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Nvidia, South Korean chip startup Rebellions, and telecommunications provider SK Telecom are partnering to develop sovereign artificial intelligence infrastructure. Backed by South Korea's Ministry of Science and ICT, the plan centers on Rebellions' upcoming R200 neural processing unit integrated into Nvidia's MGX rack architecture using NVLink Fusion interconnects. The companies expect the R200 systems to be ready for deployment in SK Telecom's AI data centers in 2028. [1][2]
The planned setup splits AI inference tasks across architectures to improve throughput and power efficiency. Nvidia graphics processing units will handle the compute-heavy prompt prefill phase, while Rebellions' R200 chips will take over the memory-bound token decoding phase across the high-speed NVLink fabric. The companies have not yet released technical specifications, memory configurations, power ratings, or pricing for the R200, which follows Rebellions' current Rebel100 silicon. [1]
SK Telecom plans to use the infrastructure to run its proprietary foundation models, including A.X K2, along with services tied to the South Korean government's AI for All project. The deployment forms part of a broader sovereign AI initiative supported by the country's technology ministry to tailor infrastructure, models, and services to domestic industrial and language needs. [1][2]
NVIDIA and Korea’s Ministry of Science and ICT (MSIT) are expanding their collaboration across the country’s sovereign AI ecosystem, from AI semiconductors and data center infrastructure to talent, startups, models, agents and security. The collaboration lays the groundwork for Korean NPU and XPU companies to explore participation in the NVIDIA NVLink Fusion ecosystem, and includes…
via NVIDIA
NVIDIA, Rebellions, and SK Telecom announced a plan to build sovereign AI inference infrastructure in South Korea around Rebellions’ next-generation R200 neural processing unit, connected inside the rack with NVIDIA NVLink Fusion and built on the NVIDIA MGX rack architecture. SK Telecom will deploy the systems in its AI data center alongside its models and
via StorageReview