[swell36]

Honestly, modern ML models are extraordinarily messy. They are inefficient, unreliable (when the goal is perfect reliability), often misused, mostly unexplainable, and very much a "throw the spaghetti at the wall to see what sticks" type of problem solving.

Kalman filters, and other similar digital filtering and prediction algorithms, are like scalpels compared to the broadsword of NNs and such. There are plenty of things that you can't or shouldn't use a kalman filter for, but for the tasks that it is suited for, you cannot do better with another solution. ML is mostly hand wavy bullshit, and DSP algorithms are like... doing real math, real engineering.