Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need for expensive simulations. Yet the approach can backfire when AI relies too ...

A study in the Journal of Cosmology and Astroparticle Physics explores how a machine-learning strategy known as transfer learning could dramatically reduce the computational cost of searching for new ...

On the same day IEEE Spectrum reported that General Motors had compressed two weeks of aerodynamics analysis into a matter of minutes using AI trained on simulation data, the broader field that made ...

Running a single physics simulation can take hours or days, depending on the complexity of the geometry and the equations involved. For engineers iterating through hundreds of design variations, that ...

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 ...

Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science. Classical machine learning approaches to molecular dynamics (MD) encode ...

Design engineering is running headfirst into a materials bottleneck. Industries such as automotive, aerospace, electronics, and semiconductors now depend on increasingly complex materials. Yet ...

The gold in your jewelry and the uranium in nuclear power plants share a common and cataclysmic origin: they were born during collisions of neutron stars in what are called kilonovae. Until ...

SIGGRAPH 2026, the world's premier conference on computer graphics and interactive techniques, is proud to announce its ...