News from the baiosphere

At the "Try me!" event in Nuremberg, small and medium-sized companies and start-ups were able to experience AI live. The focus was on various AI demonstrators to touch and test.
The Bavarian AI Council held its summer meeting at the Helmholtz Pioneer Campus in Munich. Main discussion points were the council´s impulses regarding the Bavarian “AI-Offensive” as announced earlier this year by the Bavarian State Government.
Venous thrombosis is a serious health risk as it often goes unnoticed and can become life-threatening. A team of experts is now developing an AI-based diagnostic device that detects blood clots at an early stage.
AI is revolutionizing research. But how can it remain trustworthy? Five new principles in the scientific journal PNAS are intended to ensure transparency and responsibility. Prof. Gasser from TUM also contributed to the code of conduct.
In a position paper, researchers discuss the opportunities and hurdles of using AI in medical research. They formulate political recommendations for action to facilitate access to data, among other things.
The baiosphere KI-Kompass (AI compass) - a holistic guide supports SMEs in tapping the potential of AI for their company - strategically, practically and legally compliant. This paves the way for the successful use of AI.
AI Council member Sami Haddadin presents his visionary idea of an “artificial immune system” for the Earth. In the TED Talk, he explains how advanced AI systems can be used to clean up and protect the environment.
GARMI masters increasingly complex tasks thanks to ChatGPT and digital twin. At the ICRA 2024 robotics trade fair, TUM researchers demonstrate how the care assistant grasps objects, navigates safely and communicates with patients.
The Humboldt Professorships are attracting international scientists to German universities. Germany's most highly endowed research award goes to Prof. Jegelka and Prof. Sra, who are strengthening TUM in the field of AI and machine learning.
A team from Helmholtz Munich has developed the MISATO dataset, which trains AI models for the production of new drugs. This innovation represents an important advance in the use of AI in pharmacy.