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Artificial Intelligence For Media Operations Why AI algorithms will become a must for every network management system

机译:人工智能用于媒体运营为什么AI算法将成为每个网络管理系统的必备条件

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Artificial intelligence already has a big impact on a lot of different segments in the media industry. With the broadcast industry moving to all-IP and data center deployments those environments are more agile and complex than ever before. With fast-evolving technologies and cycles, ever more mission critical systems and constantly changing operational practices and devops style operations, traditional network management systems (NMS) and their paradigms don't fit the bill anymore. This paper explores why machine-learning algorithms must find their way into network monitoring and management solutions to orchestrate a modern media data center dynamically and in a proactive way. The foundation for an AI-driven NMS platform is a solid big data storage architecture; a lack of profound data and data hygiene is often one of the biggest obstacles to successfully deploy big data projects. As in today's all-IP environments nothing is static anymore, an AI entity must be highly intelligent. Unsupervised learning is key to automatically adapt to changing environments. Augmented operation and a zero-configuration and zero-maintenance approach will be crucial to successfully deploy the right management strategy.
机译:人工智能已经对媒体行业的许多不同领域产生了巨大影响。随着广播行业转向全IP和数据中心部署,这些环境比以往任何时候都更加敏捷和复杂。随着技术和周期的飞速发展,越来越多的关键任务系统以及不断变化的操作实践和开发人员风格的操作,传统的网络管理系统(NMS)及其范例已不再适用。本文探讨了为什么机器学习算法必须找到进入网络监视和管理解决方案的途径,才能以主动方式动态地协调现代媒体数据中心。 AI驱动的NMS平台的基础是坚实的大数据存储架构。缺乏深刻的数据和数据卫生通常是成功部署大数据项目的最大障碍之一。就像在当今的全IP环境中一样,没有什么是静态的,因此AI实体必须高度智能。无监督学习是自动适应不断变化的环境的关键。增强的操作以及零配置和零维护方法对于成功部署正确的管理策略至关重要。

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