By Markus Meuwly, Department of Chemistry, University of Basel, Switzerland   Machine Learning-based techniques have the potential to fundamentally change how we approach characterizing and understanding chemical and biological materials. It is anticipated that ML applied to protein dynamics allows to carry out atomistic simulations on functionally relevant time scales using models approaching chemical […]

By Simon Olsson, Chalmers University of Technology, Department for Computer Science and Engineering, Section for Data Science and AI, Sweden Generative AI, including large language models and image generation technologies, is influencing society and industry broadly. Current, Generative AI methods are machine learned models. These models learn statistical distributions similar to those broadly used across […]

  By Cecilia Clementi, Einstein Professor Freie Universität Berlin, Department of Physics, Berlin, Germany The last years have seen an immense increase in high-throughput and high-resolution technologies for experimental observation as well as high-performance techniques to simulate molecular systems at a microscopic level, resulting in vast and ever-increasing amounts of high-dimensional data. However, experiments provide […]