NVIDIA Expands U.S. AI Chip and Supercomputer Manufacturing with Blackwell Rollout

NVIDIA has launched a major U.S. manufacturing expansion for its next-gen AI infrastructure. Blackwell chips will now be produced at TSMC’s Arizona facilities, with AI supercomputers assembled in Texas by Foxconn and Wistron. Backed by partners like Amkor and SPIL, NVIDIA is localizing its AI supply chain from silicon to system integration—laying the foundation for “AI factories” powered by robotics, Omniverse digital twins, and real-time automation. By 2029, NVIDIA aims to manufacture up to $500B in AI infrastructure domestically.
NVIDIA Expands U.S. AI Chip and Supercomputer Manufacturing with Blackwell Rollout
Image Credit: Nvidia

NVIDIA Builds Domestic AI Infrastructure with TSMC, Foxconn, and Wistron

NVIDIA has officially announced a major expansion of its AI infrastructure footprint—this time on U.S. soil. For the first time in the company’s history, NVIDIA will manufacture its AI supercomputers and next-generation semiconductors entirely within the United States.


In collaboration with manufacturing giants TSMC, Foxconn, and Wistron, NVIDIA is establishing over one million square feet of dedicated production capacity in Arizona and Texas. This move supports not just chip manufacturing but the entire lifecycle of AI supercomputer development—from silicon fabrication and testing to packaging and system integration.

The initiative signals a fundamental shift in the AI supply chain and reflects growing pressure for technological sovereignty, supply chain resilience, and the onshoring of strategic infrastructure.

NVIDIA Blackwell AI Chips Begin Production in Arizona with Full Supercomputer Builds in Texas

NVIDIA’s new Blackwell chipsets—tailored for AI model training and inference—have officially entered production at TSMC’s advanced node facilities in Phoenix, Arizona. These chips are at the heart of NVIDIA’s next-generation computing systems, designed to handle the computational demands of modern large language models (LLMs) and Generative AI.

Down the supply chain, two major supercomputer manufacturing sites are being launched: one in Houston, operated by Foxconn, and another in Dallas, operated by Wistron. These factories will assemble, test, and integrate the full AI computing platforms powered by the Blackwell architecture.

Mass production is expected to scale significantly over the next 12–15 months, with NVIDIA signaling that these plants will play a pivotal role in meeting global demand for AI processing power.

Building a Domestic AI Supply Chain—From Silicon to System Integration

NVIDIA is addressing more than just chip production. The entire value chain—from chip packaging to end-to-end testing—is being localized. The company is partnering with Amkor and SPIL in Arizona for backend manufacturing processes, which are typically outsourced to Asia. These partnerships support the packaging of advanced chipsets and ensure seamless integration into full-stack AI supercomputers.

By 2029, NVIDIA aims to manufacture up to $500 billion worth of AI infrastructure in the U.S., a bold strategy that emphasizes economic impact alongside technical advancement. It also showcases a commitment to national priorities such as supply chain independence, high-tech job creation, and domestic innovation.

NVIDIA’s AI Factories Signal a Shift in Global Tech Infrastructure

NVIDIA describes these new manufacturing sites as “AI factories”—data center-grade facilities built solely for AI workloads. Unlike traditional compute environments, these factories are optimized for real-time data processing, model training, inference, and advanced analytics.

Tens of such gigawatt-scale AI factories are expected to be built in the coming years to support use cases across sectors like healthcare, financial services, automotive, and telecom.

These facilities will be vital for delivering high-throughput AI capabilities to power applications like digital twins, autonomous systems, virtual assistants, and generative AI tools.

NVIDIA Uses Omniverse and Robotics to Power Smart AI Factories

To streamline operations, NVIDIA plans to use its own technology stack to design and run these factories. Using the NVIDIA Omniverse, the company will build high-fidelity digital twins of its production facilities to simulate workflows, test equipment placement, and optimize throughput before physical deployment.

Additionally, NVIDIA Isaac GR00T, the company’s robotics platform, will automate large portions of the manufacturing process. These smart robots will handle component assembly, automated inspection, and logistics, reducing error margins and increasing productivity across sites.

This integration of AI, robotics, and automation signals a new standard in factory operations, merging digital infrastructure with physical manufacturing in real time.

U.S. AI Manufacturing Expansion Fuels Jobs and Global Tech Leadership

NVIDIA’s U.S.-based production is expected to generate hundreds of thousands of jobs, from factory technicians to software engineers. It also strengthens the U.S. position in the global race to dominate AI, semiconductors, and advanced computing.

According to Jensen Huang, Founder and CEO of NVIDIA, “The engines of the world’s AI infrastructure are being built in the United States for the first time. Adding American manufacturing helps us better meet the incredible and growing demand for AI chips and supercomputers, strengthens our supply chain, and boosts our resiliency.”

A Strategic Move That Sets the Tone for the AI-First Economy

NVIDIA’s announcement isn’t just about moving manufacturing closer to home—it’s a signal to the broader tech ecosystem. As AI becomes foundational to everything from drug discovery and cybersecurity to smart cities and self-driving vehicles, companies will need more localized, secure, and scalable AI infrastructure.

By integrating semiconductor manufacturing with edge computing, digital twins, and AI software frameworks under one national footprint, NVIDIA is building a comprehensive blueprint for the AI-powered future.


Recent Content

In a rapidly evolving business landscape, enterprises across different sectors are increasingly turning to customized connectivity solutions to address unique challenges. This article delves into how tailored IT strategies are essential in driving business performance amidst cybersecurity risks and sector-specific regulations.
Intel’s Gaudi 3 AI accelerator emerges as a formidable contender in the enterprise AI space, rivaling Nvidia’s H100 with superior performance, efficiency, and scalability. Through strategic collaborations and a commitment to an open AI ecosystem, Intel is paving the way for businesses to harness next-generation AI capabilities.
Few industries have been as fast and far-reaching as financial services in their response to the opportunities of the digital economy. Legacy connectivity models, once the cornerstone of the financial sector, now present challenges regarding speed, cost, flexibility, and security. The cracks are beginning to show. This article examines the role of Closed User Groups and the strategic shift that could disrupt banking operations.
Data Scientists are already in short supply. One of the most promising areas to make Data Scientist more productive is Generative AI. However, while Generative AI will increase the productivity of Data Scientists, it will lead to an even more serve crunch in the Data Scientist supply.
What did Insight Research conclude during its coverage of AI in the RAN in its report “AI and RAN – How fast will they run?
1. AI intersects the RAN at numerous angles – the principal end-applications for AI in RAN are traffic optimization, caching, coding and energy management.
2. The impact of AI on these applications is on technical, commercial and competitive fronts.
3. There are numerous AI, ML and DL algorithms that are being used to improve the above end-applications.
4. Thanks to the penchant of AI in dealing with complexity, each of these end-applications will enjoy high CAGRs.
5. AI has democratized the RAN vendor landscape
SK Telecom has ambitious plans for global expansion of ifland, its metaverse platformThe telco has further expanded its partner ecosystem to enable the develop…

Currently, no free downloads are available for related categories. Search similar content to download:

  • Reset

It seems we can't find what you're looking for.

Download Magazine

With Subscription

Subscribe To Our Newsletter

Scroll to Top