Fine-Tuning
The process of further training a pre-trained AI model on a specific dataset or task to adapt its capabilities for a particular use case.
In plain language
Taking a general-purpose AI and specialising it for a specific job. Like taking a general doctor and training them as a cardiologist; same foundation, but now expert in one area.
Why this matters
Fine-tuning introduces governance obligations. When your organisation customises a foundation model, you become responsible for the behaviour of the resulting model and any harms it produces. Your governance framework should include policies for testing, validation and documentation of fine-tuned models.
Relevance
GovernanceFine-tuning creates a new point of responsibility and accountability, requiring organisations to implement controls over model customisation and deployment.
Related terms
Putting fine-tuning into practice in your organisation?
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