Designing a material, unlike designing a bridge or a car, still relies mainly on trial and error. The recent advances in artificial intelligence came with the promise to make computational materials design viable. By machine-learning the expensive quantum-mechanical calculations, it is possible to create accurate models with which materials can be simulated and prescreened in a high-throughput manner. In our lab, we develop such algorithms and apply them in academic and industrial research.