A machine learning approach where models perform tasks without having seen labeled examples for those tasks during training.
More about Zero-Shot Learning
Zero-Shot Learning allows AI models to handle tasks they haven’t been explicitly trained on by leveraging pre-trained knowledge from large datasets. This capability is achieved through transfer learning, enabling models like GPT or BERT to generalize to new domains or tasks.
Zero-shot learning is integral to systems like retrieval-augmented generation (RAG) and knowledge retrieval, where understanding and processing unseen queries is critical.
