Abstract: Reduced weight, size, and maintenance cost, as well as quieter and eco-friendly operation of electro-mechanical actuators (EMA), gained profound attention in various sectors, particularly ...

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 ...

By Harrison Tasoff, UCSB Artificial intelligence is becoming increasingly vital to everyday activities across diverse sectors of society, from AI assistants to autonomous vehicles to healthcare. But ...

The automotive industry holds some of the highest-value and most complex design disciplines you can think of. Designers face ...

Embodied AI world models drew $6 billion in Q1 2026 alone, but new analysis from Fusion Fund investors argues the LLM scaling ...

High Energy Physics (HEP) is a deeply collaborative and software-driven discipline, where scientific discovery depends on advanced computing, data analysis, ...

Pipeline network simulations Unit conversions across SI, CGS, and Imperial systems Component-based property calculations And more, with advanced features under active development.

It’s been three-and-a-half years since generative AI exploded onto the scene. In this past year, progress has continued its relentless pace: Vibe coding took off, companies embraced agentic workflows, ...