MCML PI Reinhard Heckel About the Importance of Data in AI

TUM Research

In this interview, MCML PI Reinhard Heckel discusses the importance of data in the context of AI. He explains why data is the crucial component for generative AI, which methods can be used to prevent biases, and how data protection should be approached in the context of AI.

Learn more

#research #heckel

Subscribe to RSS News feed

24.02.2026

Cosmology: Measuring the Expansion of the Universe With Cosmic Fireworks

Daniel Gruen leads LMU’s campaign on rare SN Winny to refine the Hubble constant and address the Hubble tension in cosmology.

19.02.2026

COSMOS – Teaching Vision-Language Models to Look Beyond the Obvious

Presented at CVPR 2025, COSMOS shows how smarter training helps VLMs learn from details and context, improving AI understanding without larger models.

05.02.2026

Daniel Rückert and Fabian Theis Awarded Google.org AI for Science Grant

Daniel Rueckert and Fabian Theis receive Google.org AI funding to develop multiscale AI models for biomedical disease simulation.

05.02.2026

Needle in a Haystack: Finding Exact Moments in Long Videos

ECCV 2024 research introduces RGNet, an AI model that finds exact moments in long videos using unified retrieval and grounding.

04.02.2026

Benjamin Busam Leads Design of Bavarian Earth Observation Satellite Network “CuBy”

Benjamin Busam leads the scientific design of the “CuBy” satellite network, delivering AI-ready Earth observation data for Bavaria.

MCML PI Reinhard Heckel About the Importance of Data in AI

TUM Research

Related