Edge computing is just cloud computing but it happens at the "edge" of the network.
Well one application of edge computing would be to use ML/AI to do some task. For example imagine you have your phone and you take a photo with a cancer app. Your phone doesn't have enough compute power to run a very good ML model on it so instead the app would upload the image to the cloud to do the analysis. To take the app run fast you wound want the computation to happen on the edge of the network so you have the smallest latency possible giving a better user experience.
Thanks @kmather73 for your example. One of the possible uses I red about was using ML to decide when to do the computation in the cloud and when to do it in the device. Do you know a bit about this? Thanks again for your explanation! The concept seems clearer now
Well one application of edge computing would be to use ML/AI to do some task. For example imagine you have your phone and you take a photo with a cancer app. Your phone doesn't have enough compute power to run a very good ML model on it so instead the app would upload the image to the cloud to do the analysis. To take the app run fast you wound want the computation to happen on the edge of the network so you have the smallest latency possible giving a better user experience.