Functional overview of integration of AIML with 5G and beyond the network

4 G/LTE mobile networks resolved this issue. Strong physical layer and adaptable network design enable high-capacity mobile broadband Internet. Despite this, the prevalence of bandwidth-intensive technologies like virtual reality, augmented reality, and others has grown. In addition, the rising popularity of new services places astrain on mobile infrastructure. Applications requiring high availability and low latency, such Internet-of-Vehicles or communications between vehicles (IoV). With the advent of the new 5G technology with its massive MIMO radio interface, these problems are no longer a concern. Networks protected by software-defined networking (SDN)and NFV have added a new level of flexibility that allows network operators to serve services with very high requirements across several industries. Network operators must increase and diversify their intelligence to fully comprehend the operational environment, user behaviours, and user demands. A further goal is to become(self-) networkable proactively and effectively. This chapter will look at how AI may help us in the modern world. Next-generation mobile networks that are both efficient and adaptable may benefit greatly from machine learning in the 5G era and beyond. The evolution of AI and ML in network applications.