Fine-Tuning is a process in AI where a pre-trained model is further trained on a specific dataset to adapt it to a particular task. It allows the model to leverage its existing knowledge while specializing in new domains.
Example: Fine-tuning a language model like GPT to generate legal documents by training it on a dataset of legal texts.
This approach saves time and resources compared to training a model from scratch.