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Why Diffusion Will Win AI Inference with Inception Co-Founder and CEO Stefano Ermon

Why it matters

Stanford professor and Inception CEO Stefano Ermon tells Sarah Guo why he believes diffusion architecture will displace autoregressive LLMs: parallel token generation could offer superior inference scaling and GPU utilization, with Inception's Mercury models already applied to voice-agent use cases. The conversation covers discrete text diffusion, the software stack needed to serve these models at scale, and the argument that efficiency will define the next era of AI competition.

Discuss: If parallel token generation gives diffusion models better inference scaling and GPU utilization than autoregressive LLMs, which current workloads do you expect to remain autoregressive, and why?

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Watch: https://www.youtube.com/watch?v=N1rjtDs8blY