The original version of this story appeared in Quanta Magazine. When she was 10 years old, Rose Yu got a birthday present that would change her life—and, potentially, the way we study physics. Her ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...

Methodology of the CondensNet model. CondensNet is a physically constrained DL parametrisation coupled with a climate dynamics engine to support hybrid modelling. The network architecture mainly has ...

The partnership combines GPU-native physics simulation with cloud scalability, allowing engineers to run massive, high-fidelity simulations and generate the data needed to train Physics AI models.

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...

A physicist has mounted one of the most detailed technical challenges yet against the idea that our universe is a computer simulation, arguing that the energy required to run such a program would ...

During surgery to correct an abnormal heartbeat, doctors rely on a mix of imaging and inference. Still, many critical details remain hidden. At RIT, artificial intelligence (AI) researchers want to ...

Are some fields of study more theoretical than others? Indeed, it seems that some require only documentation to instill knowledge. On the other hand, it's difficult for future specialists in medicine, ...