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AI will change the way we operate telecom networks. But what’s the best way to get there? How should we introduce AI to get the benefits it promises but avoid duplication, conflicts among different AI models, and undesired outcomes? How do we know AI models will deliver what we expect?
Per Kangru and Takai Eddine Kennouche at VIAVI Solutions shared their AIOps practical experience and vision for integrating AI and ML in network operations in an efficient and streamlined way while preserving the reliability and quality of experience that are non-negotiable.
Much of the discussion was about how a decomposable AI approach allows operators to use a common framework where data and models can be used for multiple tasks and thus reduce costs, duplication and energy consumption, thus strengthening the business case for AIOps to deliver a higher operational efficiency.
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