Retrieval-augmented generation enhances large language model prompts with relevant data for more practical, accurate responses.
Related resources
- GTC session: Techniques for Improving the Effectiveness of RAG Systems
- GTC session: Retrieval Augmented Generation: Overview of Design Systems, Data, and Customization
- GTC session: How to Leverage Retrieval-Augmented Generation (RAG) With Red Hat OpenShift AI and NVIDIA AI Enterprise (Presented by Red Hat, Inc.)
- SDK: NeMo Retriever
- Webinar: Building Intelligent AI Chatbots Using RAG
- Webinar: Achieve World-Class Text Retrieval Accuracy for Production-Ready Generative AI
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