Improving AI using transfer and few-shot learning techniques

In this method, a pre-trained model goes through further training using new data that is specific to a particular task. In order to adapt to a new task, only the top layers of the model are modified, while the bottom layers remain the same. As a result, the model is able to learn task-specific features without losing the knowledge it acquired during its initial training.