A comprehensive look at the key points of Jensen Huang's speech at NVIDIA GTC: heavyweight collaborations such as 6G, NVQLink integrating quantum computing and supercomputing, refuting the AI bubble, and Blackwell made in the USA

On Tuesday, the 28th, Eastern Time, NVIDIA CEO Jensen Huang delivered a keynote speech at this year's second GTC conference held in Washington, focusing on technological breakthroughs in the fields of 6G, AI, quantum computing, and robotics. Huang emphasized in his speech that as Moore's Law becomes ineffective, accelerated computing and GPU technology have become the core driving forces behind technological advancement.

In terms of the integration of AI and 6G technology, NVIDIA announced a strategic partnership with Nokia, investing $1 billion to acquire shares in Nokia to jointly promote an AI-native 6G network platform. In the supercomputing sector, NVIDIA launched the NVQLink technology, which integrates AI supercomputing and quantum computing, connecting quantum processors with GPU supercomputers, and has gained support from 17 quantum computing companies. NVIDIA also announced a collaboration with the U.S. Department of Energy to build the department's largest AI supercomputer. Regarding AI factories, NVIDIA will launch the Bluefield-4 processor to support AI factory operations.

Additionally, NVIDIA has further fueled the excitement for autonomous taxi services, announcing partnerships with ride-sharing pioneer Uber and Chrysler's parent company Stellantis. Uber plans to deploy 100,000 Robotaxi service vehicles based on NVIDIA technology starting in 2027.

NVIDIA has also partnered with AI star Palantir and pharmaceutical giant Eli Lilly to deeply integrate its GPU computing capabilities with enterprise data platforms and pharmaceutical research and development, aiming to drive AI from concept to practical application. These two collaborations focus on enterprise operational intelligence and drug development, marking an acceleration in the commercialization process of AI technology in complex industry scenarios.

Huang stated in his speech, "AI is the most powerful technology of our time, and science is its greatest frontier." The partnerships announced on Tuesday signify NVIDIA's strategic transformation from a chip manufacturer to a full-stack AI infrastructure provider.

Huang explicitly refuted the notion of an AI bubble, stating, "I don't think we are in an AI bubble. We are using all these different AI models—we are using a lot of services and are happy to pay for them." His core argument is that AI models are now powerful enough that customers are willing to pay for them, which in turn will justify the expensive construction of computing infrastructure.

Surge in Chip Shipments and Rapid Capacity Expansion

Huang revealed that NVIDIA's fastest AI chip, the Blackwell GPU, has achieved full production in Arizona. This means that the Blackwell chips, which were previously only produced in Taiwan, can now be manufactured in the United States for the first time.

Huang disclosed astonishing data regarding NVIDIA's chip shipments. He stated that NVIDIA expects to ship 20 million Blackwell chips. In contrast, the previous generation Hopper architecture chips shipped only 4 million units over their entire lifecycle.

Huang also mentioned that 6 million Blackwell GPUs have been shipped over the past four quarters, with demand remaining strong. NVIDIA expects that Blackwell and the upcoming Rubin chip next year will collectively generate $500 billion in GPU sales over five quartersEarlier this month, NVIDIA and TSMC announced that the first batch of Blackwell wafers has been produced at the factory in Phoenix, Arizona. NVIDIA stated in a video that systems based on Blackwell will also be assembled in the United States.

NVIDIA Partners with Nokia to Lay Out 6G Network

Jensen Huang introduced that NVIDIA will collaborate with Nokia to launch the Aerial RAN Computer (ARC) to assist in the transformation of the 6G network. NVIDIA and Nokia will develop an AI platform for 6G communication technology.

How will 6G integrate with AI? In addition to AI learning and enhancing 6G spectrum efficiency, we will also see AI-powered wireless access network (RAN) products, known as "AI on RAN." This means that, under the current state of the internet, much of the data runs on Amazon Web Services (AWS), but NVIDIA aims to build a cloud computing platform on top of 6G connectivity. This showcases the potential of ultra-fast AI, which can power technologies such as autonomous vehicles.

NVIDIA and Nokia announced on Tuesday the establishment of a strategic partnership to add NVIDIA-driven commercial-grade AI-RAN products to Nokia's RAN product portfolio, enabling communication service providers to launch AI-native 5G-Advanced and 6G networks on the NVIDIA platform.

NVIDIA will launch the Aerial RAN Computer Pro computing platform for 6G networks, and Nokia will expand its RAN product portfolio based on this to introduce new AI-RAN products. NVIDIA will also make a $1 billion equity investment in Nokia at a subscription price of $6.01 per share.

Analyst firm Omdia predicts that by 2030, the AI-RAN market size is expected to exceed $200 billion cumulatively. The collaboration between NVIDIA and Nokia will provide distributed edge AI inference capabilities, opening up new high-growth areas for telecom operators.

T-Mobile US will collaborate with Nokia and NVIDIA to promote the testing and development of AI-RAN technology, integrating the technology into its 6G development process. The trials are expected to begin in 2026, focusing on validating performance and efficiency improvements for customers. This technology will support AI-native devices such as autonomous vehicles, drones, and augmented reality and virtual reality glasses.

NVQLink Connects Quantum Computing with GPU Systems

Currently, various quantum computing technologies, while powerful, are sensitive to environmental noise and have limited application ranges. This is where GPU-based supercomputers come into play, as they can alleviate the burden on quantum processors. Jensen Huang mentioned on Tuesday that NVIDIA has built the open-source system architecture NVQLink based on its open-source quantum development platform CUDA-Q core.

Jensen Huang stated that he expects quantum computing to require support from traditional processors in addition to new technologies, and NVIDIA will help achieve this goal. "We now realize that connecting quantum computers directly to GPU supercomputers is crucial. This is the future of quantum computing."

NVQLink is a new high-speed interconnect technology that connects quantum processors with GPUs and CPUs. It is not intended to replace quantum computers but to work alongside them to accelerate quantum computing.

Huang said that NVQLink technology will help with error correction while calibrating which AI algorithms should be used on GPUs and quantum processors. He revealed that 17 quantum computing companies have committed to supporting NVQLink. "The industry's support is incredible. Quantum computing will not replace traditional systems; they will work together."

"It (NVQLink) can not only correct errors for today's quantum bits but also for future quantum bits. We will scale these quantum computers from hundreds of quantum bits now to tens of thousands of quantum bits, and even hundreds of thousands of quantum bits in the future."

NVIDIA stated that NVQLink technology has received support from 17 quantum processor manufacturers and 5 controller manufacturers, including Alice & Bob, Atom Computing, IonQ, IQM Quantum Computers, Quantinuum, and Rigetti. Nine national laboratories led by the U.S. Department of Energy will use NVQLink to drive breakthroughs in quantum computing, including Brookhaven National Laboratory, Fermi National Laboratory, and Los Alamos National Laboratory (LANL).

NVIDIA announced that developers can access NVQLink through the CUDA-Q software platform to create and test applications that seamlessly call CPU, GPU, and quantum processors.

NVIDIA and Oracle Build the Largest AI Supercomputer for the U.S. Department of Energy

Huang stated that NVIDIA will collaborate with the U.S. Department of Energy to build seven new supercomputers. They will be deployed at the Argonne National Laboratory (ANL) and Los Alamos National Laboratory (LANL).

NVIDIA announced a partnership with Oracle to construct the department's largest AI supercomputer, the Solstice system, which will be equipped with a record-breaking 100,000 NVIDIA Blackwell GPUs. Another system, named Equinox, will contain 10,000 Blackwell GPUs and is expected to be operational in the first half of 2026.

Both systems will be interconnected through NVIDIA's network, providing a total of 2,200 exaflops of AI performance. These supercomputers will enable scientists and researchers to develop and train new cutting-edge models and AI inference models using NVIDIA's Megatron-Core library and scale them with the TensorRT inference software stack.

Energy Secretary Chris Wright stated, "Maintaining America's leadership in high-performance computing requires us to build a bridge to the next computing era: accelerating quantum supercomputing. The deep collaboration between our national laboratories, startups, and industry partners like NVIDIA is critical to this mission.""

Paul K. Kearns, director of Argonne National Laboratory, stated that these systems will seamlessly connect with the Department of Energy's cutting-edge experimental facilities (such as the Advanced Photon Source), enabling scientists to address the nation's most pressing challenges through scientific discovery.

BlueField-4 Drives AI Factory Infrastructure Upgrade

Jensen Huang believes that agent-based AI is no longer just a tool, but an assistant for all human work. The opportunities brought by AI are "countless." NVIDIA's plan is to build factories dedicated to AI, filled with chips.

On Tuesday, NVIDIA announced the launch of the BlueField-4 processor, which supports AI factory operating systems.

NVIDIA's BlueField-4 data processing unit supports 800Gb/s throughput, providing breakthrough acceleration for gigabit-level AI infrastructure. This platform combines NVIDIA Grace CPU and ConnectX-9 networking technology, with computing power six times that of the previous generation BlueField-3, and the scale of AI factories supported is three times larger than BlueField-3.

BlueField-4 is designed for a new class of AI storage platforms, laying the foundation for efficient data processing and large-scale breakthrough performance in AI data pipelines. The platform supports multi-tenant networking, fast data access, AI runtime security, and cloud elasticity, with native support for NVIDIA DOCA microservices.

NVIDIA stated that several industry leaders plan to adopt BlueField-4 technology. Companies in the server and storage sectors include Cisco, DDN, Dell Technologies, HPE, IBM, Lenovo, Supermicro, VAST Data, and WEKA. Companies in the cybersecurity sector include Armis, Check Point, Cisco, F5, Forescout, Palo Alto Networks, and Trend Micro.

Additionally, cloud and AI service providers such as Akamai, CoreWeave, Crusoe, Lambda, Oracle, Together.ai, and xAI are building solutions based on NVIDIA DOCA microservices to accelerate multi-tenant networking, enhance data mobility, and improve the security of AI factories and supercomputing clouds.

NVIDIA BlueField-4 is expected to launch an early version in 2026 as part of the Vera Rubin platform.

NVIDIA Partners with CrowdStrike for AI Cybersecurity Development

Jensen Huang stated that NVIDIA will collaborate with cybersecurity company CrowdStrike on AI cybersecurity models.

NVIDIA announced a strategic partnership with CrowdStrike to provide NVIDIA AI computing services on the CrowdStrike Falcon XDR platform. This collaboration combines Falcon platform data with NVIDIA GPU-optimized AI pipelines and software (including the new NVIDIA NIM microservices), enabling customers to create customized security generative AI modelsAccording to the 2024 CrowdStrike Global Threat Report, the average breach time has dropped to 62 minutes, with the fastest recorded attack just over 2 minutes. As modern attacks become faster and more complex, organizations need AI-driven security technologies to gain the necessary speed and automation capabilities.

Jensen Huang stated, "Cybersecurity is fundamentally a data problem—the more data a business can process, the more events it can detect and respond to. Combining NVIDIA's accelerated computing and generative AI with CrowdStrike's cybersecurity can provide businesses with unprecedented threat visibility."

CrowdStrike will leverage NVIDIA's accelerated computing, NVIDIA Morpheus, and NIM microservices to bring custom LLM-driven applications to enterprises. By integrating the unique contextual data from the Falcon platform, customers will be able to address new use cases in specific areas, including processing petabyte-scale logs to improve threat hunting, detecting supply chain attacks, identifying user behavior anomalies, and proactively defending against emerging vulnerabilities.

NVIDIA's New Autonomous Driving Development Platform Helps Uber Deploy Robotaxi Fleet

Jensen Huang introduced that NVIDIA's end-to-end autonomous driving platform, DRIVE Hyperion, is ready to launch vehicles providing Robotaxi services. Global automakers, including Stellantis, Lucid, and Mercedes-Benz, will utilize NVIDIA's new technology platform, DRIVE AGX Hyperion 10 architecture, to accelerate the development of autonomous driving technology.

NVIDIA announced a partnership with Uber to expand the world's largest Level 4 mobile network using the next-generation NVIDIA DRIVE AGX Hyperion 10 autonomous driving development platform and DRIVE AV software. NVIDIA will support Uber in gradually scaling its global autonomous driving fleet to 100,000 vehicles starting in 2027.

DRIVE AGX Hyperion 10 is a reference-grade production computer and sensor architecture that enables any vehicle to achieve Level 4 readiness. This platform allows automakers to build cars, trucks, and vans equipped with validated hardware and sensors that can host any compatible autonomous driving software.

Jensen Huang stated, "Robotaxis mark the beginning of a transformation in global transportation—making it safer, cleaner, and more efficient. Together with Uber, we are creating a framework for the entire industry to deploy autonomous fleets at scale." Uber CEO Dara Khosrowshahi stated, "NVIDIA is a pillar of the AI era, and we are now fully leveraging this innovation to unleash Level 4 autonomous driving capabilities at a massive scale.""Stellantis is developing an AV-Ready platform specifically optimized to support Level 4 capabilities and meet the requirements for autonomous taxis. These platforms will integrate NVIDIA's full-stack AI technology, further expanding connectivity with Uber's global mobility ecosystem.

Uber stated that Stellantis will be one of the first manufacturers to provide Robotaxi vehicles, which will supply at least 5,000 NVIDIA-powered Robotaxi vehicles for Uber's operations in the U.S. and internationally. Uber will be responsible for the end-to-end fleet operations of the vehicles, including remote assistance, charging, cleaning, maintenance, and customer support.

Stellantis announced that it will collaborate with Foxconn on hardware and system integration, with production plans set to launch in 2028. Operations will first be conducted in the U.S. in partnership with Uber. Stellantis expects pilot projects and testing to gradually unfold in the coming years.

Lucid is advancing Level 4 autonomous driving capabilities for its next-generation passenger vehicles, using NVIDIA's full-stack AV software on the DRIVE Hyperion platform to deliver the first batch of Level 4 autonomous vehicles to customers. Mercedes-Benz is testing future collaborations based on its proprietary operating system MB.OS and DRIVE AGX Hyperion, with the new S-Class model set to offer an exceptional Level 4 luxury driving experience.

NVIDIA and Uber will continue to support and accelerate the development of software stacks on NVIDIA's DRIVE Level 4 platform with global partners, including Avride, May Mobility, Momenta, Nuro, Pony.ai, Wayve, and WeRide. In the trucking sector, Aurora, Volvo Autonomous Solutions, and Waabi are developing Level 4 autonomous trucks powered by the NVIDIA DRIVE platform.

NVIDIA and Palantir Build Operational AI Technology Stack; Lowe's First to Apply Supply Chain Optimization Solutions

The core of NVIDIA's collaboration with Palantir is to integrate NVIDIA's GPU-accelerated computing, open-source models, and data processing capabilities into Palantir's AI Platform (AIP) Ontology system. Ontology creates a digital twin of the enterprise by organizing complex data and logic into interconnected virtual objects, links, and actions, providing the foundation for AI-driven business process automation.

Jensen Huang stated, "Palantir and NVIDIA share a common vision: to put AI into action and transform enterprise data into decision intelligence. By combining Palantir's powerful AI-driven platform with NVIDIA's CUDA-X accelerated computing and Nemotron open-source AI models, we are building the next-generation engine to power AI-specialized applications and agents that run the world's most complex industrial and operational pipelines."

On the technical side, customers can use Ontology to process data with NVIDIA's CUDA-X data science library, combined with NVIDIA's accelerated computing, to drive real-time AI decision-making for complex business-critical workflows. The NVIDIA AI Enterprise platform (including cuOpt decision optimization software) will support enterprises in dynamic supply chain managementNVIDIA's Nemotron inference model and NeMo Retriever open-source model will help enterprises quickly build AI agents powered by information from Ontology.

Palantir co-founder and CEO Alex Karp stated, "Palantir focuses on deploying AI that can deliver asymmetric value to customers immediately. We are honored to collaborate with NVIDIA to integrate our AI-driven decision intelligence system with the world's most advanced AI infrastructure."

Retailer Lowe's is one of the first companies to adopt the integrated technology stack from Palantir and NVIDIA, creating a digital twin of its global supply chain network for dynamic and continuous AI optimization. This technology aims to enhance supply chain agility while improving cost savings and customer satisfaction.

Lowe's Chief Digital and Information Officer Seemantini Godbole said, "Modern supply chains are extremely complex dynamic systems, and AI is crucial for helping Lowe's quickly adapt and optimize under changing conditions. Even small changes in demand can create a ripple effect throughout the global network. By combining Palantir technology with NVIDIA AI, Lowe's is reimagining retail logistics, enabling us to serve our customers better every day."

NVIDIA and Palantir also plan to introduce NVIDIA's Blackwell architecture into Palantir AIP to accelerate the end-to-end AI pipeline from data processing and analysis to model development, fine-tuning, and production AI. Enterprises will be able to run AIP in NVIDIA's AI factory for optimized acceleration. Palantir AIP will also be supported in NVIDIA's newly launched government AI factory reference design.

Eli Lilly Builds the Strongest Supercomputer in Pharma Powered by Over 1,000 Blackwell Ultra GPUs

Eli Lilly's collaboration with NVIDIA will build a supercomputer powered by over 1,000 Blackwell Ultra GPUs, which will be connected through a unified high-speed network. This supercomputer will power the AI factory, a dedicated computing infrastructure for the large-scale development, training, and deployment of AI models for drug discovery and development.

Eli Lilly's Chief Information and Digital Officer Diogo Rau stated that it typically takes about 10 years from the first human drug trial to product launch. The company expects to complete the construction of the supercomputer and AI factory by December and go live in January next year. However, these new tools may not yield significant returns for Eli Lilly and other pharmaceutical companies until the end of 2030. Rau said, "What we are discussing now in terms of discoveries made with this computing power will truly show benefits by 2030."

Eli Lilly's Chief AI Officer Thomas Fuchs stated, "This is indeed a new type of scientific instrument. For biologists, it is like a giant microscope. It truly enables us to do things at a scale that we could not do before." Scientists will be able to train AI models through millions of experiments to test potential drugs, "greatly expanding the scope and complexity of drug discovery."Although discovering new drugs is not the only focus of these new tools, Rau stated that this "is where the biggest opportunity lies," adding, "We hope to discover new molecules that could never be found by humans alone."

Multiple AI models will be available on Lilly TuneLab, an AI and machine learning platform that allows biotechnology companies to access Eli Lilly's drug discovery models trained on its years of proprietary research. This data is valued at $1 billion. Eli Lilly launched the platform last September, aiming to broaden access to drug discovery tools across the industry.

Rau pointed out that in exchange for access to the AI models, biotechnology companies need to contribute some of their own research and data to help train these models. The TuneLab platform employs what is known as federated learning, meaning that biotechnology companies can leverage Eli Lilly's AI models without having to share data directly.

Eli Lilly also plans to use supercomputers to shorten drug development times, helping to deliver treatments to patients more quickly. Eli Lilly stated that the new scientific AI agents can support researchers, and advanced medical imaging can provide scientists with a clearer understanding of how diseases progress, aiding them in developing new biomarkers for personalized care