Fine-Tuning

Fine-tuning is the process of taking a pre-trained foundation model and further training it on a smaller, more specific dataset to improve its performance for a particular task or domain. A general-purpose LLM fine-tuned on medical literature becomes better at clinical language. One fine-tuned on a company's internal documents becomes better at answering questions about that company's products and processes.

Fine-tuning is how organizations customize AI behavior without training a model from scratch — which would require enormous compute resources and data.