The Deep Underground Neutrino Experiment (DUNE), a massive detector being built a mile underground in South Dakota, will use artificial intelligence to catch elusive particles. Researchers are developing AI systems to sort through huge amounts of data, identify neutrino interactions, spot signs of a stellar explosion, and detect problems inside the detector. This could fundamentally change how scientists run a particle-physics experiment at DUNE’s scale, with AI identifying important events in near real time. “These approaches are going to really accelerate DUNE in terms of the commissioning process and the sensitivity of the experiment to reach our full discovery potential,” said Sowjanya Gollapinni, a representative from DUNE. Fermilab will generate a powerful neutrino beam that will travel to a detector at the Sanford Underground Research Facility in South Dakota, where chambers filled with liquid argon will record traces left when neutrinos collide with argon atoms. Each of DUNE’s two planned far-detector cryostats will house about 17,000 tons of liquid argon, kept at roughly −300°F. The MicroBooNE experiment was among the first high-energy physics experiments to use deep neural networks to analyze images from a liquid-argon detector. DUNE is now taking that approach further. “We are going to have very high resolution, almost photographic-quality images of these interactions. Which is great, but also brings challenges such as making reconstruction more difficult because we see such fine detail,” said Leigh Whitehead, an AI expert at DUNE