Definition
Fine-tuning is a form of transfer learning where a large, general foundation model is adapted to a specific use case by training it on a curated dataset. The result is a model better suited to domain-specific language, format and expertise. Fine-tuning requires significant data and compute, and is not always the best solution - RAGRetrieval Augmented Generation - AI architecture where the model is supplemented with documents retrieved in real-time to provide fact-based answers. and prompt-engineering are often cheaper alternatives.