User

What are different styles / types of data art?

Gemini

Thinking: Exploring Data Art Basics

I’m starting by defining the concept of “data art” and gaining a general understanding. After establishing this foundation, I will delve into specific styles and subcategories. I plan to study types like generative art, data visualization, and physical data installations to gain a comprehensive view.

Expanding Interactive Data Art

Now, I’m incorporating interactive data art into the mix. I’m focusing on finding concrete examples and key artists within that style. My next step will be to synthesize this expanding information to provide a clear categorization of the various styles and types of data art, and the final delivery will include descriptions and illuminating examples for each.

Thinking: Discovering Data Art Forms

I’ve been exploring diverse data art forms, starting with a general definition. Foundational knowledge is building; I’ve identified several key styles and variations. This research solidifies my perspective, and I’m prepared to delve into specific examples soon.

Mapping Artistic Expressions

I’m now cataloging the diverse styles of data art. It’s more than just visualization, with physical sculptures, generative algorithms, interactive installations, performance-based works, and even analog drawings. The distinction between data art and visualization is becoming clear; aesthetics are paramount, but not at the expense of meaning. It’s an exciting field to explore!

Cataloging Artistic Styles

I’m focusing now on the aesthetic styles, rather than just the medium. I’ve begun compiling a list of specific examples. In my search, I found that “Dear Data” is a handmade visualization project, along with other physical examples. Generative AI art and interactive installations are also on my radar. I need to make clear distinctions between what creates the work and the overarching aesthetic style.

Expanding Aesthetic Categories

I’m now focusing on specific visual and conceptual styles within data art, identifying distinct artistic movements like Glitch Art, Biomimetic Data Art, and Data Landscapes. I’m also compiling a list of prominent contemporary artists representing these styles. Furthermore, I’ll delve deeper into the unique experience offered by Data Sonification, broadening the scope beyond visual representation. This approach will create a richer and more complete view.

Analyzing Aesthetic Nuances

I’m now zeroing in on the aesthetic styles within data art. I’m moving beyond the technology, aiming to clearly categorize by visual and conceptual aspects. My research will focus on identifying specific aesthetic styles, like minimalist or glitch art, and connect them with prominent artists to create concrete examples for analysis. I aim to create a classification that encompasses both aesthetic and medium.

Thinking: Exploring Data Art Forms

I’ve made a key distinction between functional data viz and artistic data art, which has helped narrow my focus. I’ve compiled a solid base of information on these categories and types of data art, which has yielded more options and possibilities.

Identifying Key Aesthetics

I’ve fleshed out my understanding of mediums, expanding beyond just digital forms. I’m excited by the possibilities in physical sculptures and textiles. I’ve uncovered distinct aesthetic styles like Glitch Art and Biomimetic designs, and I’ve also incorporated influences from abstract art movements, focusing on their potential impact. While I have a core list of artists, I’m working to confirm their precise data art connection, and expand the list.

Expanding the Data Landscape

I’m now diving into the specifics of data art “movements” beyond Glitch and Biomimetic. I’m exploring “Quantified Self” as an artistic style and seeking more diverse examples, particularly within Data Landscapes and Glitch art. I’m focusing on confirming the data-driven nature of works by Refik Anadol and Ryoji Ikeda to ensure my research is accurate, and ready to refine.

Thinking: Categorizing Data Art

I’ve been drilling down on the landscape of data art, focusing on two main branches. First, I’ve outlined the broad strokes: Functional versus Artistic, Physical, Digital, Interactive, and Performative. Now, I’m starting to get into specific aesthetics and techniques, like Glitch Art, exploring how digital errors and corruption can be harnessed for artistic expression, including datamoshing and pixelation.

Exploring Key Artists

I’ve been immersed in the work of key artists. Refik Anadol’s deeply data-driven, AI-powered pieces are a fascinating contrast to the mathematical precision of Ryoji Ikeda’s immersive data environments. Laurie Frick’s “Quantified Self” approach with handmade materials provides another perspective. I’m also confirming specific movements, and I’ve now identified Willem Besselink and Jer Thorp to add to the list.

Finalizing Categorization Structure

I’ve solidified my categorization framework. It will cover Medium (Physical, Digital, Performative), Aesthetic Style (Glitch, Biomimetic, Minimalist/Abstract, Hand-Drawn/Humanist), and a thematic section on Quantified Self. I can now provide a coherent response.

Refining the Framework

I’m now in the final stages of the plan. I’ve conducted a final check and refined the structure for clarity and completeness. The introduction will clearly differentiate data art from visualization. I’ve ensured a logical flow covering Medium, Aesthetic Style, and Themes, including “Quantified Self” and Activist/Environmental sections. A concise conclusion will tie it all together. No further research is required.

Data art (often called information art) is distinct from standard data visualization. While visualization aims for clarity and efficiency (charts, graphs), data art prioritizes expression, emotion, and aesthetic experience. It uses data as a raw material—like paint or clay—to create something that may not be immediately “readable” but is deeply felt.

The world of data art is typically categorized in three ways: by Medium (how it is made), by Aesthetic Style (how it looks), and by Theme (what it is about).

1. By Medium: How It Is Created

This categorization looks at the physical or digital tools used to construct the artwork.

  • Generative & Algorithmic Art:
    • What it is: Artists write code (algorithms) that acts as a set of rules. When data is fed into this code, it generates complex, often unpredictable visual outputs.
    • Key Example: Refik Anadol. He uses AI and machine learning to process massive datasets (like millions of images of glaciers or brain scans) to create fluid, dream-like “data paintings” that move and morph on giant screens.
    • Style: Often fluid, particle-based, and highly complex.
  • Physical Data Art (Data Sculptures):
    • What it is: Bringing data out of the screen and into the real world using materials like wood, metal, paper, or 3D-printed plastic.
    • Key Example: Willem Besselink. He creates large-scale installations using physical objects (like beads or bricks) to visualize data such as his own daily movements or city traffic patterns.
    • Notable Mention: The Tempestry Project, where knitters create “temperature tapestries” using different colors of yarn to represent daily temperatures, visualizing climate change through textiles.
  • Immersive & Interactive Installations:
    • What it is: Room-sized environments where the viewer walks inside the data. These often use sensors to change the art based on the viewer’s presence or movement.
    • Key Example: Ryoji Ikeda. His work (like data-verse) uses massive floor-to-ceiling projections of high-precision mathematical data. It immerses viewers in a strobe-lit, black-and-white digital universe that feels like standing inside a computer processor.
  • Performative & Sonic Art (Sonification):
    • What it is: Turning data into sound or performance rather than visuals.
    • Key Example: Brian Foo created a track called “Two Trains” where the volume and energy of the music rise and fall based on the income inequality data of the neighborhoods the NYC 2 train passes through.

2. By Aesthetic Style: The Visual Language

This categorization looks at the “vibe” or visual rules the artist applies to the data.

  • Data Humanism (Hand-Drawn / Analog):
    • The Vibe: Imperfect, personal, warm, sketchy.
    • Philosophy: Rejects the idea that data is “objective” or “cold.” It emphasizes the human stories behind the numbers.
    • Key Artist: Giorgia Lupi. Her project Dear Data (with Stefanie Posavec) involved sending weekly hand-drawn postcards to each other, tracking personal things like “times I complained” or “doors I opened,” visualized with colored pencils and markers.
  • Glitch Art:
    • The Vibe: Distorted, pixelated, chaotic, “broken.”
    • Philosophy: Uses digital errors, corrupted files, and “noise” to show the fragility of technology and memory.
    • Technique: Artists might “bend” the data of an image file to intentionally break it, creating colorful, jagged artifacts.
  • Biomimetic Data Art:
    • The Vibe: Organic, floral, creature-like.
    • Philosophy: Uses data to mimic natural forms. Instead of bars and lines, data might determine the growth patterns of a digital tree, the flocking of birds, or the blooming of flowers.
    • Key Example: Jer Thorp, who visualized 10,000 bird species by creating a unique digital feather for each one based on its data attributes.
  • Precisionism / Minimalist:
    • The Vibe: Stark, black and white, grid-based, hyper-clean.
    • Philosophy: Strips away all decoration to reveal the raw mathematical sublime of the data. (This is the style often associated with Ryoji Ikeda, mentioned above).

3. By Theme: The Subject Matter

Sometimes styles are defined by what they track.

  • Quantified Self Art:
    • Focus: Intense self-tracking. Artists track their sleep, heart rate, steps, or mood and turn it into art.
    • Key Artist: Laurie Frick. She takes personal tracking data (like sleep cycles) and turns them into warm, tactile wall art using wood, leather, and paper, making intimate personal data feel cozy rather than surveillance-like.
  • Data Landscapes:
    • Focus: Geography and environment.
    • Technique: Using elevation data, wind speeds, or ocean currents to generate digital topographies.
    • Example: “Warming Stripes” by Ed Hawkins is a simple, iconic visualization using colored stripes to show global temperature rise—it has transcended into a symbol used on everything from ties to stadium walls.

Summary Table

Style/TypePrimary MediumAesthetic VibeKey ArtistGenerativeCode / AIFluid, complex, dreamlikeRefik AnadolPhysicalWood, Yarn, 3D PrintTactile, sculpturalWillem BesselinkImmersiveProjection, LightOverwhelming, hypnoticRyoji IkedaData HumanismInk, PaperSketchy, personal, warmGiorgia LupiQuantified SelfMixed MediaIntimate, patternedLaurie FrickExport to SheetsA next step you can do: If any of these specific styles resonate with you (e.g., “I love the idea of Data Humanism”), I can suggest a specific small project or tool you could use to try creating a piece in that style yourself.

User

Let’s limit ourselves to generative & algorithmic visual art. Within this, expand the aesthetic styles (the visual language) to cover popular as well as niche and even obscure styles of art. Describe the vibe and philosophy in a sentence each, along with a practitioner and example. List at least 25.

Gemini

Thinking: Investigating Visual Styles

I’m currently focused on the aesthetic range within generative art. I’m actively searching for both well-known styles and lesser-known sub-genres. Right now, the search terms are focused on “glitch art,” “datamoshing,” and “fractal art.” I’ll refine this later. I’m planning to broaden the search soon to include more abstract approaches as well.

Expanding Style Exploration

I’ve significantly broadened my investigation to include “pixel sorting,” “reaction-diffusion,” and several other niche generative art styles. My focus is now on identifying representative practitioners and characteristic examples for each, as well as succinctly capturing their visual vibe and underlying philosophy. I’m aiming to compile a comprehensive list of at least 25 distinct styles, complete with the requested details, to answer the user’s specific request.

Thinking: Analyzing Initial Results

I’ve begun to analyze the initial search results, focusing on the aesthetics of generative and algorithmic art. Promising broad categories, like generative art, are emerging, alongside some specific artists. This provides a solid foundation for deeper exploration.

Cataloging Art Forms

I’m now cataloging the identified art forms, separating them into specific styles and techniques. The list includes pixel sorting, reaction-diffusion, strange attractors, and fractal art. I’m also delving into isometric generative art, vector fields, and L-systems, plus cellular automata, ray marching, dithering, and feedback loops. It’s a growing collection of visual ideas.

Deepening Style Taxonomy

I’m expanding my style taxonomy, identifying artists for niche forms. I’ve added artists like olo Gamboa Naon, Anders Hoff, and Mark J. Stock to existing categories. I’m also exploring artists like Jon McCormack, Frieder Nake, and Jared Tarbell to fill gaps, as well as Tyler Hobbs, and Helena Sarin. I am hoping to create a more comprehensive overview of these fields.

Pinpointing Specific Artists

I’m now zeroing in on artists who exemplify niche styles like dithering, ray marching, and cellular automata. I’ve found Laurent Malys for dithering and am confident I’ll identify specialists for the others. I’m also refining my approach to discern the “vibe” and philosophy behind these generative forms to make sure they are distinct. I will look for plotter art, live coding visuals, dithering, and 4k intro style artists. I’m also expanding my search to include ASCII generative art.

Narrowing Search Scope

I’ve refined my search to a precise list of generative art forms and specific artists. Now, I’m focusing on “Generative Plotter Art,” “Ray Marching/SDF Art,” “Live Coding Visuals,” “Generative ASCII/Petscii Art,” “Asemic Writing Generative,” “Demoscene procedural graphics,” “Pixel Sorting,” “Flow Fields,” “Circle Packing,” and “Delaunay Triangulation/Voronoi” art. I’ll include “Subdivision” and “Evolutionary/Genetic Art” as well, which will allow me to hone in on dithering and slit-scan art. Eventually, “Vector Synthesis” and related artists are the key. My goal is to synthesize the list down to the required twenty-five.

Thinking: Refining Artistic Styles

I’ve made considerable strides in compiling data on diverse generative and algorithmic art techniques. I’m focusing on defining twenty-five specific styles. I’m prioritizing clarity, ensuring that each has a unique set of parameters and aesthetic qualities. My next step involves solidifying these distinctions, especially in areas where certain techniques overlap.

Cataloging Artists Now

I’m now cataloging artists and concrete examples for each of the pre-defined artistic styles, and am getting close to 25. For Generative Plotter Art, I have Molnar, Paslier, and Hobbs. Ray Marching boasts Quilez and Shadertoy contributions. Hydra, TidalCycles, and Jay exemplify Live Coding. I’ve anchored ASCII Art with Knowlton and noted Warez culture. Asemic Writing has Xu Bing, Gaze, and Serafini. Finally, Demoscene boasts “Farbrausch”. I still seek a dither artist who uses the aesthetic, and I am close.

Expanding Artist Database

I am actively searching for artists who embody the styles I’ve already defined. I’ve located artists for Vector Synthesis like Jerobeam Fenderson and Derek Holzer. For Flow Fields, Tyler Hobbs is a key example. I am searching for a good fine art example for Reaction-Diffusion but Jonathan McCabe seems promising. I have artists for Feedback Loops like Andrei Jay. Finally, I’m identifying Cellular Automata artists like Maxime Causeret, and for Strange Attractors groups such as “Chaotic Atmosphere” are helpful.

Seeking Visual Examples

I’m now hunting for visual examples to solidify the remaining categories. I’ve found Adam Magyar and Erik Boertjes for Slit-Scan, and Manolo Gamboa Naon for Isometric Generative work. I have Stephanie Pan and The Tempestry Project for Generative Knitting. Matt DesLauriers fills the Noise Functions slot. Now, I need to refine and expand a few areas: identifying a Datamoshing artist to distinguish Glitch Art, pinpointing an L-Systems artist (Jon McCormack seems strong), confirming Michael Hansmeyer for Subdivision, and finding a Circle Packing artist (Julien Gachadoat is promising).

Expanding The Styles List

I’m digging deeper into the artistic categories. I’ve pinpointed candidates for several styles. For Voronoi/Delaunay, Raven Kwok seems like a strong choice. Fractal Art now includes Tom Beddard’s stunning 3D work. Sage Jenson is perfect for Physarum/Slime Mold, and Woody Vasulka represents Scan Processing. I’m also adding Particle Systems, Swarm Intelligence, Tessellation, Genetic Art, Projection Mapping, and Creative Coding Minimalism to the target list. Refik Anadol, Robert Hodgin, Hamid Naderi Yeganeh, Karl Sims, Adrien M & Claire B, and Mur are emerging as potential candidates, expanding my roster.

Identifying Key Artists

I’ve identified key artists for Voxel Art, with Beeple’s tool use and MadMaraca’s manual approach now clearly excluded. I’m focusing on code-heavy generative voxel terrain. I’ve also identified Neural Style Transfer artists like Gene Kogan. Finally, I’ve confirmed artists for Plotter Art with Lichentritt’s interference patterns and Rev Dan Catt. My current task involves finalizing examples for the weaker categories before writing the definitive response. This involves pinpointing a generative circle packing artist and a true example of Dithering art.

Pinpointing Visual Styles

I’m zeroing in on final examples. For Swarm Art, I’m set with Robert Hodgin. I’m also actively trying to pinpoint a great artist for Generative Tessellation to finalize the aesthetic. I need to make some decisions on how to present the visuals for Datamoshing and Sorting Art as well, as they are not immediately defined by an artist. I’m close to completing the main artistic styles to include in the list.

Thinking: Defining Art Styles Further

My research has successfully identified an extensive list of generative and algorithmic art styles, practitioners, and relevant examples. I have organized them for clarity and will continue to work on categorization. I am now delving deeper into specific examples of strange attractors, cellular automata, and fractal art to understand their nuances.

Exploring Style Practitioners

I’ve confirmed Dimitris Ladopoulos as a key figure in Chaotic Atmosphere visualization. I’ve also found Sage Jenson to be a strong example for Physarum/Slime Mold art. For Circle Packing, I’m leaning toward Julien Gachadoat, Marius Watz, or Jer Thorp to represent the aesthetic, as their work stands out more than generic tutorials. I’m still hunting for a definitive name within the pure Dithering art.

Defining 1-Bit/Dithering

I’ve refined the “Dithering” style to “1-Bit / Dithering”, acknowledging the challenge of finding a dedicated “Dithering Artist.” Dmitry Morozov (::vtol::) is now a leading contender, along with Laurent Malys and Hellocatfood (Antonio Roberts), for their glitch/dithering work. Lia’s early generative art also informs this.

Constructing The List

I’m now satisfied with the style list candidates, and I’m ready to categorize them. My structure will be built on broad “Vibe” categories to make it easily digestible for viewers. The list is finalized.

Building the Taxonomy

I’ve been busy adding to the taxonomy, focusing on specific practitioners and examples. I’ve successfully incorporated styles like Wave Function Collapse (marian42) and Cellular Automata (Maxime Causeret). I’ve also integrated Live Coding and Swarm/Flocking into the framework. I’m now refining the organization for clarity.

Consolidating Style Choices

I’ve narrowed down the style list to 26 distinct styles. I’m now making final decisions about which styles to include, potentially merging or selecting the most representative 25. The goal is to provide a clear and concise presentation. I’m focusing on structuring the information for optimal user experience.

This list explores the visual languages of generative art, ranging from the widely recognized to the niche and obscure.

I. The Organic & Biological

Styles that mimic nature’s growth, flow, and evolution.

1. Flow Fields

  • The Vibe: Silky, sweeping, painterly lines that look like combed fur, topographic maps, or river currents.
  • Philosophy: Uses a grid of invisible vectors (arrows) to guide the path of drawing agents, simulating fluid dynamics.
  • Practitioner: Tyler Hobbs
  • Example: Fidenza — A series that feels like a perfect hybrid of computer precision and abstract expressionist painting.

2. Reaction-Diffusion

  • The Vibe: Psychedelic animal print, brain coral textures, and fingerprint-like mazes that morph and breathe.
  • Philosophy: Simulates chemical chemicals diffusing and reacting to create complex, self-organizing patterns (Turing patterns).
  • Practitioner: Jonathan McCabe
  • Example: Multi-Scale Turing Patterns — Hypnotic, colorful, microscopic-looking textures.

3. Physarum (Slime Mold) Simulation

  • The Vibe: Ghostly, veiny networks that look like fungal roots or city traffic seen from space.
  • Philosophy: Mimics the behavior of Physarum polycephalum (slime mold) foraging for food, creating efficient transport networks.
  • Practitioner: Sage Jenson
  • Example: Ceres — A digital simulation where millions of particles form organic, breathing vascular structures.

4. Swarm & Flocking (Boids)

  • The Vibe: Murmurations of starlings, schools of fish, or particles moving in synchronized, liquid chaos.
  • Philosophy: Emergent complexity arises from simple rules: separation, alignment, and cohesion.
  • Practitioner: Robert Hodgin
  • Example: Flight Patterns — Visualizations of air traffic data that look like glowing, living organisms.

5. L-Systems (Lindenmayer Systems)

  • The Vibe: Fractal trees, alien ferns, and recursive branching structures.
  • Philosophy: Uses a grammar of string rewriting rules to model biological growth processes like plant branching.
  • Practitioner: Jon McCormack
  • Example: Fifty Sisters — Evolved digital plant species generated from code, presented as botanical illustrations.

II. The Glitch & Chaos

Styles that embrace errors, noise, and destruction.

6. Pixel Sorting

  • The Vibe: Melty, dripping streaks of color where an image looks like it’s sliding off the canvas.
  • Philosophy: Reorders the pixels of an image based on brightness or hue, treating image data as a list of numbers to be organized.
  • Practitioner: Kim Asendorf
  • Example: Mountain Tour — The project that popularized the “pixel sort” aesthetic, turning landscapes into digital waterfalls.

7. Datamoshing

  • The Vibe: Surreal, smeared transitions where one video frame “melts” into the next, often leaving artifacts of the previous scene.
  • Philosophy: Exploits video compression errors (specifically removing I-frames) to force motion from one clip to carry the pixels of another.
  • Practitioner: Takeshi Murata
  • Example: Monster Movie — A video work that turns a B-movie monster into a pulsating, liquid abstraction.

8. Dithering (Algorithmic 1-Bit)

  • The Vibe: Retro, grainy, noisy textures composed entirely of black and white dots (or limited palettes).
  • Philosophy: Exploring how to represent continuous tone using only binary states (on/off), often finding beauty in the “noise” of error diffusion.
  • Practitioner: Dmitry Morozov (::vtol::)
  • Example: Ra — Uses 1-bit dithering aesthetics in hardware installations to visualize sound and laser scans.

9. Feedback Loops (Video Feedback)

  • The Vibe: Infinite tunnels, liquid trails, and “hall of mirrors” effects that drip and echo.
  • Philosophy: Feeding the output of a system back into its input, creating self-perpetuating, chaotic, and often uncontrollable results.
  • Practitioner: Andrei Jay
  • Example: Waaave Pool — A video synthesis tool that creates melting, retro-psychedelic visuals using digital feedback.

III. The Mathematical & Geometric

Styles rooted in pure geometry, dimensions, and logic.

10. Ray Marching (SDFs)

  • The Vibe: Smooth, plastic-like, infinite 3D landscapes that morph continuously; often looks “squishy” or mathematically perfect.
  • Philosophy: Renders scenes by “marching” rays forward until they hit a mathematically defined distance field, allowing for infinite detail without polygons.
  • Practitioner: Inigo Quilez
  • Example: Elevated — A 4KB intro (program) that generates a photorealistic mountain range from pure math in real-time.

11. Strange Attractors

  • The Vibe: Wispy, fine-line tornados or glowing wireframe butterflies orbiting invisible points in space.
  • Philosophy: Visualizes chaotic systems where a point orbits a specific set of values (the attractor) but never exactly repeats the same path.
  • Practitioner: Dimitris Ladopoulos (Chaotic Atmosphere)
  • Example: Attractors — High-definition renderings of mathematical equations that look like exquisite digital jewelry.

12. Mandelbulbs (3D Fractals)

  • The Vibe: Infinite alien cathedrals, H.R. Giger-esque tunnels, and hyper-detailed geometric caverns.
  • Philosophy: Extends the 2D Mandelbrot set into 3D space, creating structures with infinite complexity at any zoom level.
  • Practitioner: Tom Beddard (subblue)
  • Example: Fabergé Fractals — Intricate, ornate 3D fractals that resemble alien artifacts or baroque architecture.

13. Circle Packing

  • The Vibe: Bubbles, cellular structures, or pebbles filling a container perfectly without overlapping.
  • Philosophy: The algorithmic challenge of fitting the maximum number of non-overlapping circles (or shapes) into a defined boundary.
  • Practitioner: Julien Gachadoat
  • Example: Voronoi / Packing Studies — Minimalist plotter drawings where thousands of tiny circles form larger shapes or gradients.

14. Voronoi & Delaunay (Generative Low Poly)

  • The Vibe: Shard-like, crystalline, faceted structures that look like stained glass or crumpled paper.
  • Philosophy: Partitions a plane based on distance to points (Voronoi) or connects points into triangles (Delaunay) to reconstruct forms.
  • Practitioner: Raven Kwok
  • Example: 1194D — An interactive creature made of subdividing tetrahedrons that explode and reform.

15. Isometric Generative

  • The Vibe: Impossible architecture, endless staircases, and tumbling geometric blocks in a 2.5D orthographic view.
  • Philosophy: Uses a grid-based isometric projection to create optical illusions or dense structural compositions without perspective distortion.
  • Practitioner: Manolo Gamboa Naon
  • Example: Mantissa — Vibrant, dense compositions of overlapping geometric forms that feel like futuristic blueprints.

IV. The Retro & Structural

Styles defined by hardware limitations or structural rules.

16. Generative Plotter Art

  • The Vibe: Minimalist, high-contrast, pen-on-paper, “shaky” lines, moiré patterns.
  • Philosophy: Writing code specifically to be drawn by a robotic arm (pen plotter), embracing the friction and ink bleed of the physical world.
  • Practitioner: Vera Molnár
  • Example: Structure de Quadrilatères — Simple squares slightly offset by random algorithms to investigate the line between order and chaos.

17. ASCII / PETSCII Art

  • The Vibe: Images constructed entirely from text characters, looking like “The Matrix” code or vintage terminal displays.
  • Philosophy: Using the density of typographic characters (glyph brightness) to represent light and shadow.
  • Practitioner: Kenneth Knowlton
  • Example: Studies in Perception I — An iconic nude portrait made entirely of computer symbols, one of the earliest digital artworks.

18. Vector Synthesis (Oscilloscope Art)

  • The Vibe: Glowing green neon lines, lissajous knots, and shapes that vibrate and twist with sound.
  • Philosophy: Using audio signals to drive the X and Y deflection of an electron beam on an analog oscilloscope—you are literally “seeing” the sound.
  • Practitioner: Jerobeam Fenderson
  • Example: Oscilloscope Music — Music videos where the audio waveform draws 3D shapes (mushrooms, butterflies) on the screen.

19. Demoscene (4k Intros)

  • The Vibe: Flashy, high-speed, techno-futuristic 3D graphics that push hardware to the limit.
  • Philosophy: Extreme efficiency; creating a full audiovisual experience (music + video) in an impossibly small file size (e.g., 4096 bytes).
  • Practitioner: Farbrausch
  • Example: fr-08: .the .product — A seminal 64kb intro that generated an entire 3D world and soundtrack from a file smaller than a JPEG.

20. Subdivision / Computational Architecture

  • The Vibe: Gothic, bone-like, incredibly detailed columns and grottos that look grown rather than built.
  • Philosophy: Recursively dividing simple shapes into smaller, more detailed versions of themselves (folding) to create massive surface complexity.
  • Practitioner: Michael Hansmeyer
  • Example: Digital Grotesque — A 3D-printed room so detailed it contains millions of unique facets, generated by subdivision algorithms.

V. The Abstract & Conceptual

Styles that deal with language, time, and perception.

21. Asemic Writing (Generative)

  • The Vibe: Alien scripts, calligraphy that means nothing, sprawling glyphs that look like ancient manuscripts.
  • Philosophy: Generating text-like forms that have no semantic meaning, focusing purely on the aesthetic of written language.
  • Practitioner: Xu Bing (or digital practitioner Tim Gaze)
  • Example: A Book from the Sky — While hand-carved, it is the foundational conceptual work for this style; modern versions generate these glyphs with AI/code.

22. Slit-Scan / Time Displacement

  • The Vibe: Stretched, jelly-like distortions where moving objects look like long, twisted tubes.
  • Philosophy: visualizing time as space by capturing a single sliver of a video frame over and over and stacking them horizontally.
  • Practitioner: Adam Magyar
  • Example: Stainless — High-speed subway trains captured through a slit-scan, making the busy commuters look like frozen statues in a void.

23. Cellular Automata

  • The Vibe: Pixelated “critters” moving on a grid, expanding crystals, and retro-arcade textures.
  • Philosophy: Discrete models where the state of a cell depends on the state of its neighbors (e.g., Conway’s Game of Life), creating complex behavior from simple rules.
  • Practitioner: Maxime Causeret
  • Example: Order from Chaos — A video visualizing cellular automata rules that evolve from simple dots into complex, organism-like colonies.

24. Live Coding (Algorave)

  • The Vibe: Cyberpunk, flashing code overlaid on top of the visuals it is creating in real-time.
  • Philosophy: Showing the “seams” of the art; the code is the interface and the art simultaneously, written live in front of an audience.
  • Practitioner: Olivia Jack
  • Example: Hydra — A live-coding video synth that runs in the browser, allowing for glitchy, feedback-heavy visuals created by typing code on the fly.

25. Wave Function Collapse

  • The Vibe: Pixel-art cities that assemble themselves, pipes that always connect perfectly, procedural dungeons.
  • Philosophy: An algorithm that fills a grid by determining which tiles can exist next to each other based on a set of constraints, solving the “puzzle” of the image.
  • Practitioner: marian42 (Marian Kleineberg)
  • Example: Infinite City — A procedural city generator that creates endless, logical, navigable 3D structures.