What Is Fine-Tuning in AI?
Fine-tuning is the process of taking an AI model that has already been trained on broad data and training it further on a smaller, specialized dataset so that it performs better on a particular task, style, or subject. It adapts an existing model rather than building a new one from scratch.
Fine-Tuning vs. RAG
Fine-tuning changes the model’s internal parameters. Retrieval-augmented generation (RAG) leaves the model unchanged and supplies relevant documents at the time of each request, which makes it easier to keep information up to date.
Typical Uses
Teaching a consistent tone, a specialized vocabulary, or a specific output format are common reasons to fine-tune.
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Last updated: September 29, 2026. This definition is for general educational purposes only. It is not financial, investment, tax, legal, or medical advice, and it does not recommend any product or course of action. For decisions about your own situation, consult a qualified professional.