Need of Edge AI Hardware
The edge AI provides efficient as well as powerful computing solutions which can be used for edge computing environments. Earlier, when people use traditional cloud based architectures they were very powerful but they had to face various challenges for example, low latency, low bandwidth as well as privacy concerns but when we deploy systems on edge AI and it’s hardwares, there’s little to no latency and there are no concerns regarding privacy. in low latency or latency sensitive applications like the autonomous vehicles as well as industrial hardware it becomes important to use edge AI because it offers low latency and it is very efficient.
Edge AI for Network Traffic Optimization
The edge AI for the network traffic algorithm refers to the various applications of the artificial intelligence and its algorithms and techniques at the edge of a network which are used in order to optimise and manage the network and its traffic more efficiently, So in this article we will understand what is edge AI, applications, advantages and disadvantages of using edge AI.
Edge AI means that we deploy AI models directly onto the network devices. for example, the routers switches or even the edge computing devices we deploy these in order to perform various tasks such as traffic prediction analysis as well as optimisation and this happens in the real time without having the need to send the data to a cloud or some centralised server.