<story><title>Extracting training data from diffusion models</title><url>https://arxiv.org/abs/2301.13188</url></story><parent_chain><item><author>FeepingCreature</author><text>100 images out of 350,000 that they looked at were memorized.&lt;p&gt;This seems to mostly happen when an image appears frequently (more than 100 times) in the training data, and&amp;#x2F;or the dataset is small relative to the model.</text></item></parent_chain><comment><author>wombat_trouble</author><text>Oh come on. I&amp;#x27;m excited about new technologies and I think that image generation can be a net positive for the society, but can we not do that? First, we had people confidently asserting that stuff of this sort absolutely can&amp;#x27;t happen. Now, we&amp;#x27;re moving the goalposts to &amp;quot;well, not a legitimate criticism because it doesn&amp;#x27;t happen often&amp;quot;.&lt;p&gt;The point is that basically &lt;i&gt;all&lt;/i&gt; Stable Diffusion &amp;#x2F; DALL-E &amp;#x2F; MidJourney output is some shade of this; the only new data is that contrary to prior assertions, in some cases, it goes all the way to a verbatim copy.&lt;p&gt;I think there are some defensible stances one can take. One is to reject the idea of intellectual property. Another is to advocate for some specific legal or technical bar that the models would have to pass for it to qualify as &amp;quot;not stealing&amp;quot;. Yet another is to argue it&amp;#x27;s a morally-agnostic technology like VHS or a photocopier, and the burden of using it in a socially acceptable way rests with the user.</text></comment>
<story><title>Extracting training data from diffusion models</title><url>https://arxiv.org/abs/2301.13188</url></story><parent_chain><item><author>FeepingCreature</author><text>100 images out of 350,000 that they looked at were memorized.&lt;p&gt;This seems to mostly happen when an image appears frequently (more than 100 times) in the training data, and&amp;#x2F;or the dataset is small relative to the model.</text></item></parent_chain><comment><author>londons_explore</author><text>Removing duplicates and very near duplicates ought to be one of the first things done to any training dataset...&lt;p&gt;I wonder why this wasn&amp;#x27;t done?   Too computation heavy?</text></comment>