← All experimentsJosh Cole signatureINDEPENDENT EXPERIMENTS
001 / LIVING SYSTEMS

Culture

Living matter, imagined.

BUD / STRETCH / RELEASE
— FPSLIVE MATERIAL / 64 SIMULATION UNITS
CULTURE / LIVE GENERATIVE STUDY

A living simulation.
Plant a seed. Watch it evolve.

Evolving above. Plant anywhere in the living field.
SIMULATION STATE
state
evolving / live
seed
45838
iteration
600
growth
cell budding + separation
render
— FPS
INSIDE THE EXPERIMENT

How Culture works

Enter the Culture study ↗

Rounded bodies follow changing currents, grow daughter cells and pull apart through soft, narrowing connections.

  1. Drift

    Each cellular family follows its own path through the moving field.

  2. Stretch

    A daughter grows away from its parent. The connecting neck stretches, thins and releases.

  3. Renew

    New buds form on independent cycles, keeping the culture in motion.

An authored, microscopy-inspired system. Planting introduces new growth; the seed lets you revisit its starting conditions.

002 / FORCE + FLOW

Field
conditions.

Direction emerges
from local forces.

VECTOR STUDYSEED 31
Small marks. A larger current.
INSIDE THE EXPERIMENT

How the field takes shape

A seed places short line segments across the surface. Each line turns in response to its position around a shared center. Together, the local directions reveal a larger flow.

Place the marksCalculate directionReveal the current
003 / PROPORTION + RHYTHM

Type,
in motion.

A letter becomes a material.

FORM / COUNTERFORM
INSIDE THE EXPERIMENT

How proportion changes a voice

Width and angle alter the relationship between a letter’s body and the space inside it. Move either control to explore how the same forms feel compressed, open or off balance.

The study transforms the drawn forms; it does not change the font’s underlying outlines.

004 / ORDER + INTERFERENCE

Grid
pressure↙

A regular system.
A localized disturbance.

18 COLUMNS14 ROWS
PRESSURE FIELD / DENSITY STUDY
INSIDE THE EXPERIMENT

How order becomes a signal

The grid stays regular. Distance from a focal point determines which dots become larger and brighter. Increasing pressure expands the active region, making a local disturbance visible inside the larger system.

Regular spacingDistance from a pointVisible interference
005 / OPEN EXPERIMENT / WORLD MODELS

Dry Run
Dungeon.

24 possible futures.
One real move.

Actual Dry Run Dungeon: cyan shows the committed move; violet shows candidate paths predicted by the learned model
ACTUAL PLANNING CAPTUREENGINE MODEL

The left side happens.
The right side might.

BUILT TO SHOW WHERE PREDICTIONS BREAK

A small dungeon. Three neural nets. A visible gap between prediction and reality.

WHAT TO TRY

Change one thing.
Watch what follows.

Choose a test to open its corresponding control.

HOW IT WORKS

The rules are written.
The predictions
are learned.

The engine runs the dungeon’s real rules. A separate ensemble of three small neural networks predicts what a move will do. The planner uses those predictions to try possible futures.

  1. 01 / OBSERVE

    Start from the real state.

    The current board becomes the starting point for each set of dry runs.

  2. 02 / IMAGINE

    Try 24 futures.

    The model predicts sequences of moves. The planner scores the parts that remain within its trust line.

  3. 03 / COMMIT

    Take one real step.

    Only the first move of the chosen sequence reaches the game engine. Then the agent plans again.

  4. 04 / LEARN

    Compare with what happened.

    The actual transition becomes training data. Prediction error stays visible as the model learns from play.

READING THE PICTURE

The fading is
part of the story.

Uncertainty is the model’s own disagreement about a prediction. Error is the comparison with a result after a real move. Watch both.

Solid path
The chosen dry run.
Dashed paths
The other candidate futures.
Scattered dots
Predictions beyond the trust line.
Warm paths / ?
Unfamiliar terrain near the dropped pads.
WHAT THE RECORDED TEST SHOWED

More cautious.
Less efficient.

Planning produced fewer deaths in this test, but used more steps and finished fewer runs.

DEVELOPMENT BENCHMARK / NOT THE LIVE SESSION
MeasurePlanningReactive
Deaths527
Mean steps11092
Wins5 / 3010 / 30

Recorded P3 measurement: 10 seeds × 3 random streams, 120 real steps per seed-run, horizon 12 and 24 candidate sequences. Mean steps include runs that reached the 120-step cap. These are development measurements, not a promise about every run.

Training and prediction run in your browser. The live study starts from an existing trained reference model and continues learning from real moves.

WORLD MODEL / 3 SMALL NEURAL NETWORKSDESIGN + BUILD / JOSH COLE
006 / AUDIO INTO GENERATIVE ART

genSound.

Sound,
made visible.

Actual GenSound output from the Chopin example: concentric rings and a Hilbert arrangement
ONE ANALYSIS / TWO WAYS TO SEE IT
CHOPIN / NOCTURNE OP. 9 NO. 2

Loading the color lab…

HOW IT WORKS

A whole track.
A single field.

The lab measures sound, maps the measurements to color, then places the same moments in two different arrangements.

01 / MEASURE

Overlapping moments.

250,000 windows, each a tenth of a second long. Each window records the note, loudness and strongest frequency.

02 / MAP

Measurements become color.

By default, note chooses hue, loudness drives saturation and strongest frequency sets lightness. Change the rules or palette in the lab. Silence stays black.

03 / ARRANGE

Time takes a shape.

Rings grow outward from the opening. The Hilbert layout keeps nearby moments together. Both show the same analysis.

SOURCE / RECORDINGS / CREDITSView GenSound source ↗

Example recordings: Chopin, Nocturne Op. 9 No. 2, performed by Peter Johnston via Musopen (CC0); Beethoven, Symphony No. 8, iv. Allegro vivace, Musopen recording (public domain); “Hitman” by Kevin MacLeod (incompetech.com), licensed under CC BY 4.0. The recordings are not hosted here.