Artificial intelligence and machine learning

Autonomous driving, smart homes, Industry 4.0 - artificial intelligence (AI) is everywhere. While AI was still fiction just a few decades ago, data-driven models in the form of voice assistants and image recognition algorithms are dominating our everyday lives. Only recently, models such as ChatGPT and StableDiffusion have shown what modern AI methods are capable of. However, such computer algorithms, which are trained using large data sets, also offer enormous potential for progress and innovation in the natural sciences and engineering. AI models can, for example, help to drive the energy transition, develop new materials or create faster weather forecasts.

At SCC, we are therefore researching the development of AI for scientific and engineering applications, and in particular for energy research, life sciences and earth system sciences. We combine scalable methods of high-performance computing with new training and modeling approaches to improve the robustness and efficiency of AI. We consider not only classical CPU/GPU-based computing systems, but also quantum computers. We are also working on frameworks for the efficient execution of AI training and models in European and national networks.

Helmholtz AI

KIT is responsible for energy research in the Helmholtz AI platform with its local unit. Within this framework, SCC supports researchers with a consulting unit in the implementation of AI research projects to explore new approaches of energy generation, distribution and storage. Find out more...

Quantum Machine Learning

SCC combines expertise from the fields of computer science, electrical engineering, theoretical physics and experimental physics and is dedicated to fundamental questions of learnability and trainability in hybrid quantum-classical workflows, with a focus on feasibility, applicability and scalability. Learn more...