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.
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…
