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OpenAI Unveils Sora 2: Revolutionizing Text-to-Video Social Media

Sora 2 brings text-to-video generation to the next level. Create, remix, and discover videos with advanced physics and sound effects. Plus, insert yourself or friends into videos with the novel cameo feature.

There is a poster in which there is a robot, there are animated persons who are operating the...
There is a poster in which there is a robot, there are animated persons who are operating the robot, there are artificial birds flying in the air, there are planets, there is ground, there are stars in the sky, there is watermark, there are numbers and texts.

OpenAI Unveils Sora 2: Revolutionizing Text-to-Video Social Media

OpenAI has introduced Sora 2, the latest iteration of its text-to-video generation model, now powering the new social media app Sora on iOS. The app enables users to create, remix, and discover videos, with improved physics obedience and advanced features.

Sora 2, the successor to the original Sora model, offers enhanced capabilities. It can now follow intricate instructions and maintain world state across multiple shots, making videos more coherent and realistic. Additionally, it can create background soundscapes, speeches, and sound effects, further enriching the video experience.

The app also introduces a novel feature: cameos. Users can insert themselves or friends into videos, adding a personal touch. Sora's recommendation algorithm, instructed through natural language, aims to minimize doomscrolling and addiction by learning from user interactions. However, the default feed is initially biased towards followed or interacted accounts.

OpenAI's launch of Sora 2 directly competes with Google's Veo-3, indicating a significant leap in text-to-video generation technology.

Sora 2, with its improved physics obedience, advanced sound and object insertion capabilities, and intelligent recommendation system, promises a more immersive and personalized social media experience. As users explore the app, OpenAI's new recommendation algorithms will adapt, potentially reducing biases and enhancing user satisfaction.

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