Welcome to relAI! – Konrad Zuse School of
Excellence in Reliable AI
The current technological revolution is largely driven by spectacular progress in artificial intelligence (AI). Yet, although the huge potential is widely recognized, the lack of reliability of AI technology is still considered a serious issue of concern, limiting its adoption both by industry and society at large. Indeed, aspects such as safety, security, and privacy-preservation are essential prerequisites for the use of AI in domains of public interest – e.g. ensuring that robots do not endanger life or respecting confidentiality of data.
The vision of the 'Konrad Zuse School of Excellence in Reliable AI' (relAI) is to train future generations of AI experts, who for the first time combine technical brilliance with awareness of the importance of AI’s reliability. Our novel, highly innovative AI program will educate top international candidates in the end-to-end development of reliable AI systems (including scientific knowledge, business expertise, and industrial exposure), both for industry and academia, and perform cutting-edge research to make AI ready for deployment in critical application domains.
relAI trains future generations of AI experts who combine technical brilliance with an eye on AI's implications for society.
NEWS
relAI at the European Embodied Robotics Week
We are pleased to share relAI’s contribution to the European Embodied Robotics Week, whichtook place last week in Munich. The event was organizedby RoboTUM together with START Munich and the ESRA (European Student Robotics Association) network. The Robotics Festival convened a diverse range of stakeholders from the European robotics and physical artificial intelligence ecosystem. Specialists, students, and … Read more
...more
Robotic Decision Making via Diffusion Models
Machine learning (ML) – based techniques enable robots to perform a range of tasks in complex environments. Research in this area has increased significantly in recent years, with various ML methods being explored to allow robots to make decisions based on task requirements and changes in their surroundings. However, some of the tested approaches, such as reinforcement … Read more
...more
Disparate privacy risks from medical AI
relAI is proud to announce an outstanding achievement – a first author publication of Moritz Knolle, one of relAI’s PhD students, in Nature journal. Medical AI models are increasingly utilized in applications such as diagnosing and remotely treating patients. While these models have proven valuable to both practitioners and patients, concerns remain about the privacy of patients … Read more
...more