Within the RSI platform, every materials research project is carried by four tightly integrated modules—Project, Session, Experiment and Resource Center—and driven by three layers of deep iterative ...

A dual-graph deep learning network that hard-codes petroleum physics alongside learned statistics cuts oil production prediction error to about 20 percent, far outperforming conventional models.

The FIA World Endurance Championship’s broadcast product races into a vibrant new era in Brazil this weekend (12-13 July), introducing a fresh on-screen visual identity that reflects the series’ core ...

Liquid AI released d1-ultra, a text and image decision model that returns calibrated probabilities in 1 forward pass. It ...

The benchmark confirms that some AIs are becoming exceptional tools for research-level math. But open-source models still ...

AI may soon be the default way to solve theoretical problems in economics, high-energy physics, and other fields, MIT ...

A bicycle robot combines the strengths of wheeled and legged systems and demonstrates a range of acrobatic behaviors.

Researchers at Friedrich Schiller University Jena and the University of Regensburg have developed a method for determining, ...

Robotics labs are collecting egocentric video and motion-capture data to train AI models, as the sector raises nearly $48 ...

Drawing and interpreting graphs are core practical skill in chemistry, yet many learners still lose marks on graph questions. Examiners’ reports consistently highlight avoidable errors: inappropriate ...

An illustration of Commonwealth Fusion Systems' SPARC fusion reactor,CFS A new US Department of Energy-backed project aims to predict the behavior of plasma inside a fusion reactor in less than 20 ...

Boost R&D ROI by reducing discovery time and costs through AI-driven platforms, strategic partnerships, generative AI, acquisitions, and geographic expansion.Dublin, Oct. 12, 2026 (GLOBE NEWSWIRE) -- ...