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NSF AI Research Institute on Interaction for AI Assistants (NSF ARIA) is sponsored by NSF. NSF AI Research Institute on Interaction for AI Assistants (NSF ARIA) is a grant from the National Science Foundation (NSF) that funds cutting-edge research into next-generation AI assistant technologies, including energy-efficient computing and human-AI interaction.
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NSF announces $100 million investment in National Artificial Intelligence Research Institutes awards to secure American leadership in AI | NSF - U.S. National Science Foundation NSF announces $100 million investment in National Artificial Intelligence Research Institutes awards to secure American leadership in AI The investment will accelerate open innovation, empower an AI-ready workforce and strengthen U.S. global competitiveness The U.S. National Science Foundation, in partnership with Capital One and Intel, today announced a $100 million investment to support five National Artificial Intelligence Research Institutes and a central community hub.
These institutes will drive breakthroughs in high-impact areas such as mental health, materials discovery, science, technology, engineering and mathematics education, human-AI collaboration and drug development. This public-private investment aligns with the White House AI Action Plan , a national initiative to sustain and enhance America's global AI dominance.
"Artificial intelligence is key to strengthening our workforce and boosting U.S. competitiveness," said Brian Stone, performing the duties of the NSF director. "Through the National AI Research Institutes, we are turning cutting-edge ideas and research into real-world solutions and preparing Americans to lead in the technologies and jobs of the future."
While headlines often focus on the newest chatbot, AI is quietly powering advances across nearly every sector, helping doctors detect diseases, enabling smarter manufacturing and supporting resilient agriculture and financial security. The AI Institutes are designed to translate cutting-edge research into scalable, practical solutions that improve lives.
The institutes will also help build a national infrastructure for AI education and workforce development, training the next generation of researchers and practitioners, empowering educators and reaching into communities.
This effort directly supports the goals outlined in Executive Order 14277, "Advancing Artificial Intelligence Education for American Youth ," which calls for expanding AI literacy and expanding access to training and tools across all communities.
With this latest round of awards, NSF continues to grow a nationwide network of AI research institutes dedicated to advancing open innovation, strengthening U.S. competitiveness and ensuring that AI serves the public good — today and for decades to come. Each institute brings a unique interdisciplinary approach that connects AI research to tangible public benefit: NSF AI-Materials Institute (NSF AI-MI) .
Led by Cornell University , NSF AI-MI is accelerating the discovery of next-generation materials essential to energy, sustainability and quantum technologies. It will create the AI Materials Science Ecosystem, a cloud-based portal that integrates large language models with experimental data, simulations, images and scientific literature.
Through partnerships with high schools, universities and industry, NSF AI-MI will educate and train students at all levels, opening new career pathways at the intersection of AI and physical sciences. NSF AI Institute for Foundations of Machine Learning (NSF IFML) . NSF IFML is part of the first cohort of AI Institutes announced in 2020.
Led by The University of Texas at Austin , the new award will build on the trajectory of the past five years and develop new foundational tools to advance generative AI. NSF IFML's work on diffusion models is a key technology behind major Google products, powering widely used generative models such as Stable Diffusion 3 and Flux.
In its next phase, NSF IFML will expand generative AI to new domains, including protein engineering and clinical imaging. It also plans to develop new methods to handle noisy data and improve model reliability, key challenges for deploying AI in health contexts. NSF Institute for Student AI-Teaming (NSF iSAT) .
Led by the University of Colorado at Boulder, NSF iSAT — part of the first cohort of AI Institutes announced in 2020 — is transforming how AI is used to enhance STEM learning in the classroom. The institute developed two AI partners that help student groups learn together by facilitating discussion, exploration and reasoning, in close collaboration with teachers.
More than 6,000 middle-school students and educators have benefited from these tools and new AI curricula. In its next phase, NSF iSAT will address the urgent national need to build an AI-ready workforce. It will continue to advance AI support for group learning and co-develop a semester-long curriculum to build AI literacy.
NSF Molecule Maker Lab Institute (NSF MMLI) . Led by the University of Illinois Urbana-Champaign , NSF MMLI is part of the first cohort of AI Institutes announced in 2020. The institute has been developing cutting-edge AI and machine learning to dramatically speed up molecule discovery and creation for applications in medicine, materials and clean energy.
In its next phase, the institute will develop advanced AI tools — including new types of language models and intelligent agents — that can reason, predict and help design useful molecules such as drugs, catalysts and new materials. NSF AI Institutes Virtual Organization (NSF AIVO) . Led by the University of California, Davis , NSF AIVO serves as a national hub for the entire AI Institutes network.
Expanding on a successful pilot launched in 2022, it connects federally funded AI Institutes, government stakeholders and the public to create a cohesive and collaborative innovation ecosystem. Through events, networking tools and collaboration support, NSF AIVO fosters communication across the network and helps form new public-private partnerships.
It also promotes public engagement by amplifying the work of the AI Institutes and raising awareness of how AI can help address real-world challenges. NSF AI Research Institute on Interaction for AI Assistants (NSF ARIA) . Led by Brown University , NSF ARIA will accelerate the development of next-generation AI assistants that are safer, more effective, and better able to adapt to individual user needs.
To learn more about all the awards and collaborators of the National AI Research Institutes, click on the interactive map . Learn more about the AI Institutes by visiting nsf. gov .
Directorate for Computer and Information Science and Engineering (CISE) Directorate for Mathematical and Physical Sciences (MPS) Directorate for STEM Education (EDU)
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Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH) is sponsored by National Science Foundation (NSF) & National Institutes of Health (NIH). This interagency program supports transformative high-risk, high-reward advances in computer and information science, engineering, mathematics, statistics, behavioral and/or cognitive research to address pressing questions in the biomedical and public health communities. It emphasizes scientific and engineering innovations by interdisciplinary teams developing novel methods to intelligently collect, sense, connect, analyze, and interpret data from individuals, devices, and systems to enable discovery and optimize health, particularly leveraging machine learning and artificial intelligence.
Mathematical Biology Program is a grant from NSF that funds research in applied and computational mathematics with relevance to the biological and life sciences. The program supports projects across all areas of mathematical sciences that demonstrate strong integration between mathematics and biology. Successful proposals must show mathematical innovation, biological relevance and significance, and rigorous interdisciplinary methods. Projects may include development of new mathematical theories, methodologies, and computational tools aimed at advancing the life sciences. Eligible applicants are typically academic researchers and institutions. Award amounts and deadlines vary by submission cycle.
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