Fine-tuning
Fine-tuning is the process of giving additional specialized training to an already-trained general-purpose AI model so it can better perform specific tasks or understand domain-specific knowledge.
How it works
Think of it as sending a knowledgeable generalist back to school to specialize in one field. It works by further training a pre-trained base model on domain-specific datasets (such as customer service conversations or legal documents) and adjusting its internal parameters, improving the model's performance in that area. This allows businesses to obtain a highly customized, specialized AI assistant at a relatively low cost.
Examples
- 1.Training a general-purpose chat model on internal product manuals and customer service scripts to turn it into a professional support assistant.
- 2.Fine-tuning a model on medical papers and case reports so it can help doctors with diagnostic analysis.
- 3.Training a text generation model on literary works in a particular style so it can create in that style.