Zero-shot learning

Zero-shot learning is an advanced technique in machine learning in which a model is able to perform tasks or recognize classes that it has never seen during training. This is achieved by using transfer knowledge and semantic relationships between known and unknown classes. Zero-shot learning significantly increases the flexibility and adaptability of AI systems, especially in scenarios where new categories or tasks occur frequently.