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Ai Category: Simulation PlatformsAi Tags: differentiable Embodied AI generative GPU multi-physics Open-Source simulation
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Genesis is a comprehensive open-source physics simulation platform announced in December 2024 by Carnegie Mellon University in collaboration with more than twenty research labs. It is implemented entirely in Python on top of GPU-accelerated kernels and unifies a wide range of physics solvers — rigid body, MPM, SPH, FEM, PBD, and stable fluid — under a single API, allowing simulation of articulated robots, soft skin, liquids, gases, granular materials, and thin-shell objects in the same scene. Headline performance figures include up to 43 million FPS for a Franka manipulation scene on a single RTX 4090 (around 430,000x real-time), which the project’s authors report as 10 to 80 times faster than existing GPU-accelerated simulators such as Isaac Gym, Isaac Sim, and MuJoCo MJX. Genesis runs cross-platform on Linux, macOS, and Windows with NVIDIA, AMD, and Apple Metal back-ends, supports MJCF / URDF / OBJ / GLB / PLY / STL imports, includes native ray-traced rendering, and is fully differentiable for several solvers. A separate generative agent layer can synthesise simulation scenes and trajectories from natural language. Genesis is a rapidly maturing alternative to Isaac Sim for academic labs.

Genesis
Website URL

Family of embedded AI computing modules (Orin Nano, Orin NX, AGX Orin, AGX Thor) running deep-learning inference on robots. Top-end AGX Orin delivers 275 TOPS of AI performance at 15-60 W; the de-facto standard for on-board AI in commercial robotics.

Genesis is a comprehensive open-source physics simulation platform announced in December 2024 by Carnegie Mellon University in collaboration with more than twenty research labs. It is implemented entirely in Python on top of GPU-accelerated kernels and unifies a wide range of physics solvers — rigid body, MPM, SPH, FEM, PBD, and stable fluid — under a single API, allowing simulation of articulated robots, soft skin, liquids, gases, granular materials, and thin-shell objects in the same scene. Headline performance figures include up to 43 million FPS for a Franka manipulation scene on a single RTX 4090 (around 430,000x real-time), which the project’s authors report as 10 to 80 times faster than existing GPU-accelerated simulators such as Isaac Gym, Isaac Sim, and MuJoCo MJX. Genesis runs cross-platform on Linux, macOS, and Windows with NVIDIA, AMD, and Apple Metal back-ends, supports MJCF / URDF / OBJ / GLB / PLY / STL imports, includes native ray-traced rendering, and is fully differentiable for several solvers. A separate generative agent layer can synthesise simulation scenes and trajectories from natural language. Genesis is a rapidly maturing alternative to Isaac Sim for academic labs.

differentiable, Embodied AI, generative, GPU, multi-physics, Open-Source, and simulation
Genesis Embodied AI consortium (CMU + 20+ research labs)
Simulation Platforms
United States
Open source (Apache 2.0)
Beta
N/A (hardware platform; runs models up to 70B+ on AGX Thor)
On-device possible (CUDA / Metal / AMD GPU recommended; CPU back-end available)
Python SDK
Documentation URL
GitHub URL
Genesis Authors, 'Genesis: A Generative and Universal Physics Engine for Robotics and Beyond' (2024)
Used in research labs across CMU, Stanford, MIT, and the broader Genesis consortium

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