Universities are preparing students for an ever-changing world. Emerging technologies like artificial intelligence and data science are poised to become a core fabric of higher education and research institutions and a key to unlocking scientific breakthroughs. Leading universities are tapping into NVIDIA GPU-accelerated supercomputers, labs, and programs to equip students, faculty, and researchers with the tools they need to transform the world.
An initiative between NVIDIA and the University of Florida is turning the idea of an “AI university” into reality. From the perspective of the Innovation Technology and Innovation Foundation (ITIF), this public-private partnership model is working to advance AI research, train the next-gen workforce, and ensure equitable access to AI resources.
This Industry brief outlines the steps universities should take to retain top talent, drive breakthrough research, attract funding and prepare the next gen workforce for the AI-powered future.
Empowering the Next-Generation Workforce
The NVIDIA Deep Learning Institute (DLI) puts AI training materials directly into the hands of students, researchers, and faculty. Through practical, hands-on experience with the latest technology, they can experience firsthand how supercomputers and labs run by NVIDIA GPUs can deliver massive processing gains, driving forward a next-generation workforce with exascale computing.
Partnering to Boost Academic Research and Funding
Research and workforce capacity can be grown through private-public partnerships. These strategic partnerships open up the potential for faster, large-scale AI compute capabilities, unleashing innovation within academic institutions. Government also plays a key role here, creating the legislative pathways for national AI research hubs.
Focusing on Equity in AI and Developer Diversity
Partnering with educators and leaders, NVIDIA is focused on the creation of fair and inclusive AI, committed to bringing the power of GPUs into the hands of K–12 students, state and community colleges, historically black colleges and universities, and Hispanic-serving institutions.
Setting the Bar for Enterprise AI Infrastructure
From lab desks to data centers, NVIDIA GPU platforms provide researchers, students, and data scientists with the performance and tools they need to get up and running quickly. NVIDIA DGX™ systems reduce the critical time organizations spend going from AI concept to AI readiness.
Don't miss these upcoming higher education sessions at GTC.
AI is creating opportunities, making history, and turbocharging scientific breakthroughs. From record-setting DNA sequencing to the most advanced computing chips, systems, and software of the future, we're seeing true innovators develop solutions that change the world. If you're a student inspired by AI but don’t know where to begin, this is a great opportunity to learn from today’s leading experts. Join us for this GTC panel and learn about their accomplishments, challenges, and lessons learned.
The U.S. government recognizes its important role in broadening access to AI resources for workforce development with the passage of the $280B CHIPS & Science Act. The National Science Foundation is leading an effort to create a national network of AI research centers by facilitating partnerships between government agencies, academic institutions, and industry leaders. A model example of such a partnership is that of the University of Florida and NVIDIA, who in 2021 built the largest AI supercomputer in academia. This conversation with key individuals from industry, academia, and government will review how the partnership was constructed & implemented, national goals for equitable AI research & education, and how federal agencies can learn from this project to strengthen the American workforce as a whole.
Conventional microelectronics design tools employ modeling and simulation to study system performances and limitations. Over the last decade, the microelectronics design space has grown exponentially because of the enormous growth in computing architecture types and application software. Computer simulators are commonly used for microelectronics design exploration. However, complex chip simulations, utilizing these conventional simulators, take an enormous amount of time. AI-based methods for microelectronics design are gaining popularity due to reduced cost and time-to-market for chip design and fabrication. We'll discuss AI-based approaches for microelectronics design and fabrication.
Learn from the academic institutions using AI to optimize processes, trim costs, and solve society’s toughest challenges.
The University of Florida’s academic health center, UF Health, has teamed up with NVIDIA to develop a neural network that generates synthetic clinical data—a powerful resource that researchers can use to train other AI models in healthcare. Trained on a decade of data representing more than 2 million patients, SynGatorTron is a language model that can create synthetic patient profiles that mimic the health records it’s learned from. The 5 billion-parameter model is the largest language generator in healthcare.
Scientific discovery powered by supercomputing has the potential to transform the world with research that benefits science, industry, and society. The open, cloud-native supercomputer at Cambridge University offers unrivaled performance that will enable researchers to pursue exploration like never before. NVIDIA® BlueField® DPUs connected with NVIDIA HDR InfiniBand enable this secured, multi-tenant supercomputer.
Linköping University has been building Sweden’s fastest AI supercomputer, based on the NVIDIA DGX SuperPOD™ computing infrastructure. The new BerzeLiUs supercomputer will deliver 300 petaflops of AI performance to power state-of-the-art AI research and deep learning models and accelerate Swedish AI research across academia and industry.
We look forward to DGX H100 systems powering our collaborative research tackling grand challenges in climate science, sustainability, and microelectronics. The systems are key groundwork for AI infrastructure we’ll deploy in the new Jen-Hsun and Lori Huang Collaborative Innovation Complex, enabling Oregon State University to drive innovation, solutions, entrepreneurship, and partnerships with industry and other higher education institutions to benefit Oregon, the nation, and the world.
— Edward Feser, Oregon State University Provost and Executive Vice President
We adopted a unique philosophy of ‘AI Across the Curriculum’ to ensure that all students in all majors have the opportunity to acquire the skills of AI in the context of their chosen disciplines. All colleges and departments have enthusiastically embraced this, and most are integrating AI into the curriculum. Not only does this give our students a leg up in the job market, but we believe it is a scalable model to answer the nation’s pressing need to develop a twenty-first-century AI-savvy workforce at scale.
— Joe Glover, Provost, University of Florida
Learn about the AI and high-performance computing (HPC) hardware, software, and networking solutions for academic institutions.
Whether creating quality customer experiences, delivering better patient outcomes, or streamlining the supply chain, enterprises need infrastructure that can deliver AI-powered insights. Find out how NVIDIA DGX systems deliver the world’s leading solutions for enterprise AI infrastructure at scale.
NVIDIA platforms are powering next-generation capabilities in AI, HPC, and graphics, pushing the boundaries of what’s possible. With NVIDIA’s GPU-accelerated solutions available through all top cloud platforms, innovators everywhere can access massive computing power on demand and with ease.
NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics software that’s optimized to enable any organization to use AI. It’s certified to deploy anywhere—from the enterprise data center to the public cloud—and includes global enterprise support to keep AI projects on track.
In this self-paced course, experience how deep learning works through hands-on exercises in computer vision and natural language processing and train deep learning models from scratch, learning tools and tricks to achieve highly accurate results.
Designed for enterprise IT professionals and administrators, this course explores an introduction to AI, GPU computing, NVIDIA AI software architecture, and how to implement and scale AI workloads in the data center.
This course explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs on massively parallel NVIDIA GPUs.
Engage, train, and nurture students, researchers, and faculty through practical, hands-on experience with the latest technology. Supercomputers labs run by NVIDIA GPUs deliver massive processing gains, driving a next-generation workforce with exascale computing.
Learn the AI essentials from NVIDIA. Check out our “getting started” resources to explore the fundamentals of today’s hottest technologies. Or, take a deeper dive with NVIDIA DLI training and discover new interests at your own pace.
The NVIDIA DLI University Ambassador Program certifies qualified educators to deliver free hands-on workshops to university faculty, students, and researchers in the areas of GPU-accelerated computing, AI, and data science.
The NVIDIA Applied Research Accelerator Program promotes innovation by supporting research with technical guidance, hardware, and funding for projects with the potential to make a real-world impact through deployment into GPU-accelerated applications.
Get the resources you need to develop critical skills in AI, data science, or accelerated computing.
Learn about the latest developments and available resources for the NVIDIA Omniverse™ platform.
Learn more about the program designed to support cutting-edge PhD research in all areas of computing innovation.
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