Physics is deterministic in states and always tends towards an equilibrium, so novel results from DL may still fit some continuum math model without being stabl

Physics is deterministic in states and always tends towards an equilibrium, so novel results from DL may still fit some continuum math model without being stable or even real. Domain expertise, on the other hand, helps prepare data for ML algos in such a way that results will come (or not) within the boundaries of reality and hopefully stability. I am trying both approaches for some materials science goals of mine and am curious to see what happens, now that powerful hardware is cheap enough on the cloud to put some ideas to work. Side point is all this was just impossible five years ago, so I am grateful and excited to have this opportunity.