The GP implies that was not tried before: "There was a revolution, when they started using backpropogation to optimize the gradient search". "Back-propagation

The GP implies that was not tried before: "There was a revolution, when they started using backpropogation to optimize the gradient search". "Back-propagation allowed researchers to train supervised deep artificial neural networks from scratch, initially with little success. Hochreiter's diploma thesis of 1991[1][2] formally identified the reason for this failure in the "vanishing gradient problem", which not only affects many-layered feedforward networks,[3] but also recurrent networks." https://en.m.wikipedia.org/wiki/Vanishing_gradient_problem https://en.m.wikipedia.org/wiki/Vanishing_gradient_problem