Researchers are exploring the use of machine learning to improve density functionals, which are used to predict electronic structure. Various approaches are being developed, including hybrid functionals and those based on neural networks, to enhance the accuracy of these predictions. The applications of this work may include materials science, nanomaterials, and drug discovery, among other fields.