Two-Day Workshop on AI-Assisted Productivity

HyperMet hosted a two-day workshop titled “Next Level Productivity using AI Assistants”, led by Dr. Daniel Mertens, biochemist, lecturer, and group leader at the German Cancer Research Center and the University of Ulm, and part-time trainer with Schiller & Mertens. The workshop introduced the development of large language models (LLMs) and addressed current challenges, risks, and data protection considerations. Dr. Mertens outlined the strengths and limitations of different LLMs and demonstrated how outputs from one model can be strategically used as input to another to improve the quality of the results. He also discussed institutional guidelines for text generation and review, including regulations set by different organizations.

To tailor the workshop to the participants,  several applied sessions followed. These included LLM-supported literature searches, workflows combining multiple tools, the setup and use of local LLMs for work with sensitive data, and hands-on data analysis from raw Excel tables to final visualizations. An additional segment focused on project management, specifically for the HyperMet research unit. The workshop concluded with an overview of teaching, training, and the development of lecture material in the context of LLM technologies.

For the participants, the workshop provided a comprehensive introduction to practical LLM applications and offered concrete strategies for integrating AI-based tools into research, data handling, and academic communication.

HyperMet research examines the impact of muscle growth (hypertrophy) and muscle loss (atrophy) on metabolism. Increased muscle mass reduces the risk of obesity, diabetes, osteoporosis, and potentially cancer. We are exploring the underlying metabolic processes to develop new strategies for prevention and everyday life.