16.07.2026
Gitta Kutyniok Featured in Heise on Energy-Efficient AI
Exploring the Potential of Neuromorphic Chips
MCML PI Gitta Kutyniok is featured in a recent Heise article exploring how neuromorphic chips could help reduce the energy consumption of artificial intelligence. The article examines how new computing architectures inspired by the human brain could make AI applications more efficient.
Kutyniok discusses the mathematical and computational foundations behind efficient AI and the potential of neuromorphic approaches. The article highlights how combining advances in AI algorithms and specialized hardware could help address the growing energy demands of modern AI systems.
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03.09.2026
Julia Schnabel: What if a Broken Rib Could Save Your Life?
MCML PI Julia Schnabel explores how AI can uncover hidden signs of disease in medical images that might otherwise go undetected.
