This approach allows robotic systems to be trained faster than in real-world conditions by multiplying learning scenarios without hardware constraints. By leveraging simulation, the companies hope to significantly reduce the time required to make robots operational and capable of executing concrete tasks.

Both groups believe this collaboration could accelerate the transition from research to industrial application. By combining the precision of physical simulations with the power of artificial intelligence models, they aim to improve development efficiency and foster faster adoption of robotic solutions across various sectors.