Why do devices run edge ai rather than cloud-only models?

Example Concept: Edge AI involves deploying machine learning models directly on IoT devices or gateways, enabling them to analyze and act on data at the source. This reduces the need to transmit large volumes of data to the cloud, thus decreasing latency and bandwidth usage, and enhancing privacy by keeping sensitive data local. It is especially useful in scenarios requiring real-time processing, such as predictive maintenance and anomaly detection in industrial IoT systems.