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Beyond Uncanny Valley: Breaking Down Sora

a16z Podcast

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Advantages of Diffusion Models over Other Generative Models

Diffusion models are preferred over prior generative models like GANs and regressive transformers due to their stability in training, ability to generate tokens in parallel, access to a deep computation graph at inference time without the need to unroll it during training, and collaborative training approach through score matching. These features make diffusion models highly effective by enabling the utilization of ample resources at inference time without bearing a heavy cost during training.

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