Multimodality · 2024

Video Generation Models as World Simulators (Sora)

Tim Brooks, Bill Peebles, OpenAI

Framed video generation as training a diffusion Transformer on patches of video and image data at scale, producing minute-long coherent videos and evidence of emergent world-simulation behavior.

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Plain-language summary

Sora represents videos as spacetime patches and trains a diffusion Transformer over them, scaling data and compute rather than baking in physics. The technical report shows long, high-resolution, temporally consistent clips and argues that scale yields rudimentary simulation of objects and dynamics. It signaled diffusion-Transformer scaling as a path to video and world models.

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Provenance

Record ID
P-533
Record created
2026-07-13
Last reviewed
2026-07-14
Record version
2

Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.