While AI chatbots grab most of the attention, deep learning is also quietly revolutionizing science and engineering. A new AI model that can help predict the outcome of fusion power experiments could accelerate the technology’s arrival.
Achieving nuclear fusion involves some of the most extreme conditions known to nature, which makes designing and operating fusion reactors incredibly challenging. Simulations of key processes typically require huge amounts of time on supercomputers and are still far from perfect.
But AI is starting to accelerate progress in this area. Google DeepMind made headlines in 2022 when it trained a deep-learning model to control the roiling plasma inside a fusion reactor. And now, the scientists behind the first fusion experiment to show a net gain of energy have revealed that, thanks to AI, they were already pretty confident of success before they flicked the switch.
In a new paper in Science, researchers at Lawrence Livermore National Laboratory outline a generative machine learning model that they used to predict a 74 percent chance the experiment at the US National Ignition Facility would lead to net energy gain. The team say having an accurate prediction model could accelerate the design of new experiments and help them make decisions about how to upgrade hardware.
“This outcome demonstrates a promising approach to predictive modeling of ICF experiments and provides a framework for developing data-driven models for other complex systems,” write the authors.
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