Physicl Secures $10M to Enhance Robot Training with Realistic Simulations
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Physicl, founded by Alex de Vigan, has raised $10 million in seed funding led by Inovia Capital. The startup aims to improve robot training through realistic simulations, utilizing technology originally developed for creating 3D product renderings. De Vigan's previous experience with nfinite, which focused on generative imagery, informs this new venture's approach to bridging the gap between AI and physical interactions.
The significance of Physicl's work lies in addressing the challenges faced by researchers in developing physical AI models. Traditional training methods using video have proven inadequate, and gathering real-world data can be costly. By providing high-fidelity simulations that accurately represent real-world physics, Physicl seeks to enhance the effectiveness of robots in handling complex tasks, particularly in edge cases.
Physicl plans to launch its product, Studio, which will feature 10,000 3D environments and 100,000 assets for generating synthetic training data. This tool aims to assist robots in overcoming specific challenges, such as identifying objects in cluttered or shadowed environments. No further timeline was disclosed at the time of publication.
Original report
Physicl raises $10M to make the digital world real enough for robots
TechCrunch · Tim FernholzThis briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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