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 model updates are exchanged, ensuring data privacy and security. Federated Learning enables businesses to harness the collective intelligence of distributed devices while maintaining data confidentiality.
Instance-Based Learning is an AI approach where models make predictions based on similarity to previously seen examples. Instead of generalising from a predefined set…