Data
Fine-Tuning
Fine-tuning is the process of training an existing AI model on additional task-specific data so its weights adapt to a narrower domain. It improves performance on specialized tasks but costs more upfront than RAG and locks the knowledge into model weights.
Related terms
- RAG (Retrieval-Augmented Generation) — RAG is a pattern in which an AI model retrieves relevant documents from a knowledge base at query time and uses them as additional context to generate its response.