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There was a Quanta Magazine article talking about predicting the evolution of a flame-front using ML. The ML algorithm remained accurate for eight Lyapunov intervals; eight times longer than the previous SOTA.

https://www.quantamagazine.org/machine-learnings-amazing-abi...

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The only real argument I think you can make is that it might be more efficient to have a neural network quickly spit out an approximate solution instead of solving the actual equations.

But if you have the time having the actual equations is more valuable?

Assuming that "having the actual equations" is possible, which in market predictions it most likely is not.

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