Patches, small parts of frames, are crucial in training the Sora AI model. Sora processes sequences of patches to predict the next patch, unlike GPT-4 which deals with tokens. By training on patches, Sora can handle varied sizes of images and videos without the need for pre-processing, leading to higher quality outputs from a larger amount of data.
On today's episode NLW digs into the recently published research on OpenAI's Sora.
Read more: https://openai.com/research/video-generation-models-as-world-simulators
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