Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved by leveraging existing knowledge and transferring it to unseen classes. Zero-Shot Learning is useful when acquiring labelled data for all possible classes is challenging or unfeasible.
Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…