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Telecom AI: a guide for data teams

anastasiavalti

on 13 April 2021

Tags: 5g , AI/ML , data , machine learning , Telco , Telecommunications

This article is more than 3 years old.

Data is the new oil, and Artificial Intelligence is the way to monetize it. According to an IDC report, Artificial Intelligence (AI), alongside 5G, IoT, and cloud computing, is one of the technologies reshaping the telecom industry. From data-driven decisions to fully automated and self-healing networks, AI developments are accelerating innovation and driving costs of operation down.

However, while it is easier than ever to implement AI solutions in the telecom space, navigating a landscape of multiple databases, workflow engines and ML frameworks remains difficult.

Our latest telco whitepaper aims to provide a guide of existing use-cases for AI/ML in mobile networks. Download to discover:

  • Key questions to consider around core network, radio network, and enterprise IT parts before implementation, by use case
  • Recommendations of open source software components for building efficient solutions
  • Operation tips for AI in production

Download whitepaper

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What is Kubernetes?

Designed with economics in mind, Canonical's solutions for telecommunications ensure ROI, providing first class quality at the same time.
Save costs by operating your infrastructure and applications the smart way, ensuring full automation from day 0 to day N.

Learn more about Ubuntu for telco ›

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