What changed
Alex de Vigan, founder of Physicl, has raised $10 million in seed funding led by Inovia Capital to develop tools that help robot builders and world model designers create more realistic simulations for training robots. The funding aims to address the challenges of training robots on real-world tasks by using high-fidelity 3D environments.
What this means in practice
Physicl is leveraging the technology from its previous company, nfinite, which specialized in creating 3D product renderings for e-commerce. The startup is now focusing on transforming unstructured real-world data into high-fidelity 3D environments that can be used to train robots. The company is releasing a product called Studio, which includes 10,000 30 environments and 100,000 assets representing various objects. This allows users to create synthetic data for training robots on specific problems, such as identifying objects in cluttered or shadowed environments.
Limitations and availability
Physicl is entering a competitive market of startups providing data and tooling for foundation model builders and robot operators. The startup aims to be more than a data provider by offering a platform for ongoing synthetic data generation. While the company is collaborating with early customers like SpAItial, it is still in the process of refining its offerings. The supplied announcement does not specify the exact release date or pricing for Studio.
