to produce content for us, we're not always guaranteed that the content the system creates is accurate or complete. For example, if we ask the system to produce a complete list of all the traffic laws in a specific region, it will do its best to put this together for us. But depending on how well it was trained and how reliable its data sources are, the list may not be 100% accurate or complete. We then need to manually review the list and verify that those laws listed are correct, and then further check to see if any more laws need to be added to the list. In other words, the generative AI system will do the bulk of the work for us, but it's up to us to then proof and edit this content before it can be used and relied upon. Retrieval-augmented generation or RAG for short is a traditional technique used with LLMs whereby they're given access to external data sources that they can…
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