Edge Computing brings computing resources closer to the source of data generation, reducing latency and improving response times. By processing and analysing data locally on edge devices such as IoT Devices or Edge Servers, businesses can handle real-time applications and achieve faster data insights. Edge Computing is especially valuable for AI applications that require low-latency and efficient use of network bandwidth.
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…