few-shot

In the realm of machine learning, few-shot learning refers to the concept where an artificial intelligence model is trained to learn from a minimal number of examples. This approach is particularly useful in classification tasks where there is a lack of ample training data. It's a significant step towards achieving human-like learning efficiency in AI systems.