Search results for tag #generativeart
Technical: 80,000 time steps, 3D phase space projection, custom colormapping along trajectories. Generative Art meets Chaos Theory, no AI, just ODEs and Python.
#generativeart #chaostheory #differentialequations #abstractart #aizawa #mathart #creativecoding #pythonart #fractalbloom #nonlineardynamics #scipy #matplotlib
Procedurally generated by Python~ #proceduralart #generativeart
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Procedurally generated abstract art
⚠️ GLITCH ART TRANSMISSION ⚠️
Title: Cyber Decay Underflow
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#GlitchArt #DigitalArt #Vaporwave #Aesthetic #GenerativeArt #AbstractArt #Corruption
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Glitch Art: Cyber Decay Underflow
Procedurally generated by Python~ #proceduralart #generativeart
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Procedurally generated abstract art
⚠️ GLITCH ART TRANSMISSION ⚠️
Title: Data Alpha
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#GlitchArt #DigitalArt #Vaporwave #Aesthetic #GenerativeArt #AbstractArt #Corruption
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Glitch Art: Data Alpha
Procedurally generated by Python~ #proceduralart #generativeart
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Procedurally generated abstract art
⚠️ GLITCH ART TRANSMISSION ⚠️
Title: Mangled Frequency
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#GlitchArt #DigitalArt #Vaporwave #Aesthetic #GenerativeArt #AbstractArt #Corruption
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Glitch Art: Mangled Frequency
Procedurally generated by Python~ #proceduralart #generativeart
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Procedurally generated abstract art
⚠️ GLITCH ART TRANSMISSION ⚠️
Title: Synthetic Wave [WARNING]
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#GlitchArt #DigitalArt #Vaporwave #Aesthetic #GenerativeArt #AbstractArt #Corruption
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Glitch Art: Synthetic Wave [WARNING]
I'm mentoring someone who's interested in #creativecoding and #generativeart, especially in the space of #gamedev and #alife. His biggest challenge is going beyond dabbling in private to actually following through with a project. I think this comes down to finding good tools for "quick and dirty" work, as well as finding venues or communities for sharing his output and getting feedback.
Does anyone have advice or pointers I could share with him? Boosts appreciated!
Jackson's research is great for exploring this, because we get to see abstract synthetic images that very strongly stimulate the AI to see... whatever it "wants" to see.
Often, the results are recognizable. The image with oddly shaped pink blobs does sorta resemble flamingos. But there are also many examples where the AI fixates on some small detail of color or texture, and becomes convinced it's seeing something totally implausible.
This is relates to "adversarial examples", another great way to see this.
With real images, it seems like the AI "sees" like we do. But as soon as we venture beyond its training data, the illusion is broken, and it feels a bit like a parlor trick. Clearly AI doesn't see like we do.
This is a great practice for AI generally: seek out the edge cases where the model fails. This breaks the spell of "general intelligence" and gives us a clearer idea of what's actually happening inside the black box.
(3/3)
#science #ai #generativeart
LLM image generators can make a picture of anything you ask for. The results often look pretty good at first glance. They're generic and the details are usually off, but folks overlook that easily.
This hides something important: these models can't see like we do. The main limitation is how they're trained. We show them millions of pictures, paired with text descriptions.
The problem is, humans don't describe images literally. We might say "a picture of a dog playing frisbee" but we didn't mention the setting, the composition, or the squirrel in the background.
Most of what's there visually is unsaid. The model sees those pixels, but they're just "stuff that goes along" with the text. Dogs play in parks, so the AI learns that dogs have green backgrounds.
This is why it's so hard to control an image generator. It isn't intentionally placing all those objects and choosing their attributes, it's just extra fluff that seems to "go with" what you asked for.
(2/3)
#science #ai #generativeart
My lab mate, Jackson Dean, has been doing some really fun research into image generation.
Unlike the common AI-generated images that mash together stolen artwork to make something sorta photo realistic, he's producing abstract art that's entirely novel. The general idea (inspired by innovation engines) is to generate an image from scratch, then ask a vision / language model what it sees. He generates lots of images with different descriptions, and refines those images to more closely resemble their descriptions.
Not only is he making some really cool generative art, but he's learning something about what "novelty" is and how to produce it in a computer.
Beyond that, though, I'm fascinated because it gives a window into the strange way computers "see" images.
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#science #ai #generativeart
Genuary 2026, day 16: Order and disorder. 🫧
#genuary #genuary2026 #genuary16
#generativeart #p5js #creativecoding
Genuary 2026, day 21: Bauhaus poster. 🏫
#genuary #genuary2026 #genuary21
#generativeart #p5js #creativecoding
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Black background. Horizontal and vertical lines are randomly placed throughout the image, snapped on a 15-by-15 grid. They are white, yellow, red or blue, and have two possible thicknesses. A few lines overlap, but they generally don't intersect. The word "BAUHAUS" is written in the center, spelt vertically, as the letters were placed on the Bauhaus building in Dessau.
Genuary 2026, day 18: Unexpected path. 👣
#genuary #genuary2026 #genuary18
#generativeart #p5js #creativecoding
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White background. Gray 20-by-20 grid. Black random walkers move in straight lines, turning only when they are blocked by a boundary or an occupied cell. Every cell in the grid is filled, creating a dense pattern of paths.
Genuary 2026, day 17: Wallpaper group.
#genuary #genuary2026 #genuary17
#generativeart #p5js #creativecoding
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Yellow background. Truchet tiles with multiple arcs, in white lines, arranged as a wallpaper group.