What Is "Sora"?
Sora is an artificial intelligence model released by OpenAI, designed to transform text into high-definition videos of any size. It is capable of generating smooth videos up to one minute in length, and can also create videos based on images or other videos. This allows for the creation of both realistic and imaginative scenes.
Sora is the latest text-to-video model released by OpenAI. It can generate videos up to one minute long, fully adhering to the user's prompt while maintaining visual quality. OpenAI's vision is grand. Unlike typical companies that tout slogans like 'everyone is a director/artist', OpenAI is committed to developing AGI and World Simulators to help people solve problems that require interaction with the real world.
As an impressively powerful new generation video generation model, Sora is paving the way for a new era in AI video creation!
The official website of Sora: https://openai .com/sora
The technical report URL of Sora: https://openai.com/research/video-generation-models-as-world-simulators
How to Generate A Video with Sora?
At present, OpenAI has not yet opened Sora for public testing, nor is there a public channel for beta testing. However, we believe that in the near future, we will all be able to conveniently experience this astonishing new model. Stay tuned!
What are the features of Sora? (the layman's version)
Below are some distilled features of the Sora model.
- The largest model supports the generation of high-fidelity videos up to 60 seconds long;
- It supports the extension of short videos both forwards and backwards, maintaining continuity while extending the duration;
- It supports video editing based on video + text, allowing a single sentence to change the original video, completely altering the logic of video editing.
- Video information is compressed into spacetime patches and modeled using a diffusion-transformer structure.
- Due to the compression of video information into spacetime patches, direct generation of different sizes, times, and resolutions is supported.
- Dalle3 is used for fine-grained video text annotation, and a model is trained to expand short prompts into complex text for video generation.
- There are still some defects in physical interactions, such as the inability to generate shattered glass or footprints in the snow.
- While it has not been mentioned whether a physics engine is used, it may have been utilized in data collection.
What are the features of Sora? (the expert's version)
Unified visual data representation
Researchers convert all types of visual data into a unified representation for large-scale generative model training. Sora uses visual patches as its representation, similar to text tokens in Large Language Models (LLMs).
Video compression network
Researchers have trained a network to compress original videos into a low-dimensional latent space and decompose their representation into spacetime patches. Sora is trained in this compressed latent space and generates videos.
Diffusion model
Sora is a diffusion model that generates videos from input noise patches by predicting the original 'clean' patches. Diffusion models have shown significant scalability in language modeling, computer vision, and image generation.
Scalability of video generation
Sora can generate videos of different resolutions, durations, and aspect ratios, including full HD videos. This flexibility allows Sora to directly generate content for different devices or prototype content quickly before generating full-resolution videos.
Language understanding
To train a text-to-video generation system, a large number of videos and corresponding text captions are needed. Researchers applied the re-description technique introduced in DALL·E 3, first training a highly descriptive caption generator, then generating text captions for all videos in the training set.
Image and video editing
Sora can generate videos based on text prompts, as well as prompts based on existing images or videos. This allows Sora to perform a wide range of image and video editing tasks, such as creating perfect loop videos, animating static images, extending videos forward or backward, etc.
Imitation ability
When video models are trained on a large scale, they exhibit some interesting emerging abilities, allowing Sora to simulate certain aspects of the physical world, such as dynamic camera motion, long-term consistency, and object persistence.
Discussion
Although Sora has shown potential as a simulator, it still has many limitations, such as a lack of accuracy in simulating basic physical interactions (like glass shattering). Researchers believe that continuing to expand video models is a promising path to developing simulators for the physical and digital world.