RAG vs Fine-tuning

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Retrieval-Augmented Generation (RAG)

• When to use: Dynamic content, cost-sensitive applications
• Implementation considerations
• Limitations and challenges

Fine-tuning

• When to use: Specialized tasks, consistent behavior needed
• Resource requirements
• Training considerations