NVIDIA SoftBank are working on a pioneering platform for generative AI and 5G/6G applications that is based on the NVIDIA GH200 Grace Hopper Superchip and which SoftBank plans to roll out at new, distributed AI data centres across Japan.
Paving the way for the rapid, worldwide deployment of generative AI applications and services, SoftBank will build data centres that can, in collaboration with NVIDIA, host generative AI and wireless applications on a multi-tenant common server platform, which reduces costs and is more energy efficient.
The platform will use the new NVIDIA MGX reference architecture with Arm Neoverse-based GH200 Superchips and is expected to improve performance, scalability and resource utilisation of application workloads.
Junichi Miyakawa, president and CEO of SoftBank, said they will provide next-generation social infrastructure to support the super-digitalised society in Japan.
“Our collaboration with NVIDIA will help our infrastructure achieve a significantly higher performance with the utilisation of AI, including optimisation of the RAN,” said Miyakawa.
“We expect it can also help us reduce energy consumption and create a network of interconnected data centres that can be used to share resources and host a range of generative AI applications,” he added.
Jensen Huang, founder and CEO of NVIDIA, said demand for accelerated computing and generative AI is driving a fundamental change in the architecture of data centres.
“NVIDIA Grace Hopper is a revolutionary computing platform designed to process and scale-out generative AI services,” said Huang. “Like with other visionary initiatives in their past, SoftBank is leading the world to create a telecom network built to host generative AI services.”
The new data centres will be more evenly distributed across its footprint than those used in the past, and handle both AI and 5G workloads.
This will allow them to better operate at peak capacity with low latency and at substantially lower overall energy costs.
SoftBank is exploring creating 5G applications for autonomous driving, AI factories, augmented and virtual reality, computer vision and digital twins.
