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Scaling laws for distributed random forests: New insights from Helmholtz AI researchers at KIT

Random forests are among the most widely used machine learning methods for tabular data, valued for their robustness, interpretability, and strong performance across many scientific domains. As…

Helmholtz AI Annual Retrospective and Award Ceremony 2025

Another year has come to an end, and in December 2025 the Helmholtz AI community once again came together virtually for the Annual Retrospective and Award Ceremony to reflect on a year of remarkable…

Explainable AI Makes Exoskeletons Understandable—and Ready for Everyday Use

Exoskeletons are often described as a technology of the future, yet they already ease physical strain for workers in logistics and manufacturing today. Still, wearable assistive devices do not always…

Triple Recognition and Funding for Prof. Martin Reuter

Bonn/Germany, December,17, 2025. Prof. Martin Reuter, an expert in artificial intelligence at DZNE’s Bonn site, has received three recognitions simultaneously for his work in AI-based brain imaging.…

Data Bias Reduces Reliability of AI Models Predicting Antimicrobial Resistance

Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance mechanisms can be identified based on a pathogen’s genetics. However, the…

HZI podcast: New drugs enabled by artificial intelligence

At first glance, biology and computer science seem like opposites. But wherever enormous amounts of data are generated from research, progress is hardly possible without digital methods.…

Latest @ Helmholtz AI

Latest @ HelmholtzAI