Snapshot: Inaugural lecture on scientific computing in the age of AI
In his lecture on Wissenschaftliches Rechnen im KI-Zeitalter: Zwischen Rechen- und Denkmaschine, which roughly translates to "Scientific Computing in the AI Age: From Number Crunchers to Thinking Machines", Michael?discussed how scientific computing is changing in the era of artificial intelligence, using the contrast between “calculating machines” and “thinking machines” as a guiding theme. He outlined the continued importance of classical high-performance computing for large-scale simulations in areas such as aerospace, climate and weather modeling, and biomedicine, and contrasted this with recent advances of AI methods, for example in protein structure prediction and data-driven weather forecasting. At the same time, he highlighted key challenges for the use of AI in scientific computing, including issues of reliability, explainability, and reproducibility. The lecture concluded with examples from current research in numerical methods, GPU-based computing, and secure machine learning, emphasizing the complementary roles of simulation-based and data-driven approaches in future scientific computing.