[sudosysgen]

Yes, I'm also using it in the figurative sense. It's not a regression model, the models are developped and then the data is sought out to infirm them. It's the reverse for a regression technique. The model being generated before the data that can support it is a big part of how humans come up with these models and it's fundamentally different in many ways.

[XorNot]

What are you talking about? If scientific models aren't developed based on data, then what are they developed based on? Divine inspiration?

No. Very obviously no. The multi-post diversion about Kepler's laws is explicitly evidence to the contrary since Kepler's laws are a curve fitting exercise which matches astronomical data in a specific context but doesn't properly describe the underlying process - i.e. their predictive power vanishes once the context changes. But they do simplify down to Newton's Law once the context is understood.

New data is sought out for models to determine whether they are correct because a correct model has to explain existing data and predict future data. The Bohr Model of the atom was developed because it explained the emission spectra of hydrogen well. It's not correct because it doesn't work anything but hydrogen...but it's actually correct enough that if you're doing nuclear magnetic resonance (which is very hydrogen-centric for organic molecules) then it is in fact good enough to predict and understand spectra with (at least in 1D, 3D protein structure prediction is it's own crazy thing).

This is the entire point of deep learning techniques. The whole idea of latent space representations is that they learn underlying structural content of the data which should include observations about reality.

[sudosysgen]

That's not how the scientific process works. You use your intuition to make a theory, sometimes loosely based on data, and then you come up with an experiment to test it.

We both agree that Kepler was trying to fit curves. But that's not what Newton was trying to do. Newton was trying to explain. Newton's model did not fit the data better than Kepler's model until far after they both died.

Newton's model, to Newton had more loss than Kepler's model.

But it turned out 70 years later that Newton's model was better, because it's only then that there was any data for which it was a better prediction.

You're similarly wrong about Bohr. If all you were interested was to find the emission spectra of hydrogen, there's absolutely no reason you'd try to come up with the Bohr model. Why? Because Rydberg already made a formula that predicted the emission spectra of Hydrogen, 25 years earlier.

The entire point of Bohr's model and of Newton's model is that they weren't empirically better at predicting the phenomena. Indeed, simple curve fitting came up with equations that are far better in practice, earlier.

But they were better at explaining the phenomena.

And that only became relevant because after we had these models, we came up with new experiments, informed by these models, which helped us understand them and eventually push them behind the breaking point.

It's not a curve fitting experiment. We already had better curve fitting models far before either of those was invented. If your goal was to reduce the loss, they'd be useless and there would be no point coming up with them.

That's the difference between the scientific method and mere regression.

[XorNot]

> That's not how the scientific process works. You use your intuition to make a theory,

Go ahead and define what "intuition" is? Why do people have it? Why is some people's intuition better then others?

[YeGoblynQueenne]

(Not the OP) We don't know ho;w the human mind works, or how "intuitions" or "inspiration" come about, but that's no reason to call them "metaphysics". Clearly, they are physical processes that somehow take place in the human brain.

The questions you ask in this comment are good questions, for which we have no good answers. That doesn't mean there's anything supernatural going on, or that anyone is assuming something supernatural is happening. We just don't know how human scientists come up with new hypotheses, that's all there is to it.

But it's not like there's some kind of principled way to do it. There's no formulae, no laws, where we can plug in some data and out pops a hypothesis ready for the testing. Maybe we will find how to define such laws or formulae at some point, but for now, all we got is some scientist waking up one day going "holy cow, that's it!". And then spending the next ten years trying to show that's what it really is.