Verizon partners with Nvidia to enable AI workloads on 5G private networks for enterprises
Verizon has announced a collaboration with Nvidia to introduce a solution that supports artificial intelligence (AI) applications on Verizon’s 5G private networks with Mobile Edge Compute (MEC). This initiative aims to offer real-time, on-premises AI services to enterprise customers.
The solution integrates Verizon’s 5G private network and MEC capabilities with Nvidia’s AI Enterprise software and NIM microservices. The platform is designed to deliver low-latency, secure, and high-bandwidth AI applications. Demonstrations of the solution are expected to begin in early 2025 the company said.
Srini Kalapala, Senior Vice President of Technology and Product Development at Verizon, said, “We're leveraging our network's unique strengths including private networks and Verizon’s global industry leadership in private MEC, combined with Nvidia’s AI compute capabilities to enable real-time AI applications that require security, ultra-low latency, and high bandwidth.”
“Enterprises everywhere are racing to integrate AI solutions that bring new value to their employees, partners and customers, and can also help them operate with extreme efficiency,” said Ronnie Vasishta, senior vice president of telecom at Nvidia.
The infrastructure, co-developed by Verizon and Nvidia, supports a range of AI and connectivity applications. It is designed to be modular and scalable, accommodating various enterprise needs. Key features include multi-tenancy for different use cases, adaptability for future AI computing advancements, and support for deployment either on-site or remotely through portable private networks.
The platform is built to handle intensive applications such as generative AI language models, computer vision, video streaming, augmented and virtual reality, autonomous robots, and Internet of Things (IoT). Benefits of the solution include ultra-low latency, high reliability, enhanced security, and the ability to process AI workloads directly at the network edge.