The U.S. Department of Energy now has two major supercomputing systems aimed at accelerating fusion energy research through artificial intelligence. Argonne National Laboratory’s Aurora exascale ...
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 ...
Simulating the nonlinear optical physics that underlies ultrafast laser systems is computationally demanding—a practical bottleneck in settings that require rapid feedback. A study by researchers at ...
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 ...
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 ...
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 ...
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) ...
Professor Arshad Kudrolli is using “physics-informed neural networks” to develop a more efficient, accurate process to ...
San Mateo, California-based startup Luminary Cloud has released three new physics artificial intelligence models aimed at dramatically accelerating the design of collaborative combat aircraft, ...
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