Genesis Open-Source AI Physics Engine Introduced, Can Generate 4D Dynamic Worlds to Train Robots

Genesis is said to offer 80 times faster simulation speed compared to existing GPU-accelerated stacks.

Written by Akash Dutta, Edited by Siddharth Suvarna | Updated: 20 December 2024 18:24 IST

Genesis Open-Source AI Physics Engine Introduced, Can Generate 4D Dynamic Worlds to Train Robots

Photo Credit: Genesis

The researchers stated that Genesis implements a unified simulation framework

Highlights

The Genesis physics engine is developed in Python
Genesis supports character motion and robotic policy generation
The AI physics engine offers photo-realistic ray-tracing rendering

Genesis, a generative artificial intelligence (AI) physics model that can simulate four-dimensional (4D) worlds, was unveiled on Thursday. This is a unique AI model, as it combines several different capabilities to simulate scenarios for general-purpose robotics and physical AI applications. The researchers behind the project claimed that Genesis excels at simulation speed and is up to 80 times faster than typical GPU-accelerated systems. Notably, the open-source AI system is available via the Python Package Index (PyPI) repository. But those installing will need to install PyTorch as well.

Genesis AI Physics Model Can Simulate Dynamic Worlds for Robotics Training

In a post on X (formerly known as Twitter), Zhou Xian, the lead researcher of the project, announced Genesis and highlighted that it was built after a two-year-long large-scale research collaboration including more than 20 research labs. It integrates multiple physics solvers and their coupling into a unified framework.

Genesis supports simulating various types of physical phenomena. We developed from scratch a unified physics engine that integrates various SOTA physics solvers (MPM, SPH, FEM, Rigid Body, PBD, etc.), supporting simulation of a wide range of materials: rigid body, articulated… pic.twitter.com/PqhIWULKgp
— Zhou Xian (@zhou_xian_) December 18, 2024

Built entirely on Python, it features a generative agent framework and is powered by a universal physics engine. Currently, the group has only open-sourced the underlying physics engine and the simulation platform. It stated that the generative framework will be released in the future.

The promise of this AI system is big, as per the claims made by the researchers. It is said to be between 10 and 80 times faster than systems like Isaac Gym and MJX, which rely on GPU acceleration to create simulations. Further, in specific scenarios, the engine is claimed to deliver 4,30,000 faster simulation speed than real-time. The lead researchers added that it can train a robotic locomotion policy on a single Nvidia RTX4090 GPU in 26 seconds.

Coming to the key features of the Genesis AI physics engine, it is fully integrated with Python as both the frontend and the backend of the engine were natively developed in it. The system is also available via an application programming interface (API). Despite faster simulation speeds, it is said to maintain simulation accuracy and fidelity. Its unified framework also enables multiple physics solvers to create a wide range of physical phenomena and materials. The physics engine also offers ray-tracing rendering.

Comments

For the latest tech news and reviews, follow Gadgets 360 on X, Facebook, WhatsApp, Threads and Google News. For the latest videos on gadgets and tech, subscribe to our YouTube channel. If you want to know everything about top influencers, follow our in-house Who'sThat360 on Instagram and YouTube.

Further reading: Genesis, AI, Artificial Intelligence, Simulation, Robotics

Akash Dutta Email Akash Dutta

Akash Dutta is a Senior Sub Editor at Gadgets 360. He is particularly interested in the social impact of technological developments and loves reading about emerging fields such as AI, metaverse, and fediverse. In his free time, he can be seen supporting his favourite football club - Chelsea, watching movies and anime, and sharing passionate opinions on food. More