PhysicsX demonstrates that large physics models trained on simulation and real-world data can supersede traditional CAE, enabling high-fidelity simulation across the entire product lifecycl…

Established data and model-size scaling laws for physics models — where larger models trained on more data generalize better zero-shot — give PhysicsX conviction to invest heavily in larger…

A new wave of neo-manufacturers across semiconductors, quantum, fusion, and aerospace are reaching production scale and becoming major engineering organizations, creating a growing customer…

PhysicsX's work with semiconductor equipment manufacturers and fabs on advanced packaging and process control indicates the semi supply chain is a beachhead for AI-native simulation, with g…

Real-time AI control of industrial processes like aluminum smelting cell baths and gas turbine operations can materially reduce energy consumption and improve yield, linking industrial AI d…

While European policy and industry rhetoric supports working with AI-native startups, commercial adoption and spend rates remain materially lower than in the US and Asia, creating a geograp…

The compute, data, and model-size scaling laws PhysicsX has established for physics models parallel those in robotics for embodiment-free control, suggesting a shared trajectory for AI mode…