Home  | News

14.11.2023

Teaser image to We are not taking part in the scaling race with our algorithms

We Are Not Taking Part in the Scaling Race With Our Algorithms

LMU News

In this interview our PI Björn Ommer shares his opinion about the current development of Large Language Models. He talks about the problematic of computing power in AI, the importance of data security and how Germany could potentially solve these problems.

«Usually buried in the operators’ small print is the fact that any data entered by users is going to be used for the operators’ own interests, for example to train the LLMs. Companies with extremely sensitive data, like in the medical sector, cannot tolerate that.»


Björn Ommer

MCML PI

#research #ommer
Subscribe to RSS News feed

Related

Link to Needle in a Haystack: Finding Exact Moments in Long Videos

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.

Read more
Link to Benjamin Busam Leads Design of Bavarian Earth Observation Satellite Network “CuBy”

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.

Read more
Link to Cracks in the foundations of cosmology

30.01.2026

Cracks in the Foundations of Cosmology

Daniel Grün examines cosmological tensions that challenge the Standard Model and may point toward new physics.

Read more
Link to How Machines Can Discover Hidden Rules Without Supervision

29.01.2026

How Machines Can Discover Hidden Rules Without Supervision

ICLR 2025 research shows how self-supervised learning uncovers hidden system dynamics from unlabeled, high-dimensional data.

Read more
Link to Matthias Nießner Co-Founds AI Startup Synthesia

28.01.2026

Matthias Nießner Co-Founds AI Startup Synthesia

Julien Gagneur comments on DeepMind’s AlphaGenome, highlighting its precision and remaining challenges in genome prediction.

Read more
Back to Top