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 4 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
Enterprise AI, simplified
AI doesn’t have to be difficult. Accelerate innovation with an end-to-end stack that delivers all the open source tooling you need for the entire AI/ML lifecycle.
Newsletter signup
Related posts
Canonical Kubernetes officially included in Sylva 1.5
Sylva 1.5 becomes the first release to include Kubernetes 1.32, bringing the latest open source cloud-native capabilities to the European telecommunications...
Let’s meet at AI4 and talk about AI infrastructure with open source
Date: 11 – 13 August 2025 Booth: 353 Book a meeting You know the old saying: what happens in Vegas… transforms your AI journey with trusted open source. On...
Experience Edge AI use cases with Canonical at Mobile World Congress Barcelona 2025
Artificial Intelligence and Machine Learning (AI/ML) are increasingly driving change in telecommunications. Increased adoption is building organizational...