Improving AI using transfer and few-shot learning techniques

Few-shot learning, on the other hand, focuses on training AI models by utilizing a small number of examples or instances from a particular class or concept. This approach mimics how humans understand things, as we can recognize unfamiliar objects or images with very little exposure. AI systems can make precise predictions even with limited labeled data by using few-shot learning algorithms.