Yeah, I'll disagree. I work in the field and classic control algorithms are incredibly pervasive and are in no risk of being supplanted. Linear quadratic esti

Yeah, I'll disagree. I work in the field and classic control algorithms are incredibly pervasive and are in no risk of being supplanted. Linear quadratic estimators, Kalman filters, are still used everywhere. Extended Kalman filters are still the standard for navigation systems and GPS. Only a very slight change to linear quadratic estimators gives linear quadratic regulators and these are used just about everywhere. Power flow problems are solved using LQR controls, which is basically our entire power grid. Hell, even my Dad's grill uses simple control algorithms like a PID controller because it works well. Look, I'm happy that machine learning is hot and it's an interesting research area with some good applications. That said, it's ridiculous to assert that all of the sudden that all of these mature fields are dead. Control algorithms will always have a place because these dynamical systems are based on classical mechanics, which are really accurate for an extremely broad section of the world that we care about. Machine learning algorithms build models using generic functions that don't have information about the underlying physics. Now, could there be hybrid approaches? Absolutely. However, till that point, having an algorithm that works directly on the kinematics of the model is a huge advantage and that's not going anywhere anytime soon.