Unlocking Neural Network Parameters

Walt and Kyle discuss the surprising results of a study on neural networks, where the combination of regularization constraints and the Leapshift constraint led to unexpected accuracy and robustness gains. They explore the trade-off between robustness and accuracy, and the potential for unlocking network parameters to improve both.