Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

GPT-5.2 features a massive 400,000-token context window — allowing it to ingest hundreds of documents or large code ...

Three conservative groups have proposed model legislation that would dramatically change faculty tenure paths, teaching loads ...

Do Public Science Skeptics Dampen the Future of Discovery? - In the sprawling, noisy agora of modern science, one of the most ...

Project InnerSpace (InnerSpace), the leading independent nonprofit organization dedicated to the global development of ...

A study in Nature Communications by Michele Ceriotti’s group at EPFL has introduced a new dataset and model that greatly improve the efficiency of machine-learning interatomic potentials (MLIPs) and ...

Newman University releases analysis showing its Pathmaker program enables students to complete a 120-credit bachelor's degree ...

Three right-leaning organizations this month released model state legislation intended to reduce “taxpayer funding for ...

From supercomputers to soil health, sustaining national research capability requires more than one-off grants and project ...

Using cutting-edge algorithms and exascale supercomputers, researchers have created the most realistic simulations yet of matter flowing into black holes. Building on decades of research, a group of c ...

Gachon University Gil Hospital (Hospital Director Kim Woo-kyung) held a "2025 Gachon Medical Science Symposium" with Gachon ...

Imagining and preparing for the future in order to guide research and public policy is the very purpose of foresight. A perilous exercise, scientists point out. And one that requires dialogue between ...