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Cosmos World Foundation Model Platform for Physical AI

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	NVIDIA, :, Agarwal, Niket, Ali, Arslan, Bala, Maciej, Balaji, Yogesh, Barker, Erik, Cai, Tiffany, Chattopadhyay, Prithvijit, Chen, Yongxin, Cui, Yin, Ding, Yifan, Dworakowski, Daniel, Fan, Jiaojiao, Fenzi, Michele, Ferroni, Francesco, Fidler, Sanja, Fox, Dieter, Ge, Songwei, Ge, Yunhao, Gu, Jinwei, Gururani, Siddharth, He, Ethan, Huang, Jiahui, Huffman, Jacob, Jannaty, Pooya, Jin, Jingyi, Kim, Seung Wook, Klár, Gergely, Lam, Grace, Lan, Shiyi, Leal-Taixe, Laura, Li, Anqi, Li, Zhaoshuo, Lin, Chen-Hsuan, Lin, Tsung-Yi, Ling, Huan, Liu, Ming-Yu, Liu, Xian, Luo, Alice, Ma, Qianli, Mao, Hanzi, Mo, Kaichun, Mousavian, Arsalan, Nah, Seungjun, Niverty, Sriharsha, Page, David, Paschalidou, Despoina, Patel, Zeeshan, Pavao, Lindsey, Ramezanali, Morteza, Reda, Fitsum, Ren, Xiaowei, Sabavat, Vasanth Rao Naik, Schmerling, Ed, Shi, Stella, Stefaniak, Bartosz, Tang, Shitao, Tchapmi, Lyne, Tredak, Przemek, Tseng, Wei-Cheng, Varghese, Jibin, Wang, Hao, Wang, Haoxiang, Wang, Heng, Wang, Ting-Chun, Wei, Fangyin, Wei, Xinyue, Wu, Jay Zhangjie, Xu, Jiashu, Yang, Wei, Yen-Chen, Lin, Zeng, Xiaohui, Zeng, Yu, Zhang, Jing, Zhang, Qinsheng, Zhang, Yuxuan, Zhao, Qingqing, Zolkowski, Artur
Format:	Preprint
Publié:	2025
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Robotics
Accès en ligne:	Acceder al recurso
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_version_	1866916835265347584
author	NVIDIA : Agarwal, Niket Ali, Arslan Bala, Maciej Balaji, Yogesh Barker, Erik Cai, Tiffany Chattopadhyay, Prithvijit Chen, Yongxin Cui, Yin Ding, Yifan Dworakowski, Daniel Fan, Jiaojiao Fenzi, Michele Ferroni, Francesco Fidler, Sanja Fox, Dieter Ge, Songwei Ge, Yunhao Gu, Jinwei Gururani, Siddharth He, Ethan Huang, Jiahui Huffman, Jacob Jannaty, Pooya Jin, Jingyi Kim, Seung Wook Klár, Gergely Lam, Grace Lan, Shiyi Leal-Taixe, Laura Li, Anqi Li, Zhaoshuo Lin, Chen-Hsuan Lin, Tsung-Yi Ling, Huan Liu, Ming-Yu Liu, Xian Luo, Alice Ma, Qianli Mao, Hanzi Mo, Kaichun Mousavian, Arsalan Nah, Seungjun Niverty, Sriharsha Page, David Paschalidou, Despoina Patel, Zeeshan Pavao, Lindsey Ramezanali, Morteza Reda, Fitsum Ren, Xiaowei Sabavat, Vasanth Rao Naik Schmerling, Ed Shi, Stella Stefaniak, Bartosz Tang, Shitao Tchapmi, Lyne Tredak, Przemek Tseng, Wei-Cheng Varghese, Jibin Wang, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wei, Fangyin Wei, Xinyue Wu, Jay Zhangjie Xu, Jiashu Yang, Wei Yen-Chen, Lin Zeng, Xiaohui Zeng, Yu Zhang, Jing Zhang, Qinsheng Zhang, Yuxuan Zhao, Qingqing Zolkowski, Artur
author_facet	NVIDIA : Agarwal, Niket Ali, Arslan Bala, Maciej Balaji, Yogesh Barker, Erik Cai, Tiffany Chattopadhyay, Prithvijit Chen, Yongxin Cui, Yin Ding, Yifan Dworakowski, Daniel Fan, Jiaojiao Fenzi, Michele Ferroni, Francesco Fidler, Sanja Fox, Dieter Ge, Songwei Ge, Yunhao Gu, Jinwei Gururani, Siddharth He, Ethan Huang, Jiahui Huffman, Jacob Jannaty, Pooya Jin, Jingyi Kim, Seung Wook Klár, Gergely Lam, Grace Lan, Shiyi Leal-Taixe, Laura Li, Anqi Li, Zhaoshuo Lin, Chen-Hsuan Lin, Tsung-Yi Ling, Huan Liu, Ming-Yu Liu, Xian Luo, Alice Ma, Qianli Mao, Hanzi Mo, Kaichun Mousavian, Arsalan Nah, Seungjun Niverty, Sriharsha Page, David Paschalidou, Despoina Patel, Zeeshan Pavao, Lindsey Ramezanali, Morteza Reda, Fitsum Ren, Xiaowei Sabavat, Vasanth Rao Naik Schmerling, Ed Shi, Stella Stefaniak, Bartosz Tang, Shitao Tchapmi, Lyne Tredak, Przemek Tseng, Wei-Cheng Varghese, Jibin Wang, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wei, Fangyin Wei, Xinyue Wu, Jay Zhangjie Xu, Jiashu Yang, Wei Yen-Chen, Lin Zeng, Xiaohui Zeng, Yu Zhang, Jing Zhang, Qinsheng Zhang, Yuxuan Zhao, Qingqing Zolkowski, Artur
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2501_03575
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Cosmos World Foundation Model Platform for Physical AI NVIDIA : Agarwal, Niket Ali, Arslan Bala, Maciej Balaji, Yogesh Barker, Erik Cai, Tiffany Chattopadhyay, Prithvijit Chen, Yongxin Cui, Yin Ding, Yifan Dworakowski, Daniel Fan, Jiaojiao Fenzi, Michele Ferroni, Francesco Fidler, Sanja Fox, Dieter Ge, Songwei Ge, Yunhao Gu, Jinwei Gururani, Siddharth He, Ethan Huang, Jiahui Huffman, Jacob Jannaty, Pooya Jin, Jingyi Kim, Seung Wook Klár, Gergely Lam, Grace Lan, Shiyi Leal-Taixe, Laura Li, Anqi Li, Zhaoshuo Lin, Chen-Hsuan Lin, Tsung-Yi Ling, Huan Liu, Ming-Yu Liu, Xian Luo, Alice Ma, Qianli Mao, Hanzi Mo, Kaichun Mousavian, Arsalan Nah, Seungjun Niverty, Sriharsha Page, David Paschalidou, Despoina Patel, Zeeshan Pavao, Lindsey Ramezanali, Morteza Reda, Fitsum Ren, Xiaowei Sabavat, Vasanth Rao Naik Schmerling, Ed Shi, Stella Stefaniak, Bartosz Tang, Shitao Tchapmi, Lyne Tredak, Przemek Tseng, Wei-Cheng Varghese, Jibin Wang, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wei, Fangyin Wei, Xinyue Wu, Jay Zhangjie Xu, Jiashu Yang, Wei Yen-Chen, Lin Zeng, Xiaohui Zeng, Yu Zhang, Jing Zhang, Qinsheng Zhang, Yuxuan Zhao, Qingqing Zolkowski, Artur Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Robotics 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.
title	Cosmos World Foundation Model Platform for Physical AI
topic	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Robotics
url	https://arxiv.org/abs/2501.03575