25.08.2026
David Rügamer: We Need Uncertainty Quantification
Research Film
What if your AI model could tell you not just what will happen, but how sure it is?
«If you can quantify the uncertainty of the AI model, then decision-makers know to what extent they can trust the model»
David Rügamer
MCML PI
MCML PI David Rügamer explains why uncertainty quantification is one of the most important concepts in AI, and why knowing the limits of a model’s confidence is the key to actually trusting it. From flood forecasting to everyday decision-making, he makes the case that knowing how certain a model is can be just as important as the prediction itself.
In this video series, discover how MCML researchers are bridging theory and practice to build AI systems that prioritize accessibility, sovereignty, and impact.
©MCML
The film was produced and edited by Nicole Huminski and Nikolai Huber.
Related
23.10.2026
MCML at EMNLP 2026
MCML researchers are represented with 33 papers at EMNLP 2026 (21 Main, 11 Findings, and 1 Workshop).
15.10.2026
When Flatter Is Not Always Better
In their ICML 2026 paper, MCML researchers show why the flattest regions found during neural network training are not always the best.
