For the longest time I thought "diffusion" meant shrinking a model for production 😅

u/Detective-Psych0802 2026-05-25 · 07:27 UTC

For the longest time I thought "diffusion" meant shrinking a model for production 😅

I thought the idea was: Take a large pretrained model → reduce it to the size needed for production → deploy only what you need.

Introduction

I thought the idea was: Take a large pretrained model → reduce it to the size needed for production → deploy only what you need.

Basically some combination of pruning, compression, or reducing parameters.

Diffusion models are an entirely different thing related to generating outputs from noise.

Now I'm curious: Can anyone explain the idea behind diffusion?

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