A revolutionary brain-inspired supercomputer from China packs data center performance into a desk-sized unit. The breakthrough system uses 90% less power while matching GPU cluster performance, potentially upending traditional computing paradigms.
A groundbreaking study applied multiple machine learning models to predict visual aesthetic preferences in Tehran university campuses. Researchers identified 18 environmental variables that significantly impact student perceptions of beauty in campus rest spots, with ensemble models showing superior predictive performance.
Researchers have successfully employed machine learning techniques to predict visual aesthetic preferences across university campuses in Tehran, according to a recent study published in Scientific Reports. The research team developed sophisticated models that analyze environmental features to forecast how students perceive the beauty of campus rest areas, with potential implications for campus design and urban planning.
