AI-driven physics speeds up industrial innovation
By integrating AI and physics-based modelling into real-world operations, companies achieve faster, smarter, and more sustainable engineering outcomes.
PhysicsX, a London-based startup founded by former F1 engineers and AI experts, is redefining engineering with its AI-driven physics platform.
Design and testing cycles are reduced from weeks or months to seconds. Engineers can now iterate rapidly and optimise systems across multiple industries, including aerospace, automotive, semiconductors, energy, and materials.
The technology enables teams to evaluate thousands of design variations simultaneously. Semiconductor firms speed up prototype development, electronics improve thermal performance, and mining boosts copper recovery for renewable energy and AI data centres.
PhysicsX achieves this using Large Physics Models and Large Geometry Models that base design evaluation on real-world physics rather than assumptions.
Predictive reasoning lets engineers simulate multiple parameter changes before acting. The approach shifts control from reactive adjustments to proactive optimisation, helping teams make faster, better-informed decisions.
PhysicsX also bridges disciplinary divides, enabling aerodynamics, structural, and thermal considerations to be optimised together rather than in isolation.
By combining speed, system-level insight, and predictive control, PhysicsX is shrinking the gap between cutting-edge research and practical industrial impact. The platform uses physics-based AI to improve efficiency, drive innovation, and support sustainable growth.
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