if there is only one global minima corresponding to the to the ground true with finite probability well then the gradient descent also goes there so this means that the gradient descent solved this problem by optimizing this loss function corresponding to the over parameterized neural network starting from alpha equal to and here is just a little plot that you know that shows that just running numerically writing descend on relatively small systems is pretty consistent with that result so if i put that back into onto undo the