Focusing on the "Physical AI Era"! NVIDIA (NVDA.US) aims to reshape the communication ecosystem and collaborate with telecom giants to build AI-native 6G

The global publicly traded company NVIDIA (NVDA.US), known as the “AI Chip Superpower” with the highest market value, is quietly making big moves as a new wave of geopolitical conflicts in the Middle East erupts and military strikes extend beyond Iran and Israel. The chip giant is fully supporting a major effort to ensure that the upcoming 6G mobile intelligent network provides the most powerful platform for services, electronic devices, and a wide range of “physical AI” devices capable of utilizing cutting-edge artificial intelligence technology. Deep integration of 6G networks and AI has become an industry consensus. In the upcoming “Logistics AI Super Era,” NVIDIA’s AI+6G fusion technology is undoubtedly one of the most critical technological pillars of this era.

Undoubtedly, NVIDIA will play a central role in advancing 6G standards and architecture, co-building AI-native 6G platforms with telecom giants like Nokia, emphasizing AI capabilities integrated into wireless infrastructure. AI-native and software-defined networks will become hallmark features of 6G technology. This is not just a performance upgrade but a fundamental transformation of future communication systems. The “AI+6G” pathway is seen as a key underlying support for the physical AI era, providing foundational network capabilities for intelligent terminals, humanoid robots, autonomous driving, and other emerging applications.

It is understood that NVIDIA is working in deep collaboration with a group of international telecom giants including Nokia, SoftBank Group, and T-Mobile US Inc., aiming to build a sixth-generation network architecture based on new generations of computers and software. These technologies will leverage AI to safely and efficiently guide radio traffic.

In a statement on Sunday, NVIDIA said this change is urgent and necessary, as a large number of intelligent devices will connect to 6G networks in the future, and the demand for these high-performance devices will become more complex. The announcement was released just before the telecom industry conference opening in Barcelona. NVIDIA stated that current 5G networks are designed to connect people for voice and data retrieval but cannot support widespread use of AI micro-training/inference systems.

Ronnie Vasishta, NVIDIA’s head of telecom business and strategy, said, “Today’s networks are fundamentally unable to meet the needs of tomorrow’s use cases. Entering the AI era, everything will change. Network infrastructure will not only provide intelligence for smartphones but will offer intelligent services for all machines.” He added that telecom networks will need “thousands of times” more efficiency because there isn’t enough radio spectrum to support new uses.

The “AI+6G” Wave Is Coming, NVIDIA Vows to Lead

This chip manufacturer’s core infrastructure—AI training/inference systems and AI chips—is at the heart of the explosive growth of artificial intelligence. NVIDIA is working to carve out a new market and clear potential barriers.

At the GTC conference in Washington in late October 2025, Jensen Huang, CEO of NVIDIA known as the “Godfather of AI,” announced a $1 billion equity investment in Nokia. The two will jointly develop the AI-RAN product line and AI-native 6G network platform. NVIDIA also released the Aerial RAN Computer (ARC/ARC Pro) computing platform, aiming to make “AI on RAN” a new computational layer for communications infrastructure. NVIDIA plans to build a new cloud computing platform on top of 6G, demonstrating the enormous potential of ultra-fast AI, which will significantly drive technologies like robotic vision and autonomous driving.

In the previous wireless era—5G—NVIDIA’s absence was mainly because 5G architecture did not require large-scale AI integration at the foundational level, as traditional telecom vendors led the development. The primary goal of 5G was to increase bandwidth, reduce latency, and boost connection density for traditional services like voice, data, and video. Major players involved in 5G standardization and deployment included Nokia, Ericsson, Huawei, etc., who optimized networks based on traditional wireless PHY/MAC protocols. AI applications in 5G mainly focused on edge enhancement and non-critical functions, not requiring platforms with large-scale AI computing capabilities like NVIDIA.

In contrast, 6G planning from the outset is “AI-native,” demanding new levels of computing power. Unlike 5G, which emphasizes speed and low latency, 6G also requires networks to have intelligent sensing, real-time scheduling, dynamic spectrum management, and automatic optimization. In 6G architecture, AI will be deeply embedded from the radio access network (RAN) to the core network, enabling comprehensive intelligent optimization from terminals to the edge and core. This architecture is not just about adding AI applications but involves deep integration of AI with communication protocols, requiring massive training and inference capabilities to handle complex resource scheduling, channel prediction, and interference management in real time. Standardization bodies and industry alliances emphasize AI as a core design element.

To enable AI-native networks, powerful computing platforms are needed to support large-scale AI inference and training, with coordinated computing processes between the control plane and user plane. This aligns perfectly with NVIDIA’s strengths: its GPUs and AI computing platforms can perform massive parallel computations and unify network and AI loads through “Software Defined AI RAN,” improving spectral efficiency and adapting to complex, dynamic wireless environments.

Traditional telecom hardware—specialized ASICs, DSPs, etc.—are limited in large-scale AI computations. This is why NVIDIA and operators are collaborating to build open, AI-native 6G platforms. Industry collaborations and alliances clearly show NVIDIA’s involvement with over 130 industry partners pushing AI RAN innovation, establishing its role as a key technology hub in the AI 6G ecosystem.

NVIDIA has already provided the most advanced chips, computing components, and software versions for high-performance network infrastructure, aiming to expand this business significantly. Recently, the chip giant has been promoting cutting-edge AI technology into broader fields—such as robotics and autonomous vehicles, termed “physical AI”—to continue expanding demand and seek new growth points outside data center markets. Without wireless networks capable of supporting AI-level massive traffic, NVIDIA’s vision of a world filled with humanoid robots and autonomous vehicles in “physical AI” could be delayed.

Approximately every decade, telecom shifts to a new wireless technology generation, the next “G.” During the development of new hardware and software standards, telecom companies often lead industry direction through alliances that favor their product lines. However, this approach has inconsistent results and can cause delays or incompatibilities due to competitive efforts.

NVIDIA believes that new devices and software must be fundamentally open. Instead of using closed, custom hardware devices, radio transmission and reception equipment should be controlled by updatable software and run on more general-purpose computing systems. Data traffic should be guided by AI software and expanding AI infrastructure capable of handling rapidly changing patterns and priorities—something currently unachievable, NVIDIA states.

In such an environment, the telecom industry will be more open to new vendors, including startups that could quickly reach a billion-dollar valuation, according to Vasishta. He said, “This will be how a new telecom unicorn is born.” He added that over the past decade, few new companies have entered the industry.

Physical AI Era: “AI+6G” Is Indispensable

According to NVIDIA CEO Jensen Huang, “Physical AI” emphasizes enabling robots/autonomous systems to perceive, reason, and perform a full range of actions in the real world. An era where “Physical AI” assists human civilization is imminent. “Physical AI” focuses on enabling robots/autonomous systems to perceive, reason, and act in the real world—these three capabilities are key tools to advance models from “just conversation” to “physical world work.”

The integration of AI and 6G is not just an application overlay but a fundamental transformation of network architecture. Future 6G networks will be more than “faster connections”; they will become intelligent engines capable of real-time analysis of terminal, environmental, and user data, automatically optimizing network resource allocation and providing integrated end-edge-cloud intelligent services. AI will play a core role in spectrum sensing, resource allocation, network slicing, and edge inference. The most critical aspect is that AI-enabled networks will support large-scale, complex AI workloads such as IoT, autonomous driving, robotics, and smart spaces. These use cases, which are more like add-ons in 5G, will become essential features of 6G.

One of the core features of 6G planning is AI-native networks, which embed AI capabilities into the entire communication infrastructure—from RAN to the core—enabling self-optimization, intelligent spectrum scheduling, and real-time response to billions of terminals. The vision of 6G is to realize “Ubiquitous Intelligent Connectivity,” deeply integrating AI and communications so that the network itself can perceive, predict, and self-optimize. This evolution means the network will not only transmit data but also perform massive AI inference and real-time learning workloads—such as intelligent spectrum management, edge inference, and real-time signal optimization—requiring robust AI computing infrastructure and flexible software platforms.

NVIDIA’s AI platforms (like NVIDIA Aerial and AI RAN architecture) provide high-performance, programmable, AI-accelerated infrastructure for building software-defined networks, enabling the network itself to possess large-scale AI computing and inference capabilities. This is precisely what 6G demands for future high-speed, intelligent, scalable communication.

In the so-called “Physical AI Era,” a vast number of terminals—such as intelligent robots, autonomous vehicles, and smart industrial devices—will seamlessly connect and generate enormous AI workloads. This requires not only efficient connectivity but also edge AI inference, distributed machine learning, and network-aware intelligence.

To support these cutting-edge functions, networks need to have general AI computing capabilities deeply integrated with wireless protocol stacks. NVIDIA’s leadership in AI chips, accelerated computing architectures, and development tools like Aerial CUDA Accelerated RAN, Omniverse digital twin simulation platform, and AI radio frameworks provide the core foundation for building scalable, open, AI-native wireless networks. Although the physical AI ecosystem will involve multiple participants in the future, NVIDIA’s AI+6G fusion technology is undoubtedly one of the most critical technological pillars of this era.