Cosmos World Foundation Model Platform for Physical AI
Abstrak
Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present the Cosmos World Foundation Model Platform to help developers build customized world models for their Physical AI setups. We position a world foundation model as a general-purpose world model that can be fine-tuned into customized world models for downstream applications. Our platform covers a video curation pipeline, pre-trained world foundation models, examples of post-training of pre-trained world foundation models, and video tokenizers. To help Physical AI builders solve the most critical problems of our society, we make Cosmos open-source and our models open-weight with permissive licenses available via https://github.com/nvidia-cosmos/cosmos-predict1.
Penulis (79)
NVIDIA
:
Niket Agarwal
Arslan Ali
Maciej Bala
Yogesh Balaji
Erik Barker
Tiffany Cai
Prithvijit Chattopadhyay
Yongxin Chen
Yin Cui
Yifan Ding
Daniel Dworakowski
Jiaojiao Fan
Michele Fenzi
Francesco Ferroni
Sanja Fidler
Dieter Fox
Songwei Ge
Yunhao Ge
Jinwei Gu
Siddharth Gururani
Ethan He
Jiahui Huang
Jacob Huffman
Pooya Jannaty
Jingyi Jin
Seung Wook Kim
Gergely Klár
Grace Lam
Shiyi Lan
Laura Leal-Taixe
Anqi Li
Zhaoshuo Li
Chen-Hsuan Lin
Tsung-Yi Lin
Huan Ling
Ming-Yu Liu
Xian Liu
Alice Luo
Qianli Ma
Hanzi Mao
Kaichun Mo
Arsalan Mousavian
Seungjun Nah
Sriharsha Niverty
David Page
Despoina Paschalidou
Zeeshan Patel
Lindsey Pavao
Morteza Ramezanali
Fitsum Reda
Xiaowei Ren
Vasanth Rao Naik Sabavat
Ed Schmerling
Stella Shi
Bartosz Stefaniak
Shitao Tang
Lyne Tchapmi
Przemek Tredak
Wei-Cheng Tseng
Jibin Varghese
Hao Wang
Haoxiang Wang
Heng Wang
Ting-Chun Wang
Fangyin Wei
Xinyue Wei
Jay Zhangjie Wu
Jiashu Xu
Wei Yang
Lin Yen-Chen
Xiaohui Zeng
Yu Zeng
Jing Zhang
Qinsheng Zhang
Yuxuan Zhang
Qingqing Zhao
Artur Zolkowski
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓