Can machine learning improve computer models enough to ignite internal-confinement fusion? Machine learning applied to the University of Rochester's OMEGA laser increased fusion yields; the same could happen at the National Ignition facility (NIF), too.

The article reports that Laser-fusion research have turned to machine-learning techniques to seek the combinations of laser pulse characteristics and target design to optimize target implosions for inertial confinement fusion. It mentions the ultimate goal being net energy gain, producing more energy from fusion than needed to drive the fusion process, and the U.S. Department of Energy shifted more National Ignition Facility (NIF) time for experiments prospects for ignition with NIF in 2020.