OpenAI introduced its inaugural text-to-video model, Sora, on February 15, receiving positive feedback despite acknowledging its ongoing developmental journey. Sora, touted for crafting intricate videos from simple text prompts, expanding existing videos, and generating scenes from static images, is capable of producing 60-second videos featuring detailed scenes, dynamic camera movements, and expressive characters.

According to OpenAI's blog post on February 15, Sora claims the ability to generate movie-like scenes in up to 1080p resolution, incorporating multiple characters, specific motions, and precise subject and background details. Operating on a "diffusion" model, akin to its image-based predecessor DALL-E 3, Sora generates output by transforming initial "static noise" progressively over several steps.

Sora's foundation draws from past research on GPT and DALL-E3 models, enhancing its ability to faithfully represent user inputs. However, OpenAI acknowledged Sora's weaknesses, particularly in accurately simulating complex scene physics, potentially leading to discrepancies in cause and effect, such as a person biting a cookie without leaving a mark.

Spatial details pose another challenge, with Sora occasionally confusing left and right or failing to adhere to specific directional descriptions. OpenAI restricted access to the generative model to "red teamers" and select professionals, aiming to assess potential harms and gather feedback.

Despite these limitations, Sora garnered attention on social media platform X, with numerous video demos circulating and over 173,000 posts trending. OpenAI CEO Sam Altman even invited custom video-generation requests, sharing seven Sora-generated videos, including a duck on a dragon's back and golden retrievers podcasting on a mountain top.

The reactions on X were overwhelmingly positive, leaving many users "speechless." Nvidia senior researcher Jim Fan emphasized that Sora transcends being merely a creative tool like DALL-E 3, categorizing it as a "data-driven physics engine" capable of simulating intricate rendering, intuitive physics, long-horizon reasoning, and semantic grounding. Fan's perspective positions Sora not just as a video-generation tool but as a comprehensive engine influencing the physics of the generated scenes themselves.

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