LLM Workshop in Ulm: DLR-wide knowledge exchange on AI language models

At a glance
The programme combined contributions from research and development with a close focus on the user perspective. This is because AI language models, through their increasingly human-like interaction, will have a lasting impact not only on everyday scientific life but on society as a whole – regardless of whether people are researchers, developers or simply users.
The annual LLM Knowledge Exchange Workshop recently took place at the DLR site in Ulm – a key platform for cross-institutional knowledge transfer on AI language models within the DLR. More than 100 staff members from various DLR institutes and facilities accepted the invitation and spent three days discussing current developments relating to Large Language Models (LLMs).
The programme combined contributions from research and development with a close focus on the user perspective. This is because AI language models, through their increasingly human-like interaction, will have a lasting impact not only on everyday scientific life but on society as a whole – regardless of whether people are researchers, developers or simply users.
As a research organisation, the DLR is aware of this responsibility. In the highly dynamic and competition-driven environment of AI development, it is essential to create secure and reliable solutions. Issues relating to copyright, cybersecurity and the protection of personal data were therefore just as much on the agenda as technical and scientific topics.
Laboratory tours rounded off the programme and offered colleagues from other DLR sites insights into quantum research and the fields of AI security at the Ulm site. External experts complemented the programme with their contributions and enriched the cross-institutional discussion.
The Knowledge Exchange Workshop thrives on the voluntary commitment of its participants – a heartfelt thank you to everyone involved who contributed both substantively and organisationally.
Let’s continue to exchange ideas in interdisciplinary working groups until the next WAW LLMs!