Princeton’s Fusion Recurrent Neural Network (FRNN) code uses convolutional and recurrent neural network components to integrate both spatial and temporal information for predicting disruptions in tokamak plasmas with unprecedented accuracy and speed on top supercomputers. (Image: Eliot Feibush, Princeton Plasma Physics Laboratory)