zlacker

Posting a few comparisons here.

https://twitter.com/joeyliaw/status/1528856081476116480?s=21...

>>joeyco+(OP)
Imagen seems more realistic where Dall-E2 is more feel-good.

That is what I feel personally.

>>joeyco+(OP)
Looking at these… I can’t help but wonder if these are literal examples of AI imagination?

>>rg111+tK
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.

>>dclowd+mO
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.

>>joeyco+KO
What else could creativity possible be?

>>joeyco+KO
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."

>>Nition+M31
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

>>zimpen+ia1
Nice. Latent-diffusion has come out very traditional but the VQGAN/CLIP ones are fairly original.

>>Nition+U33
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.