Academia/Higher Education

Bringing AI Education to Every College and Discipline


Through a partnership with NVIDIA, UF adopts a university-wide AI education approach, offering a roadmap for seamless integration across disciplines, enhancing academic quality, and fostering a reputation for research and innovation.


University of Florida

Use Case

Academia / Higher Education



NVIDIA and the University of Florida Are Partnering to Prepare Graduates for Technology Jobs

The use of artificial intelligence in research and industry has accelerated in recent years, creating a strong demand for data scientists and tech-savvy workers.  

Per Deloitte, 94 percent of business leaders believe that AI will be critical to success over the next five years. Fifty-six percent of recent McKinsey survey respondents reported that their organization had adopted AI applications for at least one function. 

Unfortunately, there’s a growing skills gap. Only six in 10 employers believe that new graduates possess the knowledge and skills necessary to succeed in entry-level positions. The current global tech talent shortage is projected to reach 85 million people by 2030, leaving roles unfilled and research projects understaffed.

NVIDIA and the University of Florida

Image Courtesy of University of Florida

The University of Florida (UF) is a public land-grant university in Gainesville, Florida. UF is home to 16 academic colleges covering a range of arts and sciences disciplines. UF is one of 12 public universities in the state of Florida’s university system. 

Partnering with NVIDIA for AI hardware and expertise, UF has taken a whole-university approach to AI education to:

  • Undertake groundbreaking research to attract the brightest professionals, students, and investments
  • Increase AI computing capacity
  • Recruit and retrain AI-focused faculty
  • Deliver AI education to every student in every discipline
  • Enhance existing strengths with AI research programs
University-based AI knowledge and talent cultivation

Image Courtesy of University of Florida

AI Haves and Have-Nots

Universities play an important role in preparing the next generation of graduates to work with technology. However, constrained budgets and corporate competition for AI-focused faculty and researchers have left many universities falling behind. 

University-based AI knowledge and talent cultivation have often been left in a dichotomy of “haves” and “have-nots.” 

With limited access to AI hardware, data, and software and few AI-trained professors, many students are graduating without the skills they need to succeed in an increasingly AI-driven world. Public universities that lack the funding of well-resourced private universities are especially at risk.


NVIDIA and UF Are Driving Education, Research, and Impact With AI

With a goal of creating equal opportunity for students to prepare for and participate in the AI-driven future, the UF AI steering committee invited each of the 16 colleges to jointly plan and fund AI initiatives across the university.  

To get started, the university needed to raise funds to support the creation of new AI computing infrastructure, software, and laboratories and recruit new talent. 

The state of Florida provided $100 million in funding for UF to build a new data center and $15 million per year to hire 100 new AI faculty to support sustained AI education.

The steering committee also turned to its donor network to raise additional funds. 

UF spent $15 million to update their data center capacity.  

With preparations ready, NVIDIA solution architects and product engineers worked on site to install HiPerGator AI, an NVIDIA DGX SuperPOD™ consisting of 140 NVIDIA DGX™ A100 systems, each with eight NVIDIA A100 Tensor Core GPUs, and an additional 17,920 CPUs. Completed in 90 days, the installation became the largest AI supercomputer installed at a university.   

Using their DGX SuperPOD, UF developed the largest clinical language model to date, GatorTron, with 3.9 billion parameters. More than 10X larger than the second-largest clinical model, it reduced misclassification by 24 percent from BERT-large in the i2b2-2010 named-entity recognition benchmark.

“We believe that AI shouldn’t be limited to the computer science department or to one institution. Making sure that students across the curriculum learn about AI gives us the opportunity to train people at scale for tomorrow’s jobs.”

Joseph Glover
Provost, the University of Florida

Spreading the Benefits of AI

HiPerGator AI has been in production since January 2021 and is already helping UF spread the benefits of AI education, conduct impactful research, and better prepare students for the jobs in demand today.

Diversifying AI Research Across the University

To encourage AI engagement beyond traditional STEM disciplines, UF created an AI Research Catalyst Fund to help teams pursue imaginative applications of AI. In the first call for proposals, 133 requests for funding were submitted. Twenty were selected as having the greatest potential to elevate the university’s research profile. Funded projects included: 

  • AI to detect biomarkers for Alzheimer’s disease
  • Machine learning to track past and present land use and patterns in Florida to measure the impact of development
  • AI to help teach identify academically at-risk students
  • AI to identify parasitic nematodes that damage agricultural products 

The university combined existing databases and data analysis strengths with new AI computing strengths to drive these projects forward. 

By partnering with all 12 public universities in the state of Florida university system, UF is helping to increase access to AI resources, including to groups historically underrepresented in science and engineering.

Diversifying AI Research

Pursuing Moonshot Research

UF is undertaking moonshot research initiatives—complex projects intended to tackle the globe’s most pressing problems. 

One of the first examples of this is the university’s development of GatorTron, a natural language processing (NLP) model that enables computers to read and interpret medical language in clinical notes that are stored in electronic health records (EHRs). By automatically extracting accurate information from these notes, researchers hope to accelerate clinical research and medical decision-making.  

UF and NVIDIA used HiPerGator AI to train the GatorTron NLP model on 82 billion words and 8.9 million parameters contained in medical records. Training was completed in seven days, beating out the previous largest model, ClinicalBERT. 

This vast trove of medical insights can be applied to numerous use cases, including applications that more efficiently match patients to medical trials, helping to speed drug discovery.  

As a follow-up project, NVIDIA and UF are developing SynGator, a neural network that generates synthetic clinical data to train healthcare AI models. SynGator can generate health records of digital cancer patients, which researchers can then use to create tools and models without risking the privacy of protected health information.

Improving AI Education and Workforce Development

UF was the first university in the country to introduce AI curricula across disciplines, offering elective AI courses in every undergraduate major. New elective courses include: 

  • Biomedical Data Science 
  • AI In Agricultural and Life Sciences 
  • AI In the Built Environment
  • AI In Media and Society

The university offers a nine-credit AI certificate for undergraduates to acquire a baseline of AI literacy. The certificate requires students to complete an AI fundamentals course, an AI ethics course, and a major-specific course. 

To help spread AI knowledge beyond university walls, UF also launched a microcredential designed for working professionals. It provides training and digital certificates to demonstrate in-demand AI skills, know-how, and experience.

AI Education and Workforce Development

AI Education and Workforce Development

Growing a Team of AI-Focused Faculty

Hiring an additional 100 AI-focused faculty members let UF offer more AI classes to students—including beyond STEM majors.  

UF has welcomed artists and creative technologists to join its College of the Arts, who are now leading scholarly and creative research in AI in the Schools of Music, Theatre and Dance, and Art and History. 

In addition, many of UF’s staff have upskilled through NVIDIA’s Deep Learning Institute (DLI) Ambassador Program— a free training opportunity that NVIDIA offers to university faculty on GPU-accelerated computing. The training empowers instructors with the knowledge and tools needed to deliver courses in accelerated computing, deep learning, and robotics. DLI also offers students free online training, certification, and cloud access to GPUs.  

A Blueprint to Build an AI University

Thanks in part to its investment in AI education, the University of Florida is now ranked among the top five public universities in the United States. 

The success of UF’s AI initiatives can serve as a guide to other universities ready to embrace the AI future. Strategies that helped drive success include:

  • A university-wide approach with shared costs and benefits to overcome internal resistance
  • Engaging local government and private donors to secure funding
  • Ambitious research projects to attract the brightest minds and most motivated students
  • Leveraging AI and existing datasets to enhance academic core competencies
  • Sharing AI-knowledge and tools beyond campus with partnerships and open-enrollment programs

Universities that integrate AI education across disciplines position themselves to overcome enrollment and retention challenges, offer students the highest quality of scholarship and experience, and build a reputation as an acclaimed destination of research and innovation.