The U.S. National Science Foundation has launched a $100 million program to build AI computing infrastructure hubs across the country, aiming to close the gap between research institutions that have access to advanced compute and those that don't. The NSF State and Regional Artificial Intelligence Infrastructure Hubs program will support up to 10 hubs, with one award per state or region, and is designed to give researchers, students, and educators access to the AI resources frontier science now requires.
The program responds to recommendations in "Science: A New Golden Age," a July 2026 report from White House Office of Science and Technology Policy Director Michael Kratsios that calls for renewing America's research enterprise. The administration's Fiscal Year 2028 R&D priorities memorandum, issued alongside the report, identifies AI for science as a national mission and calls for expanding access to advanced compute and data infrastructure.
How the hubs will work
Each hub will function as a flexible state or multistate regional consortium, pooling contributions from research institutions, philanthropic organizations, state and local governments, and the private sector. NSF's role is catalytic: the agency will invest in consortium coordination, AI infrastructure workforce development, and faculty training to put compute resources to work.
The program is designed to connect researchers with regional infrastructure: NSF will invest in AI infrastructure professionals who can support researchers, students, and educators applying AI to scientific problems, and link meritorious research to the hubs in their regions. Hubs are also encouraged to integrate with the NSF-led National AI Research Resource to share data and surge beyond local capacity.
"Artificial intelligence is transforming how we conduct research, accelerate scientific discovery and address complex challenges across disciplines," said Brian Stone, performing the duties of the NSF director. "The State and Regional AI Infrastructure Hubs program supports a national mission to advance AI for science by expanding access to critical AI resources, strengthening state and regional ecosystems, and developing the workforce capabilities needed to harness these technologies."
Michael Kratsios, assistant to the president and director of the White House Office of Science and Technology Policy, added: "American scientists deserve the world's best tools to enable their most ambitious work. These hubs deliver on that commitment in the most practical way possible. Regional partners who share in the benefits of discovery will pool their resources to unlock compute at a scale that no individual stakeholder, and no federal program, could achieve alone."
Workforce development and industry partners
Each hub will also partner with regional industry to align AI workforce training with local job market needs. The program supports the White House-led Genesis Mission, a national effort to apply AI to science, and encourages engagement with existing national structures for workforce development.
Several private and philanthropic groups intend to support participants, including NVIDIA, AMD, Intel, Dell Technologies, Hangar, and the Secunda Innovation Fund. The program coordinates with existing federal programs - NSF's TechAccess: AI-Ready America, for instance, and the Campus Research Computing Consortium for workforce development. More organizations are expects to join as the program moves forward.
Why this matters for researchers
Until now, a researcher at a resource-strapped institution faced a stark choice: compete for time on a handful of supercomputers, or forgo AI-driven methods altogether. This program changes that calculus. Instead of a single federal program or a small cluster of ambitious states, the NSF aims to build a national fabric of regional hubs, so the researcher with a question about protein folding - or data-limited field like ecology - has a local pathway to compute access, training, and rapid experimentation.
For researchers, educators, and students, the practical effect is direct: a educated layer of regional AI infrastructure plus trained support staff to help them use it. And for regional employers, the hubs' partnership requirement means curricula will be tied to actual AI job signals.
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