Original Tweet
What if we could train AI robots in a perfect, physics-accurate simulation?
Researchers from The Chinese University of Hong Kong, Shenzhen propose GS-World.
Itโs a new method that uses a generative simulation engine to automatically create the vast, realistic dataโobjects, environments, physicsโthat AI needs to learn.
This engine-driven approach outperforms current methods in efficiency for training capable, real-world embodied AI, enabling scalable progress in robotics and autonomous systems.
GS-World: An Efficient, Engine-driven Learning Paradigm for Pursuing Embodied Intelligence using World Models of Generative Simulation
Paper:ย https://t.co/rbFzaKIAQI Project: https://dexforce.com/embodichain/index.html#/ Code:ย https://github.com/DexForce/EmbodiChain Doc: https://dexforce.github.io/EmbodiChain/introduction.html
Our report: https://mp.weixin.qq.com/s/IGe1myOEmAW7JOrQyBLhBA
๐ฌ PapersAccepted by Jiqizhixin
๐ ์๋ณธ ๋งํฌ
- https://dexforce.com/embodichain/index.html#/
- https://github.com/DexForce/EmbodiChain
- https://dexforce.github.io/EmbodiChain/introduction.html
- https://mp.weixin.qq.com/mp/wappoc_appmsgcaptcha?poc_token=HJQHh2mjK1Qs4pH0mFRxwUyzln56zR96C6sofDS9&target_url=https%3A%2F%2Fmp.weixin.qq.com%2Fs%2FIGe1myOEmAW7JOrQyBLhBA
๋ฏธ๋์ด
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