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EP 26 | CS25: Transformers in Diffusion Models episode artwork

Mar 20, 2026 19 min

EP 26 | CS25: Transformers in Diffusion Models

from AI Bites: The Academic Series Hosted by Jack Lakkapragada

Transformers aren't just for text anymore. This episode unpacks the massive shift in visual AI: merging the power of Transformers with Diffusion models. We break down how the architecture behind text generation is now the engine driving state-of-the-art image and video creation. Key Topics: The Evolution of Visual AI: Moving away from traditional U-Nets and fully embracing Diffusion Transformers (DiTs). Patching Images: How a model chops an image into "patches" and treats them exactly like words in a sentence to apply the Attention mechanism. Scaling Visuals: Why putting Transformers inside diffusion models makes them significantly more scalable and predictable when training on massive visual datasets. 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 26 | CS25: Transformers in Diffusion Models

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