NSF and NVIDIA Announce $152 Million Collaboration to Build Open AI Models for Scientific Discovery
The NSF and NVIDIA are investing $152M to develop AI models that accelerate scientific discovery across fields like biology and energy. This effort supports U.S. leadership in AI-driven research.
NSF and NVIDIA Partner with $152 Million to Advance AI for Scientific Research
The U.S. National Science Foundation (NSF) and NVIDIA have joined forces in a $152 million initiative to develop artificial intelligence models aimed at accelerating scientific discovery. This partnership will enhance the tools available to researchers and support U.S. leadership in AI-driven science.
NSF is contributing $75 million, while NVIDIA is providing $77 million to fund the Open Multimodal AI Infrastructure to Accelerate Science (OMAI) project. The Allen Institute for AI (Ai2) will lead this effort to build open-source, multimodal AI models trained on scientific literature and data.
Driving Faster, Cross-Disciplinary Scientific Insights
The AI models developed through OMAI will enable scientists to analyze complex data more efficiently, generate code, and connect knowledge across different scientific fields. Applications are expected across materials science, biology, energy, and other research areas.
Brian Stone, performing the duties of the NSF director, emphasized the importance of this partnership: “These investments are not just about enabling innovation; they are about securing U.S. global leadership in science and technology and tackling challenges once thought impossible.”
Building AI Infrastructure for Researchers
NVIDIA CEO Jensen Huang highlighted the role of large, open AI models in scientific progress: “AI is the engine of modern science — and large, open models for America’s researchers will ignite the next industrial revolution. In collaboration with NSF and Ai2, we’re accelerating innovation with state-of-the-art infrastructure that empowers U.S. scientists to generate limitless intelligence, making it America’s most powerful and renewable resource.”
This collaboration aims to equip researchers with advanced AI capabilities to speed up discovery, improve data interpretation, and foster interdisciplinary breakthroughs.
Researchers interested in AI-driven scientific tools and training can explore specialized courses and resources available at Complete AI Training.
