aesthetic taste and artistic judgement has more to do with one's own historical, cultural and philosophical references than the content of images
that is to say: vectorizing a personal aesthetic is less a machine learning problem and more a deeply personal political project
Like time has been time for a long time
- @emmettshine, 2026, imessage
I bombed a whiteboard code interview inverting a btree or something (fake startup making 3d webGL rental tours) so bad that I started a software agency at 25 so I never had to subject myself to that godawful impractical humiliation ritual ever again. Now I ship operating systems
hugh francis retweeted
GAN Poetics
Does an unfinished image ask more of its viewer than one that looks complete? And if so, what did we lose when the AI image field moved on to diffusion models, whose entire premise runs in the opposite direction: resolution, coherence, an image that looks like it was never generated at all?
For a few years, GANs left a sort of fingerprint: a smear, faces sliding into one another, unfinished images. It recurred across artists who had nothing else in common but the GAN models, so consistently critics gave this a name: GANism. Was that sameness a limit of the architecture, or a portrait of the people using it, the datasets being used? If a thousand artists bring a thousand intentions to the same generator and get back one look, where does authorship actually sit? With the artist, the dataset, or the machine? 10 years later, artists, with access to the most advanced diffusion models, are now going back to those GANs to explore them as expressive tools.
Diffusion models generate with a polish and control that GANs never had, but that polish arrives bundled with cost, with licensing, with infrastructure few individuals own outright. So where do artists go who want to keep working at the level of the pixel, the glitch, the visible seam, who find more to say in an unstable image than a resolved one? Is it strange that the technique researchers left behind is the one that remains open, inspectable, free to misuse, free to run on a laptop rather than rented compute? Does a technology's obsolescence to the field that built it create exactly the kind of margin an artist needs, a space left alone long enough to be reoccupied on different terms?
Is the artist's retreat toward the older, rougher, cheaper GAN a nostalgia, or a refusal... a way of insisting that an image should still show its work, still carry the evidence of a process rather than disappear into polish? And as diffusion gets faster, cleaner, and more expensive all at once, is the open, imperfect GAN becoming not a relic but a position? A deliberate place to stand and ask what we actually want images to do for us?
Here are some artists from the Daily Program @dailydotxyz who have explored these tools and aesthetics, each with their own unique intentions.
📺 7303711398_artificial_intelligence_wikiart_029 by @twt_cha_
To be an agency is to be a bank.
I’ve always said that our company should be a public utility: a platform to build our rich and dynamic lives.
Today, I believe it’s more radical not to refuse profit motive, but to socialize it.
This is our new deal: open.substack.com/pub/garden…
We’ve since opened Index Greenpoint, and built a new floor in Chinatown. We acquired USB Club, rebranded XXIX and Sanctuary Computer, ran the Hey Mamdani! campaign, and started Family Intelligence with Mozilla Foundation.
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