...
On July 21, SceniX, a robotics and simulation company, joined World Labs. SceniX has been building systems that turn real robots, environments, and interactions into simulations for policy training and evaluation, developing a real-to-sim-to-real (R2S2R) engine that turns one physical task into many controllable, reusable worlds, helping robotics teams train policy models and test changes faster, uncover failures earlier, and reduce costly experimentation on hardware.
The work by the SceniX team deepens World Labs’ technology development in spatial intelligence, and broadens our use cases from virtual to physical environments. As we continue to make progress, our generative world models will not only create realistic 3D scenes but also become increasingly aligned with the reality and variation that robots must interact with, learn from, and be evaluated in. And this is just the beginning.
Today, we share some early results from the R2S2R engine. Using our proprietary technology, our model generates simulations aligned with reality that allow robots to do what has long been considered out of reach: learn complex manipulation tasks with zero real-world training data; predict and evaluate through simulation which robotic policies will succeed or fail in the real world, without extensive and expensive physical trial and error; and then operate reliably for hours on physical robots in real-world settings.
....
In our functional taxonomy of world models, spanning renderers, simulators, and planners, we argued that the simulator is the linchpin because it turns a world into a place where agents can act, learn, and be evaluated. ...
See the full story here: https://substack.com/redirect/bc14fa8f-1dc2-4e3a-b8f2-1ea574c892cd?j=eyJ1IjoiMXZvc2xuIn0.zwOGgeyE8FO4iWufzcD2KbyvQRXYnOuPi8m6mXtrgrk