Glossary · Technical
Fine-Tuning
Additional training applied to an already-trained model using a narrower dataset, used to adjust its behavior, style or knowledge for a specific purpose.
What it is
A model is first trained on a broad, general dataset, then optionally fine-tuned on a smaller, targeted one to specialize its behavior — for example, to follow instructions more reliably or adopt a particular tone. Fine-tuning adjusts the model's existing weights rather than building a new model from scratch.
Why it matters for AI visibility
A fine-tuned model's knowledge of a brand is fixed at the point fine-tuning happened, the same way a base model's is fixed at its training cutoff. Fine-tuning changes how a model behaves or reasons, not what current information it has access to — that still depends on retrieval or live browsing.
See more terms in the full glossary, or read the AI Visibility 101 guide for the full picture.