EP 28 | CS25: Transformers for Video Generation

from AI Bites: The Academic Series Hosted by Jack Lakkapragada

Generating a single image is hard; generating a coherent video means mastering the dimension of time. In our CS25 finale, we break down how Transformers are being engineered to understand motion, physics, and object permanence to generate high-fidelity video content frame-by-frame. Key Topics: The Time Dimension: How "Temporal Attention" allows a model to track where an object is moving across multiple frames without it morphing or disappearing. Spatiotemporal Patches: Moving beyond 2D image patches and breaking video down into 3D blocks of space and time. Physics and Consistency: The current engineering challenges of ensuring generative video actually obeys the laws of physics and maintains visual logic. Note: This is an AI-generated study resource created via NotebookLM based on Stanford’s CS25 curriculum and personal study notes.

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EP 28 | CS25: Transformers for Video Generation

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This episode is 21 minutes long.

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This episode was published on March 26, 2026.

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