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Those example pictures are trippy! Some of them look like those weird DeepMind sick-fever dream creations. Except I assume they are all real photos, not genera

Those example pictures are trippy! Some of them look like those weird DeepMind sick-fever dream creations. Except I assume they are all real photos, not generated. It's very possible that a trained AI would be better-able to identify some of the candidates than I would. For example, from OP's post, w/ coordinate system starting at lower left, I have no idea what I'm looking at in these examples, except they look organic-ish: [1]: [1,4], [3,2], [4,1] sillysaurusx: I've never seen conglomerate pictures like this used in AI training. Do you train models on these 4x4 images? What's the purpose vs a single picture at a time? Does the model know that you're feeding it 4x4 examples, or does it have to figure that out itself? Aside: Another awesome 'sick-fever dream creation' example if you missed it when it made the rounds on HN is this[3]. Slide the creativity filter up for weirdness! [3] https://thisanimedoesnotexist.ai/ https://thisanimedoesnotexist.ai/

sillysaurusx 6y ago
I'm surprised so many people want to see our BigGAN images. Thank you for asking :) You can watch the training process here: http://song.tensorfork.com:8097/#images http://song.tensorfork.com:8097/#images It's been going on for a month and a half, but I leave it running mostly as a fishtank rather than to get to a specific objective. It's fun to load it up and look at a new random image whenever I want. Plus I like the idea of my little TPU being like "look at me! I'm doing work! Here's what I've prepared for you!" so I try to keep my little fella online all the time. - https://i.imgur.com/0O5KZdE.png https://i.imgur.com/0O5KZdE.png - Plus stuff like this makes me laugh really hard. https://i.imgur.com/EnfIBz3.png https://i.imgur.com/EnfIBz3.png - Some nice flowers and a boat. https://i.imgur.com/mrFkIx0.png https://i.imgur.com/mrFkIx0.png The model is getting quite good. I kind of forgot about it over the past few weeks. StyleGAN could never get anywhere close to this level of detail. I had to spend roughly a year tracking down a crucial bug in the implementation that prevented biggan from working very well until now: https://github.com/google/compare_gan/issues/54 https://github.com/google/compare_gan/issues/54 And we also seemed to solve BigGAN collapse, so theoretically the model can improve forever now. I leave it running to see how good it can get. I've never seen conglomerate pictures like this used in AI training. Do you train models on these 4x4 images? What's the purpose vs a single picture at a time? Does the model know that you're feeding it 4x4 examples, or does it have to figure that out itself? Nah, the grid is just for convenient viewing for humans. Robots see one image at a time. (Or more specifically, a batch of images; we happen to use batch size 2 or 4, I forget, so each core sees two images at a time, and then all 8 cores broadcast their gradients to each other and average, so it's really seeing 16 or 32 images at a time.) I feel a bit silly plugging our community so much, but it's really true. If you like tricks like this, join the Tensorfork discord: https://discord.com/invite/x52Xz3y https://discord.com/invite/x52Xz3y My theory when I set it up was that everyone has little tricks like this, but there's no central repository of knowledge / place to ask questions. But now that there are 1,200+ of us, it's become the de facto place to pop in and share random ideas and tricks. For what it's worth, https://thisanimedoesnotexist.ai/ https://thisanimedoesnotexist.ai/ was a joint collaboration of several Tensorfork discord members. :) If you want future updates about this specific BigGAN model, twitter is your best bet: https://twitter.com/search?q=(from%3Atheshawwn)%20biggan&src=typed_query https://twitter.com/search?q=(from%3Atheshawwn)%20biggan&src...
- Itsdijital 6y ago
  This is awesome, thanks.

sillysaurusx 6y ago

I'm surprised so many people want to see our BigGAN images. Thank you for asking :) You can watch the training process here: http://song.tensorfork.com:8097/#images http://song.tensorfork.com:8097/#images It's been going on for a month and a half, but I leave it running mostly as a fishtank rather than to get to a specific objective. It's fun to load it up and look at a new random image whenever I want. Plus I like the idea of my little TPU being like "look at me! I'm doing work! Here's what I've prepared for you!" so I try to keep my little fella online all the time. - https://i.imgur.com/0O5KZdE.png https://i.imgur.com/0O5KZdE.png - Plus stuff like this makes me laugh really hard. https://i.imgur.com/EnfIBz3.png https://i.imgur.com/EnfIBz3.png - Some nice flowers and a boat. https://i.imgur.com/mrFkIx0.png https://i.imgur.com/mrFkIx0.png The model is getting quite good. I kind of forgot about it over the past few weeks. StyleGAN could never get anywhere close to this level of detail. I had to spend roughly a year tracking down a crucial bug in the implementation that prevented biggan from working very well until now: https://github.com/google/compare_gan/issues/54 https://github.com/google/compare_gan/issues/54 And we also seemed to solve BigGAN collapse, so theoretically the model can improve forever now. I leave it running to see how good it can get. I've never seen conglomerate pictures like this used in AI training. Do you train models on these 4x4 images? What's the purpose vs a single picture at a time? Does the model know that you're feeding it 4x4 examples, or does it have to figure that out itself? Nah, the grid is just for convenient viewing for humans. Robots see one image at a time. (Or more specifically, a batch of images; we happen to use batch size 2 or 4, I forget, so each core sees two images at a time, and then all 8 cores broadcast their gradients to each other and average, so it's really seeing 16 or 32 images at a time.) I feel a bit silly plugging our community so much, but it's really true. If you like tricks like this, join the Tensorfork discord: https://discord.com/invite/x52Xz3y https://discord.com/invite/x52Xz3y My theory when I set it up was that everyone has little tricks like this, but there's no central repository of knowledge / place to ask questions. But now that there are 1,200+ of us, it's become the de facto place to pop in and share random ideas and tricks. For what it's worth, https://thisanimedoesnotexist.ai/ https://thisanimedoesnotexist.ai/ was a joint collaboration of several Tensorfork discord members. :) If you want future updates about this specific BigGAN model, twitter is your best bet: https://twitter.com/search?q=(from%3Atheshawwn)%20biggan&src=typed_query https://twitter.com/search?q=(from%3Atheshawwn)%20biggan&src...

Itsdijital 6y ago
This is awesome, thanks.