24.10.2024
©MCML
MCML-Exhibition at Deutsches Museum
Long Night of Munich Museums
More than 1.000 visitors passed by the Science Communication Lab in the Museum during the Long Night of Munich Musuems. Our MCML researchers Mariia Gladkova, Tarun Yenamandra, Mateo de Mayo, Mia Brandtner and Qadeer Khan were on site providing insights on their research and answered all the questions related to AI.
With the AMELIE exhibit, the MCML invited visitors to learn about the basics of machine learning in a playful and interactive way. On a big, illustrated canvas we showed how AI works and explained the difference between AI and Machine Learning. The Canvas was designed by Laura Ekes.
In a second demo, we showed how it is possible to simultaneously localize and map the environment using a camera and a connected IMU sensor. The method is called DM-VIO and can be used in self-driving cars, for example.
We also provided an insight into Stable Diffusion, a deep learning model that generates images from text descriptions. We explained how Stable Diffusion learns the connection between image and text through a latent diffusion model process and invited the visitors to try out Stable Diffusion for themselves.
For the 25th year, 'More museum for everyone!' brought together over 100 institutions, creating a night filled with art, culture, science, and technology.
Related
12.11.2026
Welcoming New Junior Members at the MCML Onboarding and Stammtisch
MCML welcomed new Junior Members at its onboarding event, followed by the November Stammtisch at Atzinger.
12.11.2026
One Toolbox for Many Kinds of Uncertainty
MCML researchers introduce probly, a unified Python package for uncertainty-aware machine learning, presented orally at NeurIPS 2026.
09.11.2026
Outstanding Paper Award at EMNLP 2026 for Work on Accent Bias in Audio Language Models
A paper co-authored by MCML PI Valentin Hofmann on accent bias in audio language models won an Outstanding Paper Award at EMNLP 2026.