Sora: A Review on Background, Technology, Limitations, and Opportunities
  of Large Vision Models
Sora is a text-to-video generative AI model, released by OpenAI in February
2024. The model is trained to generate videos of realistic or imaginative
scenes from text instructions and show potential in simulating the physical
world. Based on public technical reports and reverse engineering, this paper
presents a comprehensive review of the model's background, related
technologies, applications, remaining challenges, and future directions of
text-to-video AI models. We first trace Sora's development and investigate the
underlying technologies used to build this "world simulator". Then, we describe
in detail the applications and potential impact of Sora in multiple industries
ranging from film-making and education to marketing. We discuss the main
challenges and limitations that need to be addressed to widely deploy Sora,
such as ensuring safe and unbiased video generation. Lastly, we discuss the
future development of Sora and video generation models in general, and how
advancements in the field could enable new ways of human-AI interaction,
boosting productivity and creativity of video generation.
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Kai Zhang
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Ruoxi Chen
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Zhengqing Yuan
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YuanZhengqing
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Yue Huang
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Hanchi Sun
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Jianfeng Gao
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Lifang He
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Lichao Sun
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Lichao Sun
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Sora: A Review on Background, Technology, Limitations, and Opportunities
  of Large Vision Models
Sora is a text-to-video generative AI model, released by OpenAI in February
2024. The model is trained to generate videos of realistic or imaginative
scenes from text instructions and show potential in simulating the physical
world. Based on public technical reports and reverse engineering, this paper
presents a comprehensive review of the model's background, related
technologies, applications, remaining challenges, and future directions of
text-to-video AI models. We first trace Sora's development and investigate the
underlying technologies used to build this "world simulator". Then, we describe
in detail the applications and potential impact of Sora in multiple industries
ranging from film-making and education to marketing. We discuss the main
challenges and limitations that need to be addressed to widely deploy Sora,
such as ensuring safe and unbiased video generation. Lastly, we discuss the
future development of Sora and video generation models in general, and how
advancements in the field could enable new ways of human-AI interaction,
boosting productivity and creativity of video generation.
A comprehensive review of Sora, a text-to-video generative AI model, including its underlying technologies, applications, challenges, and future directions in video generation and human-AI interaction.
text-to-video generative AI world simulator film-making education marketing safe video generation unbiased video generation human-AI interaction productivity creativity