If the neural network makes a mistake, a special algorithm adjusts its internal parameters so that the next result is better. This process is repeated thousands or even millions of Gates of Olympus Super Scatterplay gates of olympus super scatter times. Gradually, the number of errors decreases, and the model starts to produce more accurate results. This approach is called supervised learning, but there are other types as well, such as unsupervised learning and reinforcement learning.