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Event File AI NVIDIA

LITEON and NVIDIA Showcase AI-RAN Technology and 5G Integration at MWC 2026

2 reports · First detected 2026-02-25 · Last active 2026-03-02

LITEON Technology has long invested in 5G communications equipment, while AI-RAN brings artificial intelligence computing into radio access networks and uses a software-defined architecture to allocate spectrum, computing capacity and base-station resources. The partnership combines LITEON’s telecommunications hardware with NVIDIA’s computing platform, laying the groundwork for carriers to move from 5G toward commercially viable, AI-native 6G.

At MWC 2026, LITEON and NVIDIA showcased an AI-RAN platform and applications integrating AI with 5G. The technologies have already been deployed in Europe, Taiwan and South Korea. NVIDIA has also recently joined global telecommunications operators in advancing AI-native 6G, indicating that AI-RAN is moving from field validation toward commercial deployment. The companies have not disclosed the value of the partnership or the number of deployment sites.

All Coverage

2 original reports
ITHOME.COM.TW 2026-03-02
Nvidia攜全球電信商布局AI原生6G，AI-RAN邁向商轉
FINANCE.TECHNEWS.TW 2026-02-24
光寶攜手輝達於 MWC 展 AI-RAN 技術，聚焦 AI 與 5G 應用整合

The Backstory

The history behind this event
LITEON, Singapore's SUTD Showcase AI-RAN Solution to Advance Commercialization2026-06-04 · 1 reports · similarity 0.83

AI-RAN integrates mobile base stations with AI computing resources, allowing network and edge-computing capacity to be allocated according to service demand. LITEON Technology is working with the Singapore University of Technology and Design (SUTD) and NeuroRAN on a solution using NVIDIA's AI computing architecture. The partnership targets smart-city and industrial-automation deployments, while its commercialization progress could also shape the telecom-equipment and edge AI markets.

As of July 20, 2026, the partners had demonstrated an AI-RAN solution combining a 5G network with the NVIDIA platform. Its core technology can dynamically partition AI models and adjust computing configurations according to edge-node workloads, improving resource utilization and shortening application deployment times. The team has not yet announced a formal commercial launch schedule, customer list, investment amount or performance data.

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