Verizon and NVIDIA have developed a solution that enables AI applications to run over Verizon’s 5G private network with Mobile Edge Compute (MEC). according to a press release from the carrier. Verizon combines its network and MEC with NVIDIA’s AI Enterprise software platform and NVIDIA NIM microservices in the solution, which will be demonstrated by Verizon engineers in early 2025.
Half of all companies have adopted AI in at least one business function, with 71% planning to expand AI use in the near future, according to a McKinsey Global Survey on AI. But that success has led to a new challenge of handling all that data in a quick, efficient manner, according to IEEE.
“Billions of data bytes, generated at the network edge, put massive demands on data processing and structural optimization. Thus, there exists a strong demand to integrate edge computing and AI, which gives birth to edge intelligence,” writes IEEE Explore in a white paper.
The AI-powered private 5G platform stack is designed to be plug & play, helping third-party developers to accommodate future evolutions in AI computing and a variety of AI and connectivity applications. It can support multi-tenancy for multiple use cases or customers. The stack is being built to handle compute intensive apps including Generative AI Large Language Models and Vision Language Models, Video streaming, broadcast management, Computer Vision (CV), Augmented/Virtual/Extended Reality (AR/VR/XR), Autonomous Mobile Robot/ Automated Guided Vehicle (AMR/AGV) and IoT.
The inclusion of NVIDIA’s full stack AI platform into Verizon’s solution for running AI workloads on private 5G networks is a step forward in helping enterprises of all sizes reach their business objectives faster with AI, according to Ronnie Vasishta, senior vice president of telecom at NVIDIA.
“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,” Vasishta said. “It is estimated that 5G will power $12 trillion in global economic output by 2035, with AI-enabled devices playing a key role in transforming industries like healthcare, manufacturing and logistics. The need for networks to manage AI workloads has never been greater.”
