If you're among those eagerly awaiting the opportunity to access and use OpenAI Sora, this guide is specifically tailored for you.
After witnessing the rise of AI image generators, the digital creative landscape is poised for the next leap with AI video generators, heralding a new era with OpenAI's Sora at the forefront. Sora enables users to create videos up to a minute long, maintaining exceptional visual quality and accurately reflecting the nuances of the user's prompts.
In this guide, we'll walk you through the steps and prerequisites for gaining access to Sora. We will also share the capabilities and limitations of this model.
How to access and use Open AI Sora
You cannot access or use Sora at this time, as it is currently only accessible to red teamers for identifying potential harms or risks, and to a select group of visual artists, designers, and filmmakers for feedback to refine the tool for creative use.
OpenAI has not provided specific details about the public release strategy for Sora, including the potential use of a waitlist or early access program. The decision on broader public access is likely to be influenced by feedback received during the current testing phase.
What are the capabilities of Sora?
According to Open AI, Sora is designed to generate complex video scenes with detailed characters, specific motions, and comprehensive background elements, reflecting a deep understanding of both language and physical reality.
It interprets prompts to create videos with multiple shots, consistently maintaining character appearance and visual style, and is capable of producing characters that display a wide range of emotions, showcasing its advanced language comprehension and creative capabilities.
What are the limitations of Sora?
The limitations of Sora include difficulties in accurately simulating the physical aspects of complex scenes, such as failing to show a bite mark on a cookie after it has been bitten, indicating a gap in understanding specific cause-and-effect scenarios.
Additionally, Sora struggles with spatial details within prompts, like confusing left and right, and faces challenges in accurately depicting events that unfold over time, such as following a precise camera trajectory.