Neural Networks

Computational systems inspired by the structure and function of the human brain. They consist of interconnected nodes, or 'neurons', which transmit signals to one another, adjusting the strength of these connections based on experience and feedback. When data is fed into a neural network, it passes through multiple layers, each transforming the information in increasingly abstract ways. Early layers may detect simple patterns, while deeper layers identify more complex structures or relationships. Through a process called training, the network learns by comparing its outputs to expected results, gradually tuning its connections to minimize errors.

This allows the system to generalize from examples, recognize patterns, make predictions, or generate new content. In the context of music or other creative tasks, neural networks can internalize styles, harmonies, and rhythms from vast datasets, producing outputs that reflect learned patterns while still allowing novel combinations and variations.