Improving AI using transfer and few-shot learning techniques

Few-shot learning involves training models using only a small number of examples, which enhances the adaptability of AI systems. They can rapidly accommodate new tasks or categories due to their ability to learn from limited data. This is especially beneficial when it is difficult or expensive to acquire a significant amount of labeled data.