Robots trained entirely in simulation are beginning to perform more reliably in the real world, according to a series of new robotics research papers presented by NVIDIA at the In ...

Over the past decade or so, foundation models have emerged as the dominant paradigm for interacting with language, images, ...

Standardizing calculations of the helium byproducts generated in advanced fission and fusion energy system materials can increase reactor safety and longevity, according to a study led by University ...

Chip startup NextSilicon's high-performance-computing-focused accelerators get Sandia National Lab's stamp of approval ...

Semiconductor engineering teams have long relied on an iterative simulation workflow: define the scenario, prepare the model, run the analysis, review the results, adjust the design, and repeat until ...

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 ...

Abstract: The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along ...

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.

New research from UBC Okanagan mathematically demonstrates that the universe cannot be simulated. Using Gödel’s incompleteness theorem, scientists found that reality requires “non-algorithmic ...

Zurich-based Fainite AG has received €165,000 (CHF 150,000) from Venture Kick to advance physics-based simulations and expand access to advanced engineering analysis across a wider range of ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account the laws of physics—using Newton's third law. Their research is published ...