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Nvidia’s new AI Aerial system has been launched to enable network optimization at scale unlocking opportunities in telecoms and commerce.
Cellular networks are no longer confined to solely providing voice and data services, with advanced infrastructure meeting contemporary needs including generative AI in smartphones, robotics, autonomous vehicles, 5G, and more.
Nvidia AI Aerial will also reportedly provide cost savings for the consumer, while opening up new revenue opportunities for providers.
The system is said to be the world’s first AI-RAN platform, using hardware and software to combine AI into radio access network (RAN) technology. The latter acts as a pillar of cellular communications, with the added functionality set to propel a range of AI-driven services.
The innovation could deliver substantial benefits via more efficient automation and data-driven insights to industries such as logistics and retail.
Robert Khachatryan of California-based Freight Right, a tech-focused international freight forwarder, told PYMNTS, “Telecom companies could see a significant increase in revenue from AI-driven network solutions, particularly in consumer-facing sectors like eCommerce.”
Continued Collaboration Between Nvidia and T-Mobile
The sense of opportunity was amplified by Nvidia founder and CEO Jensen Huang, during an appearance at T-Mobile’s Capital Markets Day.
Huang welcomed the potential for growth in telecoms as he explained how AI-RAN would let companies use AI models to optimize signal quality across diverse environments.
At the event in San Francisco, there was further discussion on the continued collaboration between Nvidia and T-Mobile, including the AI-RAN Innovation Center in conjunction with Ericsson and Nokia. It is designed to act as a catalyst to commercialize AI-RAN technologies.
Huang also made a point of stressing the importance of AI in making networks more energy-efficient. This will assist in the need for sustainable technologies, as demand for data and power continues to grow.
“We have to use AI to reduce energy consumption,” he stated.
“Everything that we accelerate, everything that we teach an AI model to do (we) will do a lot more energy efficiently.”
