AI and edge computing
This is yet another type of convergence, that of AI and edge computing. Certain applications, such as autonomous vehicles on the road, healthcare monitoring, and industrial robots in an assembly line, require immediate responses because they do real-time analysis and are faced with making quick decisions. This is where deploying AI algorithms at the edge comes in because it brings intelligent decision-making to the edge and reduces the need to transfer data to central servers.
We talked about deploying AI models to the edge, but the training and retraining of those models are done on the enterprise edge or the regional edge and typically not done at the far edge. Even the deployment and management of these AI models across a large number of edge devices has its own challenges of scale and consistency. Not all devices are created equal, and neither are the AI models. Solution architects must be cognizant of the form factor of the edge devices, the constraints...