VirtualTissueExplore GitHub

A computational tissue experiment

A tissue of cells.
A world of individual decisions.

What if every cell were an AI agent, sensing its surroundings and acting within the rules of biology?

Meet VirtualTissue. A virtual gut where local signals and constrained cellular choices shape the tissue together.

Watch the experimentsDiscover the idea

Recorded demonstrations · No sign-in · No live AI calls

Conceptual gut tissue cutaway: each epithelial and immune cell contains a separate luminous network representing its own AI agent.
FIG. 01 Many cells. Individual agents. One shared environment.Conceptual illustration
100individual cells
8cell identities
4recorded scenarios
0API calls during replay

01 / The idea

Intelligence at the scale of a cell

Each cell has
its own point of view.

No cell sees the whole tissue. Each reads its local environment, carries its own state, and responds from a limited set of possible actions.

The live research model asks Jev / TypeSafe AI a separate, structured question for each eligible cell. An executable biological manual defines what that cell is allowed to do.

Follow a cellular decision
Conceptual cell agent receiving nearby signals and selecting one available response while other response paths are blocked.
FIG. 02 Local input → constrained choice → local effect.Conceptual illustration
01

Sense locally

Nearby signals, physical contacts and the cell’s own condition define its view.

02

Choose within constraints

Cell identity, resources and the manual determine the available actions. Waiting is always an option.

03

Change the neighborhood

Actions take biological time. Their physical effects can change what neighboring cells sense next.

02 / Inside a decision

An illustrated walkthrough

Small decisions.
Shared consequences.

Follow the path from a local signal to a recorded effect. The manual, the choice and the physical outcome each have a distinct role.

01 / LOCAL OBSERVATION

A signal reaches one cell.

A cell reads nearby signals, contacts and its own state. A local departure can make it eligible for a decision; quiet cells are not queried.

Local sensing only. No tissue-wide view is passed to a cell.

03 / Explore the recordings

Real saved runs. Replay in your browser.

One tissue.
Four starting conditions.

Play, pause and scrub through each experiment. Select a cell to inspect its saved observations, choices and completed effects.

About these demonstrations These recordings use a deterministic fixture policy, not live AI responses. They demonstrate the simulation and its audit trail. Playback makes no AI or API calls.

Same starting seed. Independent runs. Every decision is saved, even between visual frames. Open your own recording

04 / Built to be inspected

An open experiment.
A traceable model.

Follow the reasoning all the way down to the rules, recorded state and executed effects.

Explore the source
What does the model demonstrate?

A 100-cell gut microdomain with eight cell identities, local sensing, constrained individual choices, finite resources and explicit event clocks. A 2D physical slice is presented as a 3D cutaway.

What does “each cell is an AI” mean?

Each cell is modeled as an individual agent with its own state and local observations. In live experiments, Jev chooses among legal actions for eligible cells. Cells do not each train a separate model, and quiet cells do not make requests. This website only replays recorded fixture demonstrations.

What are the scientific limits?

This is an uncalibrated mechanistic demonstration, not a validated biological predictor. Choice probabilities are not biological event rates. IBD-like injury represents a limited innate inflammatory challenge, not a complete disease model.

Where are the rules and evidence?

Manual v3 documents the mechanisms, assumptions and primary references. It defines 56 action contracts; 22 physical handlers are implemented. Unsupported actions stay blocked.

Read the complete manual ↗

The people behind the project

Conceived and created by Helder Nakaya, leader of CSBL and founder of Hylix.app. Developed with ChatGPT and Claude as AI collaborators.

Project credits ↗