According to current ideas about String Theory, is that the standard model is but one vacuum in millions of the theory.
It strikes me that to find the correct vacuum and search through all the possibilities is something that a neural network would be very good at.
We might not be able to solve it with gradient descent if the vacuums are discrete entities not joined by a continuum. But other methods of training the neural network could be used.
Has anyone tried to use neural networks or genetic algorithms to try to find the correct vacuum for String Theory or is the math just too difficult?