TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Discover the ultimate roadmap to mastering machine learning skills in 2025. Learn Python, deep learning, and more to boost ...

Explore the top AI tools and essential skills every data engineer needs in 2025 to stay ahead—covering data pipelines, ML integration, cloud platforms, and automation.

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

Machine-learning model can reliably predict cognitive performance based on lifestyle indicators by Diana Yates, University of Illinois at Urbana-Champaign edited by Gaby Clark, reviewed by Andrew ...

The paper presents a landslide warning model dealing with multi-source monitoring using unsupervised machine learning methods, which include One-Class Support Vector Machine, Isolation Forest and ...

In Recentive, the Federal Circuit acknowledged the growing significance of AI and machine learning and emphasized that its holding is limited to generic machine learning applications.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.

This study aimed to develop a practical machine learning (ML) model for the prediction of the risk of SIC in critically ill patients with sepsis. Methods: In this retrospective cohort study, patients ...