London-based startup PhysicsX secures $32 million in Series A funding to develop an AI platform that enables engineers to create and run simulations for physical systems in industries such as automotive, aerospace, and materials science manufacturing.
PhysicsX, a London-based AI startup co-founded by a former Formula One engineering superstar and a computer science expert, is making its debut with an AI platform designed to transform the way engineers build and operate physical systems in the enterprise world. The company has secured $32 million in Series A funding, led by General Catalyst, to further develop its platform and drive business development in industries where bottlenecks in development occur due to the limitations of traditional simulation methods.
Tackling a Consistent Problem in Manufacturing and Physical Production
PhysicsX addresses a long-standing issue in manufacturing and physical production that has often been overlooked. In industries such as automotive, aerospace, and materials science manufacturing, engineers frequently encounter the need to simulate and test new ideas before committing to development. Traditionally, this simulation and testing process has been carried out manually by scientists and engineers, with limited optimization capabilities.
Robin Tuluie, co-founder of PhysicsX, explains that complex simulations can be time-consuming, limiting the depth at which engineers can optimize their designs. By introducing an AI platform, PhysicsX aims to significantly reduce the computational and time costs associated with simulations, enabling engineers to optimize physical systems more effectively.
Founders with Firsthand Experience
The founders of PhysicsX, Robin Tuluie and Jacomo Corbo, have firsthand experience in the challenges faced by engineers in the physical production and manufacturing industries. Tuluie, a theoretical physicist, has worked alongside Nobel Prize winners and has held key positions in renowned racing teams, including Renault and Mercedes. Corbo, with a PhD from Harvard, has worked in racing and led the AI labs at McKinsey, collaborating with Formula One and other automotive and industrial clients.
Their combined expertise and experience have allowed them to assemble a team of 50 scientists specializing in mechanical engineering and physics to develop the PhysicsX platform. While initially focused on automotive applications, the platform has the potential to address a wide range of optimization problems across various industries.
AI’s Potential in the Physical World
PhysicsX’s emergence coincides with a significant shift in the application of AI to the physical world. DeepMind recently released research on using advanced machine learning for weather prediction, highlighting the increasing role of AI in physics and engineering. Corbo believes that this trend will pave the way for further AI applications in engineering and R&D. PhysicsX aims to leverage this opportunity by building a platform that can predict the physics of a system with high accuracy and speed, revolutionizing engineering across sectors.
A Unique Approach to Digital Transformation
While many enterprises face challenges in digital transformation, PhysicsX’s approach sidesteps these obstacles. The company focuses on engineering and R&D, which are not typically IT issues requiring widespread organizational scaling. This unique positioning allows PhysicsX to disrupt traditional development processes in industrial companies without the need for extensive infrastructure changes.
Conclusion: PhysicsX’s AI platform has the potential to revolutionize the way engineers build and optimize physical systems in industries such as automotive, aerospace, and materials science manufacturing. With its ability to accelerate simulations and improve optimization, PhysicsX aims to transform engineering practices and become a category-defining company in advanced industries. As AI continues to advance, the application of AI to the physical world is set to redefine the boundaries of engineering and usher in a new era of industrial transformation.