Machine Learning Physics Guess – Electromagnetic Induction As A Supervised Learning Problem? Electro-Sounds Would Travel Faster Than Electricity

The power guess is that all our physics must be viewed in the light of supervised learning. So there exist explanation and progress value in looking at all the old physics.

So this should then apply to electromagnetic induction. The reason would be to develop super generators and engines.

My guess is that from looking at force diagram between two magnets. It looks like a loss function. It goes to zero in a typical machine learning loss fashion.

So invert that word and you get that there could exist an Iteration potential.

That is. Something iterates when the forces are high. It could be electron iteration maybe.

Some problems from looking at Faradays law of induction.

Since you integrate. I wonder if you then loose information. I imagine the magnetic field changes are like heat mirage lines and not perfect. Then could all summations be like machine learning decision results. Some technical loss of some kind.

The supervised learning then should come in the differential equation. That is. You have some prediction and a current value. I got this from the definition of the derivative.

Since electricity then is about iterations. I imagine it could buzz some kind of sounds. In some other dimensions maybe? I choose sound over light since sounds require less energy to produce. So how could the universe use sounds? Inspired life. Localization and communication could be a reason. To inform what is happing.

So this can also be supervised learning. If that particular sound goes faster than the electricity it could provide supervised learning data.