Nokia Introduces AI-Powered Digital Twin for FTTH Networks

Oct 7, 2025
Nokia has launched new AI-powered tools and a digital twin for FTTH networks to enhance operational efficiency and network reliability, as announced in a press release.

Nokia has launched new AI-powered tools and a digital twin for FTTH networks to enhance operational efficiency and network reliability, announced in a press release. The new features, part of Nokia's Altiplano platform, allow operators to create a comprehensive digital twin of their FTTH infrastructure, providing a unified view of active and passive components.

These advancements aim to reduce operational costs and improve FTTH reliability by enabling operators to detect disruptions earlier and resolve incidents more efficiently. The digital twin capabilities are compatible with various inventory and geospatial software solutions and are effective in both greenfield and brownfield deployments.

Nokia's Altiplano platform also includes new applications like the Fiber Health Analyzer and Subscriber Line Identifier, which help operators monitor fiber link health, isolate faults, and update inventory in real-time. These tools are designed to improve service quality and operational efficiency, ultimately enhancing the subscriber experience.

Nokia Corporation continues to innovate in the telecommunications sector, providing solutions that integrate seamlessly into existing ecosystems and support the digital transformation of industries.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief or Industrial AI Weekly.

Also, consider following us on social media:

Free newsletter

Industrial AI Weekly

The latest advancements in smart manufacturing, predictive maintenance, AI-driven quality control, supply chain & more.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.