Spacetime patches are integral to OpenAI's Sora, a model designed to generate videos from textual descriptions. These patches allow the model to efficiently manage and process video data by dividing it into manageable chunks that contain spatial and temporal information. This segmentation aids in training the model on a variety of video scenes without the need for pre-processing steps like resizing or padding, enabling more flexible and robust video generation capabilities. The use of spacetime patches represents an evolution in how AI systems handle complex, dynamic data sets, allowing for improved performance in tasks that require understanding and generating video content.
The concept of spacetime patches was popularized with the release of the Sora model by OpenAI. Although the exact date of first use is not detailed, the technology gained significant attention around 2023, illustrating a key advancement in video generation technology.
The development of spacetime patches, particularly in their application within Sora, has been driven by teams at OpenAI. While specific individuals are not highlighted, the collective efforts of OpenAI's research and development teams have been crucial in realizing and applying this technology to practical AI challenges.