The financial landscape of 2026 is defined by a paradox: machine learning systems are now more powerful and autonomous than ever, yet they operate under the strictest regulatory scrutiny in history.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

A Zambian graduate student in the United States is developing a machine learning system designed to help African farmers ...

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...

For more than 30 years, credit decisioning has focused on improving speed and accuracy through automated, large-scale, ...

AI meets isotope science: Machine learning is enhancing isotope analysis techniques, improving efficiency, accuracy, and insights into geochemical processes. Key hurdles remain: Data scarcity, limited ...

A new review in Science China Life Sciences examines how machine learning and host-microbiome multi-omics can be combined to better understand health and disease. The article outlines the road from ...

Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...

Soil acidification is one of the pressing issues confronting global farmland today. Studies indicate that approximately 40% ...

Microchip expands dsPIC33A DSC family for AI data center power, motor control and intelligent sensing designs.

By integrating long-term memory, embeddings, and re-ranking, the company aims to improve trust in agent outputs.