We introduce a unified benchmarking framework focused on evaluating EEG-based foundation models in clinical applications. The benchmark spans 11 well-defined diagnostic tasks across 14 publicly available EEG datasets, including epilepsy, schizophrenia, Parkinson's disease, OCD, and mild traumatic brain injury. It features minimal preprocessing, standardized evaluation protocols, and enables side-by-side comparisons of classical baselines and modern foundation models. Our results show that while foundation models achieve strong performance in certain settings, simpler models often remain competitive, particularly under clinical distribution shifts. To facilitate reproducibility and adoption, we release all prepared data and code in an accessible and extensible format.

Astronomers have designed and trained a computer program that can classify tens of thousands of galaxies in just a few seconds, a task that usually takes months to accomplish. In research published today, astrophysicists from Australia have used machine learning to speed up a process that is often done manually by astronomers and citizen scientists around the world. "Galaxies come in different shapes and sizes," said lead author Mitchell Cavanagh, a Ph.D. candidate based at the University of Western Australia node of the International Centre for Radio Astronomy Research (ICRAR). "Classifying the shapes of galaxies is an important step in understanding their formation and evolution, and can even shed light on the nature of the Universe itself." Cavanagh said that with larger surveys of the sky happening all the time, astronomers are collecting too many galaxies to look at and classify on their own.

Scientists have developed an AI system that can classify tens of thousands of galaxies in a few seconds, a process that can take months to do manually. Up front: Astronomers classify galaxies by shape to understand how they form and evolve. But this can be a time-consuming job. The researchers used convolutional neural network (CNN) architectures to hasten the task. Attend the tech festival of the year and get your super early bird ticket now!