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Re:Imagen, a text-to-image diffusion model by joeycodes on Monday May 23, 2022 @06:19PM (#31485543)
Re:Imagen, a text-to-image diffusion model by rg111 on Tuesday May 24, 2022 @01:44AM (#31488424)
Imagen seems more realistic where Dall-E2 is more feel-good.

That is what I feel personally.

Re:Imagen, a text-to-image diffusion model by joeycodes on Tuesday May 24, 2022 @02:28AM (#31488682)
I agree with you, but for me, Dall·E 2 feels good because 90% of the time I can keep hitting the generate button and massage the prompt until I get something inspirational, surprisingly, or visually pleasing. Without access to Imagen, it's impossible for me to compare how much of the "realistic feels" of its images is constrained by the taste of the cherry-pickers.
Re:Imagen, a text-to-image diffusion model by dclowd9901 on Tuesday May 24, 2022 @02:26AM (#31488665)
Looking at these… I can’t help but wonder if these are literal examples of AI imagination?
Re:Imagen, a text-to-image diffusion model by joeycodes on Tuesday May 24, 2022 @02:29AM (#31488689)
I've started to ask myself if my own creativity is a result of random sampling from the diffusion tapestry of associated memories and experience on that topic.
Re:Imagen, a text-to-image diffusion model by albertzeyer on Tuesday May 24, 2022 @02:51AM (#31488821)
What else could creativity possible be?
Re:Imagen, a text-to-image diffusion model by Nition on Tuesday May 24, 2022 @04:52AM (#31489621)
I do wonder what Dall-E 2 would output for a request along the lines of "A still life of a vase of flowers in a completely new art style."
Re:Imagen, a text-to-image diffusion model by zimpenfish on Tuesday May 24, 2022 @05:55AM (#31490025)
Don't have access to Dall-E 2 or Imagen but I do have [1] and [2] locally and they produced [3] with that prompt.

[1] https://github.com/nerdyrodent/VQGAN-CLIP.git [2] https://github.com/CompVis/latent-diffusion.git [3] https://imgur.com/a/dCPt35K

Re:Imagen, a text-to-image diffusion model by Nition on Tuesday May 24, 2022 @04:40PM (#31497317)
Nice. Latent-diffusion has come out very traditional but the VQGAN/CLIP ones are fairly original.
Re:Imagen, a text-to-image diffusion model by zimpenfish on Tuesday May 24, 2022 @05:04PM (#31497525)
From my experiments, the LD one doesn't seem to have been trained on as big or as tagged data set - there's a whole bunch of "in the style of X" that the VQGAN knows* about but the LD doesn't. That might have something to do with it.