GoKawiilStartup Vsim builds GPU-optimized robot simulator powering Freddo
Robotics startup Vsim, founded by former Nvidia Isaac Sim engineers Lu and Storey, has built a high-performance training simulator optimized for modern GPU chips rather than older algorithms from the 1970s and 80s. The resulting software is efficient enough to run directly on the hardware of their robot Freddo, letting it simulate tens of thousands of possible near-future scenarios in real time while moving.
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Most robots learn in virtual environments before deploying learned policies to physical hardware, but running simulations onboard in real time is a much harder technical challenge. By rebuilding simulation algorithms specifically for GPUs, Vsim's approach could let robots adapt instantly to unpredictable real-world situations, such as homes with moving people, animals, or other robots, which is a key barrier to practical household robotics.
- Vsim was founded in 2022 by former Nvidia Isaac Sim developers Lu and Storey.
- Their simulator is optimized for GPUs, unlike traditional robotics algorithms from decades earlier.
- Freddo can run about 20,000 simulated scenarios roughly a second into the future while operating.
NVIDIA Jetson Orin Nano Developer Kit — This is the kind of compact GPU-powered board that makes onboard AI and robot simulation-to-hardware transfer possible, similar to the systems described in the article. It's a great way for hobbyists and developers to experiment with training and deploying robotics AI policies at home.
See NVIDIA Jetson Orin Nano Developer Kit on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: bbc.co.uk — Watch Our Pick Of Standout Clips Across The Bbc, 2026-09-17
Published there as: “The virtual worlds where robots are trained”
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