It can take years for humans to solve complex scientific problems. With AI, it can take a fraction of the time.

The model reveals that more connected brain regions are more prone to damage, while isolated areas remain resilient. This approach offers a powerful framework for understanding disease progression and ...

Researchers from Okinawa Institute of Science and Technology outline a strategy for using machine learning (ML) to address ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Learn how Kimi K2’s open-weight framework and sparse architecture are transforming AI coding and fostering global ...

A machine learning (ML) network based on transfer learning and transformer networks is applied to wave propagation models for complex indoor settings. This network is designed to predict signal ...

Conclusion: By innovatively integrating multi-source data and machine learning techniques, this study systematically analyzes the relationship between campus audiovisual environments and attention ...

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the extreme precision required and the hundreds of steps involved, such as ...

Federated learning (FL), as a promising machine learning paradigm for large-scale distributed data, faces two security challenges of privacy and robustness: the transmitted model updates potentially ...

Researchers develop two-layer neural model that matches complex visual processing in the brain by Howard Hughes Medical Institute ...