S·GSIHTI GRAPH / IMAGE MODEL
RESEARCH PROTOTYPE / OCTOBER 2026

A visual memory is
something you can question.

What if the image doesn't survive as pixels, but as a changed propagation medium? Two different orders of probing the same conductance graph may reveal different relationships.

QUESTIONΔ(q;W) = A(W)B(W)q − B(W)A(W)qORDER-SENSITIVE RESIDUE
Explore the operators ↘No pretrained weights · No biological claims · Same byte state
896 bytesper-image graph payload
4directed edge fields
14 × 16graph sites
AB ≠ BAhypothesis to test
01 / EXPLORE

The probe laboratory

Interactive *analytic* demonstration. Conductances are computed from the image, not produced by the trained Python writer.

A / THE OBSERVATION 14 × 16 RGB

Pixels are read once to write W. Subsequent probes use only the byte-valued conductance fields.

B / WRITTEN MEDIUM EAST CONDUCTANCE

The four edge fields occupy exactly 14 × 16 × 4 bytes, including forbidden-edge padding.

C / ORDER: AB A AFTER B

First transport along B's edges, then along A's.

D / ORDER: BA B AFTER A

The identical graph and query, interrogated in reverse order.

E / COMMUTATOR AB − BA

Signed order-sensitive differences. Bright means amplitude, not proven semantic significance.

F / ORDER-BLIND (AB + BA)/2

A matched two-order read that removes the antisymmetric component.

Order-sensitive RMS—
Order-blind RMS—
Relative difference—
Interpretation

Nonzero difference = order matters for this operator and query. It does not prove a mark was decoded. Run the trained held-out experiment below.

02 / IDEA

Memory in the medium

Input-written edge values replace pixel activity as the stored state. A new query can then traverse the same graph by different paths.

01

ETCH

Encode one image into four directed uint8 conductance fields. The trained PyTorch version uses a convolutional writer with byte rounding in the forward pass.

W = round(255 × Eθ(I))
02

PROBE

Apply A and B to a fresh, question-conditioned signal. Uniform filters commute; image-written edge weights generally need not.

ABq ≠ BAq
03

COMPARE

Ask whether the antisymmetric component predicts an unseen answer better than matched order-blind reads and a direct-graph decoder.

Δ = ABq − BAq
03 / TEST

A result that can fail

One trainable writer, five comparison arms, untouched held-out scenes. The code records results rather than inventing a successful benchmark.

THE TASK

Which color is the tiny mark on the queried object?

The synthetic image contains two textured objects and 2×2 red/blue marks. The reader receives only 896-byte W and a query for left or right. The source pixels are inaccessible after writing.

Heads for ordered pair, commutator, symmetric mean, isotropic two-step, and raw W have matched trainable parameters. Ordered and commutator probes consume four transports. Direct-W is an explicit memory-access upper baseline, not compute-matched.

Read frozen protocol ↗
● ● ● RUN LOCALLY / RTX 3060 OR CPU
pip install -r requirements.txt
pytest -q

python train.py --seed 41 --steps 450
python train.py --seed 97 --steps 450

JSON receipts → results/seed*.json

Boundary of the claim. An order-sensitive response may reveal useful stored information, but the paired raw responses cannot contain less information than their subtraction. Finite boundaries also create artifacts. Neither myelin nor the October lipid atlas is a measured mechanism in this model; they motivate considering the physical medium as part of computation.