Improving AI using transfer and few-shot learning techniques

 In contrast, few-shot learning emphasizes instructing AI models to gain insight from a limited number of instances. This is particularly advantageous when obtaining labeled data is difficult and expensive. By allowing AI models to make inferences from a small number of examples, few-shot learning reduces the need for a large amount of data.