The U.S. Department of Energy (DOE) and AMD are collaborating on two new AI supercomputers at Oak Ridge National Laboratory (ORNL) as part of a larger AI strategy to advance scientific, energy, and national security research and strengthen the nation’s position in high-performance computing.
The two machines will involve a combined public and private investment of approximately $1 billion. Once completed, it will form part of a secure national computing network designed to support AI research using standards-based infrastructure built in the United States. This project reflects how a tailored AI strategy can align national goals in innovation, energy efficiency, and data governance.
Dr. Lisa Su, AMD Chairman and CEO, said the company is “proud and honored to partner with the Department of Energy and Oak Ridge National Laboratory to accelerate America’s science and innovation infrastructure.” He added that these systems will “leverage AMD’s high-performance and AI computing technologies to advance America’s most important research priorities in science, energy, and medicine.”
Lux AI: Training the next wave of AI models
Scheduled to be operational in early 2026, Lux AI will be the nation’s first “AI Factory,” a facility built to train and deploy advanced AI models for science, energy, and security. The system is developed in collaboration with ORNL, AMD, Oracle Cloud Infrastructure, and Hewlett Packard Enterprise.
Lux uses AMD Instinct MI355X GPUs, EPYC CPUs, and Pensando networking to handle data-intensive AI tasks. It is designed to speed up research in areas such as energy systems, materials, and medicine. The system’s architecture allows multiple groups to work together while securely separating data, making it a model that reflects how many large enterprises are beginning to manage sensitive AI workloads.
Discovery: Strengthening America’s AI and Supercomputing Strategy
The Discovery system will follow in 2028 and become DOE’s next flagship supercomputer at Oak Ridge. It uses AMD’s upcoming “Venice” EPYC processor and MI430X GPU. These are part of a new series built for AI and scientific computing.
Discovery’s “bandwidth everywhere” design improves memory and network performance without using more power. This means you can process more data and run complex models efficiently while maintaining energy costs. This is a challenge many large data centers face today.
The system builds on lessons learned from Frontier, the world’s first exascale computer, and makes it easy to migrate existing applications to new platforms.
“Winning the AI race will require new and creative partnerships that bring together the brightest minds and industry that American technology and science has to offer,” said U.S. Energy Secretary Chris Wright. He said the new system demonstrates a “common sense approach to computing partnerships” that strengthens the country through shared innovation.
ORNL Director Steven Streifer said Discovery will “drive scientific innovation faster and farther than ever before,” adding that the combination of high-performance computing and AI will shorten the time from research problems to real-world solutions.
Partnerships that drive AI innovation and long-term strategy
AMD, HPE, and Oracle each play a key role in building and supporting the system. HPE President and CEO Antonio Neri said the partnership will enable Oak Ridge to achieve “unprecedented productivity and scale.” Mahesh Thiagarajan, Oracle’s executive vice president, said the company will work with the DOE to “provide a sovereign, high-performance AI infrastructure to support the joint development of the Lux AI cluster.”
Once operational, Lux and Discovery will enable DOE to run large-scale AI models to improve understanding of energy, biology, materials science, and national defense. Discovery will also help design the next generation of batteries, reactors, semiconductors, and critical materials.
What it means for corporate leaders
For organizations, these systems highlight how AI strategies and HPC can accelerate research, improve efficiency, and secure data management. It also shows that improved performance does not have to come at the expense of increased energy usage.
DOE’s partnerships with technology providers reflect a model that private companies may follow: combining expertise across sectors to develop shared infrastructure while maintaining data control. As AI workloads grow, both public and private organizations need to build systems that balance power, performance, and governance.
The Lux and Discovery projects show what that balance looks like in practice. That means it’s open, collaborative, and built to support discovery at scale. This is a lesson in how advanced AI strategies can transform infrastructure into a long-term competitive advantage.
(Photo provided by Saeed Ali)
See also: How to fix the AI trust gap in business
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