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 research in science, energy, and national security — and strengthen the nation’s position in high-performance computing.
The two machines represent about $1 billion in public and private investment. Once complete, they will form part of a secure national computing network designed to support AI research using standards-based infrastructure built in the US. The project reflects how a coordinated AI strategy can align national goals in innovation, energy efficiency, and data governance.
Dr Lisa Su, AMD’s chair and CEO, said the company is “proud and honoured to partner with the Department of Energy and Oak Ridge National Laboratory to accelerate America’s foundation for science and innovation.” She added that the systems “will leverage AMD’s high-performance and AI computing technologies to advance the most critical US research priorities in science, energy, and medicine.”
Lux AI: Training the next wave of AI models
Set to go live in early 2026, Lux AI will be the country’s first “AI Factory” — a facility built to train and deploy advanced AI models for science, energy, and security. The system is being developed with ORNL, AMD, Oracle Cloud Infrastructure, and Hewlett Packard Enterprise.
Lux will use AMD Instinct MI355X GPUs, EPYC CPUs, and Pensando networking to handle data-heavy AI tasks. It’s 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 keeping data secure and separate, a model that mirrors how many large organisations are starting to manage sensitive AI workloads.
Discovery: Strengthening America’s AI and supercomputing strategy
The Discovery system will follow in 2028 and become the DOE’s next flagship supercomputer at Oak Ridge. It will use AMD’s upcoming “Venice” EPYC processors and MI430X GPUs, which are part of a new series built for AI and scientific computing.
Discovery’s “Bandwidth Everywhere” design increases memory and network performance without using more power. This means it can process more data and run complex models efficiently while maintaining energy costs — a challenge many large data centres also face today.
The system builds on lessons from Frontier, the world’s first exascale computer, ensuring that existing applications can move easily to the new platform.
U.S. Energy Secretary Chris Wright said, “Winning the AI race requires new and creative partnerships that will bring together the brightest minds and industries American technology and science has to offer.” He said the new systems show “a commonsense approach to computing partnerships” that strengthen the country through shared innovation.
ORNL Director Stephen Streiffer said Discovery will “drive scientific innovation faster and farther than ever before,” adding that combining high-performance computing and AI can shorten the time between research problems and real-world solutions.
Partnerships driving AI innovation and long-term strategy
AMD, HPE, and Oracle each play key roles in building and supporting the systems. Antonio Neri, HPE’s president and CEO, said the collaboration will help Oak Ridge reach “unprecedented productivity and scale.” Oracle’s executive vice president Mahesh Thiagarajan said the company is working with DOE to “deliver sovereign, high-performance AI infrastructure that will support the co-development of the Lux AI cluster.”
When operational, Lux and Discovery will help the DOE run large-scale AI models to improve understanding in energy, biology, materials science, and national defence. Discovery will also help design next-generation batteries, reactors, semiconductors, and critical materials.
What it means for enterprise leaders
For organisations, these systems highlight how AI strategy and HPC can deliver faster research, improved efficiency, and secure data management. They also show that performance gains don’t have to come at the cost of higher energy use.
The DOE’s partnerships with technology providers reflect a model that private enterprises may follow — combining expertise across sectors to develop shared infrastructure while maintaining data control. As AI workloads grow, both public and private organisations will need to build systems that balance power, performance, and governance.
The Lux and Discovery projects show how that balance might look in practice: open, collaborative, and built to support discovery at scale — a lesson in how a forward-thinking AI strategy can turn infrastructure into long-term competitive advantage.
(Photo by Syed Ali)
See also: How to fix the AI trust gap in your business
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