You have read extensively that companies building data centers for artificial intelligence that demand massive amounts of electricity are considering reopening or building new nuclear power facilities. The problem with those facilities is that they take years, even decades, to finish because the permitting process is so difficult. Now, efforts are underway to use artificial intelligence to guide companies through the complex nuclear permitting process. One company working on the problem is Atomic Canyon, which, in conjunction with Oak Ridge National Laboratory, has developed an AI model “capable of understanding complex nuclear terminology,” according to Aaron Larson at Power Magazine. He writes:
“The first thing you need to build artificial intelligence is a data set—you need access to information,” Trey Lauderdale, founder and CEO of Atomic Canyon told POWER. Lauderdale is not a nuclear expert, but he has founded and supported multiple companies over the past 15 years with a focus on utilizing technology to improve processes, which is what Atomic Canyon’s AI platform is designed to do for nuclear power plants, manufacturers of next-generation reactors, and government and national laboratories.
“One thing we quickly realized about nuclear power is there is a tremendous amount of data. The Nuclear Regulatory Commission—the NRC—actually has a database called ADAMS [which stands for Agencywide Documents Access and Management System], where there’s all sorts of public information that’s available that can be viewed by anyone, and it’s all available on their website,” Lauderdale said.
As Atomic Canyon’s team started building AI models and experimenting with the ADAMS dataset, its experts quickly discovered a problem: all of the AI models that are generally available would get confused when they ran into “nuclear words.” Lauderdale explained, “The nuclear vernacular is very complex. It has all sorts of acronyms and words that these AI models haven’t seen enough examples of. So, what ends up happening is the AI hallucinates. That’s AI speak for: ‘It makes stuff up.’ As you can imagine, in an industry like nuclear, making stuff up is very, very bad.”
Lauderdale’s team realized they didn’t necessarily need to create a new large language model (LLM) to solve the problem, they just needed to build sentence-embedding models for AI applications so nuclear terminology could be understood. “To do that, you need access to a lot of what’s referred to as GPUs—graphical processing units,” Lauderdale said.
A typical start-up might raise millions of dollars and buy a bunch of GPUs to do a project like this, but Atomic Canyon had a better option: work with the government. ORNL is home to Frontier (Figure 1), a supercomputer that was touted as the world’s fastest when it debuted in May 2022 and has maintained that title through the most recent rankings in May 2024. “It was quickly discovered that this was a project that was worthwhile of the world’s fastest supercomputer—the ability to go train AI models on nuclear terminology and then have an output which is basically a more advanced search application that could be used to help find documents,” Lauderdale said.
Atomic Canyon isn’t the only company working on using AI for the nuclear permitting process. Software giant Microsoft is attempting a similar approach. Lee Harris reports in the Financial Times:
NRC spokesperson David McIntyre said the agency had made strides in efficiency. He pointed to a new facility being developed by Kairos Power in Tennessee, the Hermes 2 test facility, whose construction permit was approved last week in a process that took under 18 months. Last month, Google announced a deal with California-based Kairos to build small modular nuclear reactors.
The Hermes 2 licence was approved “much quicker than previous reviews”, McIntyre said, “by leveraging our work on the first Kairos application and taking innovative approaches to some of our required actions”.
Microsoft has partnered with Terra Praxis to train AI models on nuclear regulatory and licensing documents, as well as geographical and seismic data, to streamline the process of preparing applications for regulatory review. Terra Praxis said the AI tool it has built with Microsoft can cut the time to produce early application drafts from years to hours or days.
McIntyre said the NRC was “actively exploring potential uses of AI, including possibly Microsoft’s, to improve the efficiency of agency processes”.
Action Line: If AI can solve nuclear permitting, it could potentially save itself by making electricity less expensive. Click here to subscribe to my free monthly Survive & Thrive letter.
