IN-ML-OUT Project

The switch to renewable energy sources is a central issue for the future of our society and an important part of global strategies to reduce CO₂ emissions and counteract climate change. An active dialogue between research, society and politics is particularly important. This is exactly where the exhibit “IN-ML-OUT” comes in: it is designed as a starting point for this dialogue. The project is based on a cooperation between the Cluster of Excellence "Machine Learning: New Perspectives for Science" at the University of Tübingen, the "Center for Rhetorical Science Communication Research on Artificial Intelligence" (RHET AI) and the “State Academy of Fine Arts” in Stuttgart.

Renewable energy production depends on the weather and is therefore also affected by climate change. If we want to make optimal use of renewable energy sources, we need predictions that are as accurate as possible. This is precisely where modern machine learning algorithms can help.

The exhibit makes it clear that our actions influence the climate, which solutions researchers can support with the help of machine learning and which initiatives and projects for renewable energies already exist. To this end, it brings science and design together - and transfers the model aspects of "input", "machine learning" and "output" into three connected exhibition pieces that creatively invite you to discover, reflect and discuss.