The U.S. Department of Energy (DOE) has announced four locations for the development of AI infrastructure using DOE lands. DOE has selected Idaho National Laboratory, Oak Ridge Reservation, Paducah Gaseous Diffusion Plant and Savannah River Site and plans to move forward with plans to invite private sector partners to develop AI data center and energy generation projects.
The announcement is meant to support President Trump’s Executive Orders on Accelerating Federal Permitting of Data Center Infrastructure, Deploying Advanced Nuclear Reactor Technologies for National Security, and Unleashing American Energy. The goal is to utilize Federal lands to lower energy costs and help power the global AI race.
“By leveraging DOE land assets for the deployment of AI and energy infrastructure, we are taking a bold step to accelerate the next Manhattan Project—ensuring U.S. AI and energy leadership,” said Energy Secretary Chris Wright in a statement. “These sites are uniquely positioned to host data centers as well as power generation to bolster grid reliability, strengthen our national security, and reduce energy costs.”
The DOE said it chose the locations because they are well-situated for large-scale data centers, new power generation, and other necessary infrastructure. It will work with data center developers, energy companies, and the broader public to advance the initiative, and is also evaluating additional sites for future expansion.
The DOE may seem an odd choice to lead such an initiative, since its mission is to provide for the energy security and prosperity of the United States. A more logical choice would seem to be the Commerce Department or perhaps the National Science Foundation, which played a role in the early development of the Internet.
But industry executives say that this is a natural fit for the DOE. The DOE’s extensive experience with hyperscale computing provides it with a distinct advantage in AI infrastructure deployment, as it has already pioneered the operational and engineering protocols for managing systems with exascale power and energy demands, says Nic Adams, co-founder and CEO of AI security firm 0rcus.
“The DOE is positioned to lead on advanced AI infrastructure due to its historical mandate and decades of expertise in extreme-scale computing for mission-critical science and national security challenges,” he said. “National labs are central hubs for advancing AI by providing researchers with unparalleled access to exascale supercomputers and a vast, interdisciplinary technical workforce.”
“The Department of Energy is actually a very logical choice to lead on advanced AI data centers in my opinion,” said Wyatt Mayham, lead consultant at Northwest AI, which specializes in enterprise AI integration. “They already operate the country’s most powerful supercomputers. Frontier at Oak Ridge and Sierra at Lawrence Livermore are not experimental machines, they are active systems that the DOE built and continues to manage.”
These labs have the physical and technical capacity to handle the demands of modern AI. Running large AI data centers takes enormous electrical capacity, sophisticated cooling systems, and the ability to manage high and variable power loads. DOE labs have been handling that kind of infrastructure for decades, says Mayham.
“DOE has already built much of the surrounding ecosystem,” he says. “These national labs don’t just house big machines. They also maintain the software, data pipelines, and research partnerships that keep those machines useful. NSF and Commerce play important roles in the innovation system, but they don’t have the hands-on operational footprint the DOE has.”
And Tanmay Patange, founder of AI R&D firm Fourslash, says the DOE’s longstanding expertise in high-performance computing and energy infrastructure directly overlap with the demands we have seen from AI development in places.
“And the foundation the DOE has built is essentially the precursor to modern AI workloads that often require gigawatts of reliable energy,” he said. “I think it’s a strategic play, and I won’t be surprised to see the DOE pair their ‘AI for science’ initiatives to accelerate everything from battery materials to fusion energy in the days to come.”
Source:: Network World