What is fine-tuning in AI?
Fine-tuning is retraining a model on your own examples so it picks up your style or specialist knowledge. It is powerful but usually not what you actually need.
Answer curated and reviewed byMark Barclay
Key takeaways
- Fine-tuning is retraining a model on your own examples so it picks up your style or specialist knowledge.
- It is powerful but usually not what you actually need.
Fine-tuning takes a base model and nudges its weights using your examples. It is useful when you need consistent tone across thousands of outputs, or specialist jargon that the base model does not know.
For 90% of business use cases, a good system prompt plus RAG (retrieval-augmented generation) beats fine-tuning — it is cheaper, faster to iterate, and stays up to date as you edit your knowledge base.