Sandra Goettisheim, KIT

Artificial intelligence (AI) can play a key role in the energy transition. To ensure its reliable application, its methods must be transparent and comprehensible. This is the goal pursued by the Helmholtz Investigator Group “Data-Driven Analysis of Complex Systems” (DRACOS), led by Tenure-Track Professor Benjamin Schäfer, which was evaluated and rated by KIT’s Executive Board as “extraordinarily successful.” Schäfer’s goal is to make AI models used to analyze large volumes of data from energy systems more transparent. Until now, it has often been unclear which factors an AI uses to predict household energy consumption.

Markus Götz, KIT

Wildfires, floods and droughts: a new artificial intelligence (AI) from KIT promises to be a game-changer in providing more precise, faster, and energy-efficient predictions of such events. In the "WOW - a World model of Our World" project, researchers will develop an AI world model that combines multiple specialized AI sub-models through shared “latent spaces”. "Modern AI methods can not only cost-effectively imitate physics-based simulations, but can even learn correlations directly from observational data," says project coordinator Peer Nowack. The Carl Zeiss Foundation is funding the project with six million euros.

Moritz Wolf, KIT

In 2025, four YIN members took part in the varied program of the "Night of Science". Frank Rhein used the example of the cryptocurrency Bitcoin to show how vast amounts of electricity can be saved by replacing digital computing puzzles with physical processes. Julian Thimme explained which strategies really work when buying shares. Moritz Wolf presented chemical catalysts as the hidden heroes of our world and the energy transition. And Somidh Saha showed how digital twins can improve the sustainable management of urban trees. "The Night of Science" is organized by a student group since 2016.