The notion of the intelligent edge has been around for a few years. It refers to placing processing out on edge devices to avoid sending data all the way back to the centralized server, typically existing on public clouds.
While not always needed, the intelligent edge is able to leverage machine learning technology at the edge, moving knowledge building away from centralized processing and storage. Applications vary, from factory robotics to automobiles to on-premises edge systems residing in traditional data centers. It’s good in any situation where it makes sense to do the processing as close to the data source as you can get.
We’ve wrestled with this type of architectural problem for many years. With any distributed system, including cloud computing, you have to consider the trade-off of process and storage placement on different physical or virtual devices. The intelligent edge is no different.