What we're buildingRobots will learn in simulation before they hit the factory.
Genesis-World is our bet on that future.
Genesis-World is an open-source, general-purpose simulation platform for physical AI from Genesis AI.
One unified multi-physics engine: rigid bodies, FEM, MPM, particles, cloth, fluids.
A robot arm can pour water onto sand, grasp a deformable object, or cut a soft body, all in the same simulation.
Nyx, our in-house renderer, may be the most promising renderer for robotics out there: real-time photo-realistic rendering, advanced features like depth of field, and state-of-the-art techniques never seen before.
Sensors of every kind: cameras, lidar, IMU, contact forces, temperature, plus arguably the most advanced tactile simulation available (paper).
And the engine keeps growing: we are developing internally the most comprehensive and fastest Incremental Potential Contact (paper) solver for deformable body dynamics we know of, soon to be open-sourced.
It powers real business applications, from full-fledged box packaging with labelling machine and all, to wire harnessing and lab automation, without any physics hack or compromise.
Everything is Python-first and runs anywhere.
Kernels are written once, and Quadrants, our in-house JIT compiler, lowers them to CUDA, AMD ROCm, Apple Metal, Vulkan, x86, and ARM64.
A single laptop or a datacenter.
Massively batched GPU simulation for learning at scale, and complex non-batched scenes where CPU wins outright.
This is at the core of Genesis AI's strategy.
Evaluation is the bottleneck of scalable robotics: real hardware caps iteration at wall-clock time, but simulation turns it into a compute problem.
Ours already runs two orders of magnitude faster than hardware (tens of thousands of episodes in half an hour instead of 200+ hours), while correlating with on-hardware rollouts at 89%.
The north star: physical AI that improves at the speed of compute.
The roleYou push the physics of Genesis-World forward.