Just like how humans can learn from mistakes, so can neural networks. When a calculation differs from the expected solution, a neural network can determine this error and minimize it through further tries. That means: to find the minimum of the error function (its deepest spot where the treasure chest is in our game). This minimum is approximated by samples (here: sending down probes). “Gradient Descent” is the name of this method and it is used to identify a local or ideally a global minimum. It is one of the most important methods of AI.