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NVIDIA Blog · 2026/8/4 16:00:56

NVIDIA Joins NSF State and Regional AI Hubs Program to Expand AI Research and Education Across the US

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美国国家科学基金会刚启动了一个叫“州与区域AI基础设施中心”的项目,NVIDIA第一时间就加入了。一句话概括核心亮点:NVIDIA要把美国大学的AI资源“共享化”,让更多学校和学生用上顶级AI计算能力,而不只是少数名校的特权。 简单来说,这个项目就像在各地建“AI公共图书馆”。以前,只有资金雄厚的顶尖大学才买得起超级计算机搞AI研究,很多普通高校只能在一旁眼巴巴看着。现在,NVIDIA联合政府和高校,把算力、软件和专家资源聚到一起,让周边地区的大学都能按需使用。这种做法其实有成功先例——他们和佛罗里达大学合作过,已经把全校16个学院都带上了AI赛车道,还拿到了5亿多美元的研究经费。 这对普通人的影响会慢慢渗透到身边。未来你的大学老师可能用AI辅助教学,科研团队开发的新药、农业技术应用的也是这些算力支撑的成果。更重要的是,更多学生能掌握AI实操技能,毕业找工作时就更有底气。可以说,这个项目在帮美国“批量生产”AI人才,也为普通人打开了一扇通往AI时代的门。
NVIDIA is participating in the U.S. National Science Foundation’s (NSF) State and Regional Artificial Intelligence Infrastructure Hubs program, an effort launching today to expand access to the advanced computing, data, software and expertise needed for AI-enabled research and education. Consistent with the aims of the Genesis Mission, the program will support state and multistate groups of colleges and universities working together to strengthen America’s AI ecosystem. In partnership with private industry, philanthropic organizations and state and local governments, the program will expand the AI infrastructure, software, educational resources and technical support needed by faculty, students and researchers across the country.  These regional hubs will help institutions share AI computing resources, accelerate scientific discovery and innovation, and prepare students to participate in the AI economy. Expanding Access to AI Infrastructure The State and Regional AI Infrastructure Hubs program will bring shared resources closer to the institutions and communities they serve.  State or regional consortia can pool expertise, focus on specific local priorities, achieve economies of scale and create pathways for institutions that might otherwise remain outside the frontier of AI-enabled research and education. Flexible approaches — including on-premises infrastructure, cloud computing or a combination — will allow consortia to design resources around their regional needs and economic priorities.  The hubs will resemble the public-private partnership between NVIDIA, NVIDIA cofounder Chris Malachowsky and the University of Florida (UF) in 2020 to turn UF into the country’s first true AI university and provide AI compute access to all Florida public universities. That initiative now serves as a national model. Since launching its university-wide initiative in 2020, UF has grown to more than 300 AI-focused faculty and embedded AI education and research across all 16 colleges. And since 2017, UF faculty and units have received more than $511 million in AI research awards. NVIDIA has also expanded academic compute access in other ways, including as a leading contributor to the NSF-led National Artificial Intelligence Research Resource (NAIRR) pilot program on which today’s announcement is built.  Through NAIRR, NVIDIA partnered with university research teams across the country to turn computing resources into usable scientific capacity — giving researchers the infrastructure, tools and expertise needed to move from idea to experiment to discovery. The resources also facilitated meaningful educational opportunities that gave students critical real-world skills for the AI economy.  Preparing the AI Workforce AI infrastructure alone is not enough. A successful national AI strategy must include efforts to build a workforce that can use advanced computing, data resources and AI tools in real scientific and industry settings. That means pairing infrastructure with clear learning pathways. Universities, community colleges and regional partners can build degree programs, short-form certificates and stackable credentials that help learners move from foundational AI literacy into applied skills. Those pathways will help students, faculty, working adults and technical professionals use AI, including open source models and technologies, in fields like physical AI and automation, healthcare, energy, agriculture, manufacturing, quantum computing and cybersecurity.  NVIDIA can support this work by providing training resources, educator enablement, applied learning content, technical guidance, partner platforms and access to tools that help institutions move from awareness to hands-on capability. As NVIDIA’s education and training offerings evolve, the goal remains the same: help institutions build repeatable, openly available programs that prepare learners to use AI systems, accelerated computing and data workflows responsibly and effectively. This is
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