[HN Gopher] Diffusion Without Tears
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       Diffusion Without Tears
        
       Author : jxmorris12
       Score  : 36 points
       Date   : 2025-02-14 19:30 UTC (3 hours ago)
        
 (HTM) web link (baincapitalventures.notion.site)
 (TXT) w3m dump (baincapitalventures.notion.site)
        
       | huqedato wrote:
       | Without tears, right ? Seeing those mountains of cryptographic
       | math I've got red eyes.
        
       | 3vidence wrote:
       | I have an undergraduate degree in Math and generally find math
       | quite enjoyable, however, even I had a pretty hard time grasping
       | most of what this blog was talking about. I think it pretty
       | quickly went from extremely high level (add noise to image, then
       | remove noise) to extremely low level specific.
       | 
       | Also I had a hard time figuring out which part of the equation
       | differentiate the equations for different data points, is that
       | what the meaning of "theta" is in all the equations? To guide the
       | initial noise towards one type of image instead of another is
       | that what theta is responsible for? Is the innovation in GenAI
       | images to use text embeddings to create the theta?
       | 
       | I definitley feel some tears coming on.
        
         | Sharlin wrote:
         | Yeah, the article could definitely use some clarification in
         | many parts (the author may be suffering from the curse of
         | knowledge a bit). Plus there's the fact that even if you know
         | your ODEs, SDEs are a different beast bringing in probability
         | (certainly one may not be accustomed to seeing `p(x|y)` in the
         | middle of a differential equation...)
        
       | gnatolf wrote:
       | As a material scientist, the roller coaster to figure out what
       | 'diffusion' we're talking about here was surprisingly funny.
       | 
       | Means: maybe edit that title a bit :)
        
         | derbOac wrote:
         | Yeah there's lots of "diffusions" out there and I was similarly
         | curious which one they were going to be writing about.
         | 
         | I liked the post though.
        
       | CamperBob2 wrote:
       | TL,DR: "Now time-reverse the stochastic differential equation to
       | infer the rest of the fucking owl."
       | 
       | Thanks, guys, super helpful.
        
       | getnormality wrote:
       | I've noticed that when finance guys learn that there's a really
       | useful AI thing called diffusion, they get all excited and start
       | writing stochastic differential equations and drawing 1-D
       | Brownian motion plots all over the place. It's not yet clear to
       | me whether this helps anyone understand AI diffusion models, but
       | they seem to enjoy it a lot.
        
         | markisus wrote:
         | If by helping anyone you mean helping the math challenged
         | (which is technically almost everyone) then I would be inclined
         | to agree.
         | 
         | But to the quant crowd I'm guessing that couching diffusion in
         | the language of stochastic calculus is helpful.
        
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