VQV Signal
According to a post on X by @SkildAI, Skild AI has open-sourced Steel, its internal physics solver built with NVIDIA. The post says Steel runs simulations up to 13x faster than PhysX while using about 3x less GPU memory. Engineer Luca Ballan says the solver can be tried in Newton, and the company has invited pull requests. The main post is mainly a video, so these performance figures are the company's own claims.
According to a post on X by @SkildAI, Skild AI has open-sourced Steel, its internal physics solver built with NVIDIA. The post says Steel runs simulations up to 13x faster than PhysX while using about 3x less GPU memory. Engineer Luca Ballan says the solver can be tried in Newton, and the company has invited pull requests. The main post is mainly a video, so these performance figures are the company's own claims.
AI-assisted summary based on the listed source.
Skild AI says Steel, its internal physics solver built with NVIDIA, runs simulations up to 13x faster than PhysX with about 3x less GPU memory. Engineer Luca Ballan says it is available to try in Newton and invited pull requests; the main post is mainly a video. Why it matters: Faster open simulation lowers the...
Robotics teams that train manipulation skills with reinforcement learning could face lower training costs if faster open simulation holds up, as the post suggests. Engineers working in Newton can test Steel and contribute code directly. Watch for independent benchmarks and whether the solver gets adopted beyond Skild AI.
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