Earth system models are the most important tools for quantitatively describing the physical state of Earth, and—for example, in the context of climate models—predicting how it might change in the future under the influence of human activities. How the increasingly used methods of artificial intelligence (AI) can help to improve these forecasts and where the limits of the two approaches lie has now been investigated by an international team led by Christopher Irrgang from the German Research Centre for Geosciences Potsdam (GFZ) in a Perspectives article for the journal Nature Machine Intelligence. One key proposal: To merge both approaches into a self-learning "neural Earth system modeling."