Abstract <p>Multiscale modeling is essential for understanding the complex behavior of materials. However, accurately transferring all relevant information from one scale to another has remained an outstanding challenge. Neural operators, discretization-independent generalizations of neural networks, are proving to be a powerful tool in addressing this challenge. This article provides an introduction to neural operators, and illustrates their use in multiscale modeling of materials through three selected examples.</p> Graphical abstract <p></p>