Fine-tuning

Fine-tuning in artificial intelligence (AI) refers to the process of further training a pre-trained model with specific data or tasks to improve its performance. Rather than training a model from scratch, fine-tuning can save time and resources by using existing knowledge and patterns of the pre-trained model. By adapting to specific requirements or data, the model can improve its ability to predict, classify or generate content. Fine-tuning allows AI models to be adapted to new problems and support specific tasks or use cases. It is an efficient way to optimise the performance of AI models and develop customised solutions. Other methods are few-shot-learning and zero-shot-learning.