The Department of the Navy is ensuring its officers at the highest levels understand how artificial intelligence works as it adopts and integrates it into its warfighting functions.
The Naval Postgraduate School is at the center of those efforts, providing both the courses and the technology to drive that learning.
Speaking at the the West conference sponsored by AFCEA and U.S. Naval Institute back in February, Randy Pugh, then NPS’s vice provost for warfare studies, the director of the Office of Warfare Studies and the lead of the AI task force, said teaching classes and doing research are important pieces to this puzzle. But NPS’s new relationship with Nvidia is helping drive home the necessary learning.
“Our relationship with Nvidia allows us access to their Deep Learning Institute, which is commercial certifications and all these different aspects of machine learning, modeling and simulation, advanced graphic processing unit (GPU)-based, hyper-compute and so with all of that, the primary effort is to get everybody as smart and capable as possible in AI,” Pugh said in an interview on Ask the CIO. “The other gifts from Nvidia via the NPS Foundation are the $15 million AI supercomputer, which is being installed now at Naval Postgraduate School. It’s a one of a kind in the Defense Department, serial number two coming off the Nvidia assembly line is coming to the Naval Postgraduate School, so that everybody will be able to see it first there and put their hands on it there first.”
Pugh left NPS in March after serving almost four years in his roles. He has since been replaced by Navy Capt. Michael Owen.
NPS, which signed a new Cooperative Research and Development Agreement (CRADA) with Nvidia in December 2024, also is receiving access to a modeling and simulation platform, which is a $5 million Omniverse instance to help train the “brains” of robots and drones in a virtual sense, before the Navy puts them into the mechanical bodies.
“This Nvidia AI Tech Center, which connects the students and faculty at NPS back to Nvidia headquarters and all of the subject matter expertise there, as well as to the larger Nvidia ecosystem, which includes its 15,000 partners working on AI-related projects, lets us tap into that incredible corpus of knowledge and experience use cases and potential solutions for the department,” Pugh said. “Nvidia came to us and offered us a gift. One of the missions Jensen Huang, the CEO, was that they had a great understanding of commercial use cases and the infrastructure required to support those, but they did not have a lot of understanding of military use cases or the associated challenges of applying AI to these use cases. We’re going to learn by doing, by establishing this infrastructure at NPS, and then running it red hot for the next year or two. By doing that, the other thing we’re learning is as we look to help others establish their infrastructure, either at the tactical edge, so out on a ship or in a submarine or in an expeditionary advanced base with Marines, what is the kind of infrastructure that you’re going to need in order to do that? So the three lines of effort are interdependent.”
Research efforts like the one with Nvidia and many others are creating a strong foundation for educating NPS students. About 50% of NPS’ budget for research contributes directly to the education of its students.
NPS is following a simple motto: “If you want to educate somebody at the forefront, you’ve got to be at the forefront yourself,” said Dr. Michael Hesse, the vice provost for research and innovation at the school.
Hesse, who joined NPS from NASA, said partnerships with industry and other Navy organizations like the warfare centers, help to lower the risk of bringing new capabilities to the service.
Hesse said some of NPS’s top research priorities include AI, space and autonomous vehicles.
“The school has this enormous focus on AI, which is utterly appropriate because we apply that everywhere from knowledge management to making operational decisions to interfacing with humans and shaping how humans can beneficially interact and maintain decision authority in an in an environment where autonomy and AI are more and more necessary in order to address the needs of the field we’re operating in,” Hesse said. “Directed energy weapons is another big topic that we’re doing here at the postgraduate school. Autonomous vehicles is another area. The Secretary of the Navy talks about deploying autonomous vehicles and having that work in conjunction with crude vehicles in a beneficial way. That’s something we are working on in programs like CRUSER. Of course, space is another priority. Space is important for the Navy in so many ways, from position, navigation and timing to reconnaissance to detection and even in communication, of course, over the horizon radar and things like that.”
The research efforts leads to better training opportunities for sailors, marines, other service members and civilians.
First Masters degree cohort just getting started
Pugh said one example of this opportunity is a new one-year pilot program established by Vice Adm. Michael Vernazza, commander of Naval Information Forces, for a Master of Science degree in artificial intelligence.
Pugh said Vernazza recognized the value of creating the program, starting with an initial cohort of 27 full-time students this summer who already have done programming or have an undergraduate degree in computer science.
“Another thing that Adm. Vernazza and his team understand is the value of these officers when they exit the program, they’re identifying these billets or these jobs within the operating force where they can go and continue to inform people about AI and educate people about what AI is and is not and what it can and cannot do. They also will lead those efforts as change agents and thought leaders within those organizations to accelerate the adoption and integration of AI in the Navy,” Pugh said. “This degree is really well balanced because it provides a foundation in things that have not changed. How does machine learning work? For example, what is supervised learning, unsupervised learning and reinforcement learning? And these are concepts that are enduring. But then the second half of the year is really about taking electives or learning about the new technologies or the new techniques that are evolving with AI. Then, most of all, putting it together into solving a problem as part of your thesis or capstone project for the degree program.”
NPS will track the progress of the first cohort and report back to Vernazza, which will help it determine whether future cohorts are possible.
Vernazza’s sponsorship of this education cohort is a good example of how NPS determines research or innovation focus areas.
Hesse said NPS may get a request from a commander, and then the next question they have to ask is, “What role can we play in answering that question?”
“Maybe we have something on the shelf, or have a research project that addresses it directly, or something that can be re-vectored into that direction to provide what they need. If there’s a need, we can maybe help find somebody to support it,” he said. “Our students provide operational knowledge that we can feed into our research projects. They walk away with that knowledge of a dual track transition to operations. Like I always say, in the ordinary research track, you do research and we work to lower the technology readiness level (TRL). But you then work with a company or customer on something with a higher TRL and bring it into operations, we can tap into the mind of our students. They take that knowledge with them back to their commands. That is the type of thing only we can provide.”
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