Nokia launches AI networking lab to drive co-innovation with partners and accelerate next era of AI-native data center networking
Nokia launched its AI Networking Innovation Lab in Sunnyvale, California, to accelerate the development of AI-native data center networking solutions by collaborating with partners like AMD, Keysight, and Lenovo. The lab focuses on testing, validating, and integrating next-gen networking architectures for large-scale AI training and real-time inference, addressing the demands of AI workloads on infrastructure.
Nokia opened its AI Networking Innovation Lab in Sunnyvale, California, to drive co-innovation with global AI and cloud partners. The facility aims to design, test, and validate new data center networking architectures tailored for AI workloads, addressing the performance and scale challenges of large-scale AI training and real-time inference. The lab serves as a hub for Nokia Validated Designs and a collaborative space for partners to integrate commercial technologies and advance next-generation networking solutions. Early collaborators include AMD, Everpure, Keysight, Lenovo, Nscale, Supermicro, and Weka, working together to develop AI-ready infrastructure. The lab operates on three pillars: Technology Innovation, Ecosystem Collaboration, and Validation. It provides a space for partners to experiment with next-gen networking solutions, including protocols, switching silicon, congestion control, and real-time telemetry. Keysight, for example, has benchmarked AI networks under real-world conditions, optimizing AI transports like UEC and RoCEv2. Ecosystem Collaboration emphasizes joint testing for interoperability among silicon manufacturers, GPU developers, and cloud platforms. This ensures compatibility across hardware, software, and orchestration layers, aligning roadmaps for AI-ready solutions. AMD highlighted the importance of customer collaboration and an open ecosystem in accelerating AI innovation through partnerships like this lab. Validation ensures emerging technologies are rigorously tested before deployment, providing operators and hyperscalers with insights for confident, large-scale AI network adoption. The lab’s focus on real-world scenarios and commercial-grade testing positions it as a critical resource for shaping the future of AI-native data center networking.
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