Zero-shot Learning

Zero-shot learning is a technique in artificial intelligence that allows a model to recognize and understand new concepts without having seen examples of those concepts during its training. Imagine teaching a child about animals but not showing them every species. If you explain what a "zebra" is using attributes like "striped" and "horse-like," the child can identify zebras even if they've never encountered one before. Similarly, in zero-shot learning, AI can make predictions about unfamiliar categories by leveraging its existing knowledge and understanding of related concepts, enabling it to perform tasks without specific prior examples.