  In this article the Lorenz dynamical system is revived and revisited and the
current state of the art results for one step ahead forecasting for the Lorenz
trajectories are published. Multitask learning is shown to help learning the
hard to learn z trajectory. The article is a reflection upon the evolution of
neural networks with respect to the prediction performance on this canonical
task.
