NVIDIA BioNeMo Agent Toolkit Brings Accelerated AI to Life Sciences Researchers in Claude Science America is a nation of builders.
For 250 years, America has built railroads that connected a continent, power grids that lit up cities, factories that powered prosperity, semiconductors that made the digital age possible and the internet that opened knowledge to the world. Now, America is building again.
NVIDIA and its partners are investing in American manufacturing, supply chains, energy grids and skilled workforces so the U.S. can produce the infrastructure needed for better healthcare, breakthrough scientific discovery, stronger industrial productivity and global technology leadership.
That progress depends on more than chips and AI models. It depends on the wide range of physical components behind them: advanced semiconductors, packaging, power systems, cooling, cloud capacity and much more — along with the people who build and operate it all.
“AI is driving a once-in-a-generation opportunity to reinvigorate American manufacturing and supply chains,” said Jensen Huang, NVIDIA founder and CEO.
In 43 states and growing, NVIDIA’s network of American partners and suppliers spans semiconductors, boards, systems, racks and more — all to meet this rare moment in the nation’s history and set up the country’s future by bringing the supply chain home.
In just the past few years, NVIDIA and its partners have onshored the most advanced semiconductor manufacturing to build and test NVIDIA Blackwell chips in Arizona, with production underway at TSMC’s Phoenix facility and new AI supercomputer manufacturing plants planned with Foxconn in Houston and Wistron in Dallas. NVIDIA plans to produce up to $500 billion of AI infrastructure in the U.S. with partners including TSMC, Foxconn, Wistron, Corning, Lumentum, Coherent and Amkor.
That means more advanced chips made in America, more systems assembled in America and more work for the contractors, technicians and engineers who are building the future.
But the purpose of this buildout extends far beyond the chips and systems being produced in the U.S. It’s to accelerate what those chips and systems make possible.
AI can help scientists discover medicines, forecast weather and solve problems once beyond reach. It can help computer scientists write software, operations teams strengthen supply chains, and engineers design and simulate products.
In this way, the five-layer cake of AI is enabling America to build new industries and reimagine existing ones. It’s helping to increase productivity, add jobs and bolster the U.S. economy. And by producing intelligence at scale, AI is supporting open science that accelerates discovery across universities, labs, startups and industry.
Doing all of this requires building three types of factories:
Public First estimates that in 2026 alone, NVIDIA-driven AI demand will contribute $485 billion to the U.S. GDP and that AI infrastructure powered by NVIDIA chips is supporting over 100,000 jobs. This includes direct jobs like electricians, plumbers, HVAC technicians, pipefitters and construction workers, as well as indirect jobs throughout the wider supply chain. In Sherman, Texas, Coherent, a key networking supplier across NVIDIA’s AI stack, broke ground this month on its expanded facility, scaling what it calls the world’s first volume production 6-inch indium phosphide fab. This is part of a project expected to create 1,000 jobs.
Those new jobs in the city of some 54,000 people are a fraction of the positions already created in the effort to build AI in the U.S.
“The onshoring of manufacturing is intensifying,” Huang said at the groundbreaking event, highlighting the hundreds of thousands of jobs being created in America. “And most of those jobs are in manufacturing plants. They are electricians and construction workers and designers and technicians. And I think that that’s going to intensify over the next decade, because we are seeing the renaissance of manufacturing here in the United States.”
In North Carolina and Texas, Corning is expanding its U.S.-based manufacturing of advanced optical connectivity solutions needed to power next-generation AI, building new facilities and opening more than 3,000 jobs. Also in North Carolina, Lumentum is advancing U.S.-based manufacturing and deepening its R&D collaboration with NVIDIA in state-of-the-art optics technologies.
In Houston, Texas, Foxconn is building a state-of-the-art factory for manufacturing NVIDIA AI systems, including NVIDIA GB300 tray modules. Foxconn engineers have used digital twins, built on NVIDIA libraries and open models, to design and validate the physical structure and AI and robotics systems that will assist factory workers.
Wistron and NVIDIA will assemble and test NVIDIA AI systems at a new advanced manufacturing facility in Fort Worth, Texas, which was designed first as a Wistron digital twin built on NVIDIA AI and Omniverse libraries. It will use NVIDIA’s open libraries, models, blueprints and physical AI ecosystem to accelerate, scale and optimize production.
In Manassas, Virginia, NVIDIA and Digital Realty created a proven AI factory blueprint, built with American suppliers across every layer of the stack, that the industry can now replicate.
These factories are made possible by a thriving ecosystem of construction companies and power equipment and system providers.
Caterpillar is integrating AI and digital twins, built on NVIDIA technologies, across its machines, power and energy solutions, and factories to transform construction sites, supply chains and industrial innovation in the U.S.
Companies such as Vertiv, Schneider Electric, Eaton, Jacobs, Siemens, Trane Technologies and GE Vernova are helping design, power, cool, simulate and operate this new infrastructure.
In this way, America is building the infrastructure of the 21st century so scientists, doctors, entrepreneurs, engineers and builders can create the cures, innovations, factories and breakthroughs that will define our future.
“AI is the ultimate general-purpose technology,” Huang said. “Because intelligence is fundamental — the ability to process information, to reason and solve problems — it affects every single industry.”
In healthcare, NVIDIA partners are using AI to help American clinicians to spend more time with patients and less time on administrative work.
For example, Abridge is building the first foundation model purpose-built for clinical conversations, using NVIDIA Nemotron open models and the NVIDIA Blackwell platform. Deployed in the U.S. across more than 300 health systems and processing more than 2.5 million clinical conversations per week, Abridge helps reduce the documentation burden that keeps clinicians working after hours. In addition, Aidoc’s aiOS platform, deployed across more than 100 U.S. health systems and 1,300 U.S. hospitals, has analyzed more than 130 million patient cases to date, with over 50 million patient scans in the U.S. alone. The company’s First Read investigational AI software analyzes chest X-rays and drafts preliminary reports for review, designed to help radiology teams manage rising demand while preserving clinician oversight.
In science, NVIDIA, Oracle and the U.S. Department of Energy are building new supercomputing systems at Argonne National Laboratory to support scientific discovery. NVIDIA Earth-2 open models help improve weather and climate forecasting, including faster localized storm predictions and global forecasts.
Plus, U.S.-based researchers, developers and enterprises are using NVIDIA AI to advance open science, materials discovery and agentic scientific discovery.
This is AI at its best: helping people build more, discover faster and solve the nation’s and the planet’s most important problems. And more and more people are discovering the work assist AI offers them.
About three-quarters of frontline workers are now regular AI users, with 42% reporting it saves them a full workday each week and more than two-thirds saying it enables them to focus on more complex work.
In addition, Ramp’s latest report showcases early evidence that the companies making bigger AI investments see faster job growth. In the two-year span after adoption, high‑intensity AI adopters grew overall employment by more than 10% compared with their peers, and their entry‑level headcount grew by 12%.
And even as AI dramatically accelerates code generation and testing, software engineering headcount has risen steadily in the years following the introduction of ChatGPT in 2022.
NVIDIA is working with its partners to ensure America’s 21st century technology infrastructure is built with attention to energy availability, grid reliability, water use, local needs, workforce development and clear rules of the road.
New approaches are already showing what that responsible buildout can look like.
For example, the NVIDIA Rubin generation of NVIDIA AI infrastructure is the [world’s first to achieve 100% liquid cooling](https://blogs.nvidia.com/blog/liquid-cooling-ai-factories/).
** — Ali Heydari**, director of data center cooling and infrastructure at NVIDIA
NVIDIA and Emerald AI are also working with energy companies on flexible data centers that can adjust power use in response to grid conditions.
“Ten years from now, I think we’ll look back and realize AI is what made it possible to invest in sustainable energy, upgrade our energy grid and reconstitute a workforce,” Huang said. “You can’t have only information workers in an economy — you also have to have builders. We have an opportunity over the next 10 years to reshape our communities and be much more balanced.”
Learn more* about how NVIDIA and its partners build in America, for America. *