![]() ![]() Many ML algorithms and models thrive on data in large quantities and these algorithms and models in-turn underpin the AI required to automate processes. Both supervised and unsupervised ML are used within the solution today along with a branch of AI called evolutionary computing. These elements have been key components of the NITRO Mobile evolutionary capabilities. The concepts of Machine Learning (ML) and Artificial Intelligence (AI) are the cornerstone of Automation. ![]() Indeed, the openness and flexibility offered through a cloud-based approach in a multi-vendor environment can only be fully realized with automation. With the dynamic nature of cloud-based networks, the number of parameters involved and often with support of several disparate verticals, many would argue some level of Automation is a must. The complexity of 5G and Virtualization demands a level of automation allowing engineers to manage other aspects of network operations and planning. Automation takes the principles of Management, Assurance, and Optimization and encodes them in a process that can be performed automatically with minimal or even no human intervention.
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