Nuclear energy could power the AI boom—but only if proliferation risks are minimized

July 1, 2024
Miles A. Pomper, Yanliang Pan

The following is an excerpt from the Bulletin of the Atomic Scientists.

On May 10, Oklo Inc., a nuclear energy startup, began trading on the New York Stock Exchange. The chairman of the company is none other than Sam Altman, the CEO of the artificial intelligence leader, OpenAI, that launched the generative AI revolution with the release of ChatGPT late in 2022. The staggering language, image, and video processing capabilities of ChatGPT and other similar chatbots depend on large language models (LLMs) trained through computations of data at unprecedented scale. Computational power has thus become, in Sam Altman’s words, “the currency of the future” and “the most precious commodity in the world.”

The training and use of LLMs require huge amounts of electrical power and cascades of advanced microchips. Altman’s nuclear investment reflects his belief that Oklo’s microreactors can satisfy the future power requirements of AI models. In some ways, the compatibility is intuitive. Large data centers, especially those set up in remote areas with greater land availability, require power sources that avoid both the intermittency of renewables and the fuel delivery requirements of traditional thermal power plants. Such is Oklo’s narrative as it touts recent power purchase agreements with data center operators such as Wyoming Hyperscale.

But the intuitive compatibility between AI and nuclear power does not exempt the latter from traditional concerns about economics and safety, despite efforts by Oklo and other vendors of “advanced” reactors to downplay those concerns. The escalating costs of NuScale’s first VOYGR plant have cast into doubt the economics of small modular reactors, and the US nuclear regulator has yet to endorse the safety of Oklo’s Aurora microreactor, having denied its combined license application in early 2022.

Continue reading at the Bulletin of the Atomic Scientists.

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