Zero-shot learning

Zero-shot learning is an innovative approach in the field of artificial intelligence, in which a model is able to complete tasks without first being explicitly trained with examples of these tasks. This is achieved by using transfer knowledge, in which the model draws on knowledge already acquired to solve new problems. Zero-shot learning is particularly useful in situations where it is difficult or time-consuming to collect large amounts of training data. By being able to learn without previous examples, Zero-Shot Learning opens up new opportunities in the development of AI applications and can significantly increase the efficiency and flexibility of AI systems.