A U.S. company has launched the first system to test hypersonic vehicle materials against real weather before flight at ...

Scientists are using AI and physics-based simulations together to design new peptides that will kill previously ...

Free interactive tool uses particle physics-inspired Burkeanomics to predict prosperity impacts from policies in the ...

A mathematical problem that had remained unsolved for more than 10 years in the physics of complex systems has finally been ...

By remotely accessing an IBM quantum computer, a research scientist at Lawrence Berkeley National Laboratory has successfully ...

Abstract: A novel meshless electromagnetic (EM) simulation framework based on Physics-Informed Neural Networks (PINNs), enhanced by the integration of Kolmogorov–Arnold Networks (KANs) is presented.

Overview:  Explore the leading Physical AI development platforms used for robot simulation, reinforcement learning, synthetic ...

In a significant step towards strengthening India's future defence and security talent pool, Thakur College of Science and ...

Disclaimer: This column is merely a guiding voice and provides advice and suggestions on education and careers. The writer is ...

A curated awesome list of papers, benchmarks, datasets, and systems for spatial reasoning, planning-oriented simulation, and simulation-ready 3D scene generation for embodied AI. - ...

This list is about spatial intelligence for usable worlds, not just pretty renders. It prioritizes work that builds or uses structured spatial state: objects, geometry, relations, affordances, ...

Abstract: We present a sampling-based model predictive control method that uses a generic physics simulator as the dynamical model. In particular, we propose a Model Predictive Path Integral ...