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It takes ten times more electricity for ChatGPT to respond to a prompt than for Google to carry out a standard search. Still, researchers are struggling to get a grasp on the energy implications of generative artificial intelligence both now and going forward.

New research sheds light on how diffusion models—used in artificial intelligence (AI) image generation—operate across hierarchical data structures, revealing unexpected transitions between high-level and low-level features during the generative process.

Developed from EPFL research, in collaboration with MIT and Yale, the combination of secure computation and distributed algorithms opens a new era for data collaborations in medical research.

A bioinspired robot developed at EPFL can change shape to alter its own physical properties in response to its environment, resulting in a robust and efficient autonomous vehicle as well as a fresh approach to robotic locomotion.

Quantum computing could be one of the big technological revolutions of the coming decades. At EPFL, scientists are at the forefront of harnessing quantum technologies to address real-world issues, aligning their efforts with the UN Sustainable Development Goals.

EPFL scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and conditions.

“Designing Life with AI” is a cross-disciplinary MAKE project in which EPFL students get a chance to explore the research process by designing proteins. A total of eight research labs are involved.

To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.

EPFL researchers have developed a computational method to explicitly consider the impact of water while designing membrane receptors with enhanced stability and signaling, paving the way for novel drug discovery and protein engineering.

By applying techniques from explainable artificial intelligence, engineers can improve users’ confidence in forecasts generated by artificial intelligence models. This approach was recently tested on wind power generation by a team that includes experts from EPFL.