[HN Gopher] The physics principle of diffusion inspired modern A...
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       The physics principle of diffusion inspired modern AI art
        
       Author : howsilly
       Score  : 25 points
       Date   : 2023-01-05 20:40 UTC (2 hours ago)
        
 (HTM) web link (www.quantamagazine.org)
 (TXT) w3m dump (www.quantamagazine.org)
        
       | manmal wrote:
       | Can anybody explain what is meant by ,,gradient" in this context?
       | Is this a way of speeding up the search for a desirable
       | improvement of a pixel (or cluster) in each pass?
        
         | PartiallyTyped wrote:
         | They refer to score models, where the score is the density of
         | the input.
         | 
         | Imagine you have a huuuuge landscape, with peaks and valleys.
         | This landscape defines the density of the distribution. Now,
         | imagine that you have a bunch of samples drawn from the
         | distribution, this is the dataset.
         | 
         | Sampling an image is a mixture of dirac delta functions (or a
         | mixture of Gaussian with variance approaching zero).
         | 
         | We can increase the variance to smoothen the landscape. This
         | sort of builds an empirical estimate of the true landscape.
         | 
         | The height of this landscape is "the score".
         | 
         | It turns out that we can actually compute an approximation of
         | the gradient of the score.
         | 
         | The gradient of the score always points towards where the score
         | (aka density) will increase, and you essentially apply
         | gradients to "walk" towards a high density region.
         | 
         | This idea is actually very similar to using gradients to create
         | poisoned inputs that are falsely predicted.
         | 
         | I am being a bit handwavey here, we don't _just_ increase the
         | variance, but this is a decent enough approximation of what's
         | happening and what the gradient refers to in this case.
         | 
         | For all intents and purposes, you can think of the gradient as
         | a vector pointing towards the direction that the density of the
         | dataset increases.
        
         | wildpeaks wrote:
         | I think they refer to Gradient Descent:
         | https://en.wikipedia.org/wiki/Gradient_descent
        
       | hypertele-Xii wrote:
       | Is this a submarine ad for Coca-Cola?
        
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       (page generated 2023-01-05 23:00 UTC)