Building the future of AI-native networks

Building the future of AI-native networks

https://www.nokia.com/blog/building-the-future-of-ai-native-networks/

Publish Date: 2026-05-14 10:17:00

Source Domain: www.nokia.com

• AI’s Impact on Networking: The evolution in networking over the past decades, including IPTV, high-speed internet, LTE/5G, Wi-Fi, and cloud architectures, has been evolutionary. However, AI represents a fundamental transformation that requires a new approach to network technology.

• Distinct Networking Requirements of AI: AI training relies on GPU clusters with high-traffic demand for lossless, deterministic networking, while AI inference requires ultra-low-latency networks for real-time responses. Inefficiencies in this new environment negatively impact app performance, training speeds, and overall costs.

• Nokia AI Networking Innovation Lab: This lab in Sunnyvale, California, focuses on creating scalable and performant networking solutions for AI through collaboration with AI ecosystem partners.

• Fundamental Rethinking of Network Architecture: AI necessitates a fundamental rethinking of network architecture to prioritize reliability, deterministic performance, multidimensional scalability, real-time operational awareness, and end-to-end validation.

• Three Pillars of the Lab: The lab operates on three pillars: technology innovation to experiment with new protocols and architectures, ecosystem collaboration to co-develop with AI technology partners, and real-world validation to ensure solutions work under AI conditions.

• Ecosystem Collaboration: The lab works closely with partners like AMD, NVIDIA, Lenovo, Supermicro, and Weka to develop optimized designs and integrations tailored to specific use cases.

• Focus on Differentiation: The lab targets areas where Nokia can offer unique capabilities to enhance AI-driven connectivity, aiming to drive industry standards and accelerate time to market.

• Future of AI-Native Networking: The lab is positioned to shape the future of AI-native networking, enabling scalable, efficient, and reliable networks that support the growing complexity of AI workloads.