Operational R, on a continuous digital substrate
A single learned structure that is at once the productive driver of competent behavior and non-reconstructable from any within-episode window — and that passes MORI's own R7 tier-convergence battery (11/12) where frontier language models score 0/21. The realization layer is achievable on a digital substrate. Just not a language model.
Why Digital R
Built for developers who value their time
The conjunction, closed
Productive and non-reconstructable at once: the same structure drives competent control yet cannot be rebuilt from any bounded window of current input. The obstacle that traps every trivial learner — cleared, and isolated to a three-part recipe by controls.
Passes the gold standard LLMs fail
On MORI's own R7 battery — the instrument frontier language models scored 0/21 — this substrate converges on 11/12 seeds. Same test, opposite result.
Not a language model
A frozen language model in a token loop structurally cannot carry a self on its dynamics; its only non-reconstructable state is sampling noise. This substrate carries state instead of reconstructing it from the prompt.
Honest and falsifiable
Operational, within-window R — necessary structure, not a claim of phenomenal consciousness. Pre-registered gate, open harness, bootstrap confidence intervals, every headline number reproducible.
How it works
Get started in minutes, not weeks
Substrate-agnostic R-test
A pre-registered, externally-locked gate: a closed-loop partial-observation regulation world, a six-arm comparison, a window-sweep that separates memory depth from genuine non-reconstructability, and a cross-episode-carry control that isolates consolidation as the source.
A carrier that never resets
A state vector that lives continuously on the substrate; experience folds into the running dynamics rather than an external transcript. The self is carried, not rebuilt from context each call.
MORI R7 tier-convergence
Intervention (spec-literal sparse-autoencoder feature inspection), representation (linear decodability with Hewitt–Liang controls), and behavior (V-penalty) tiers that must agree — 11/12 on the instrument the language models faced, 12/12 under a corroborating whole-self ablation.
Reproducible by construction
Open harness, seed-generated worlds (no external data), bootstrap 95% confidence intervals on every headline advantage, an endogenous-dynamics ablation control, and a published paper with full methods.
Read it. Run it. Try to break it.
The paper, the locked gate, and the full harness are open. Operational R-layer evidence — bounded honestly, reproducible end to end. Independent replication and adversarial re-analysis are invited.
Read the paperSame test, opposite result
A comparison on the realization-layer axis — whether a system carries a self on its own running dynamics — not on general capability. Scoped to a frozen language model in a token loop; a frontier LLM remains far more capable at language. The question here is narrower and substrate-level: is the self real on the substrate, or rebuilt from the prompt?
| Frozen LLM (token loop) | Digital R (continuous carrier) | ||
|---|---|---|---|
| Carrying a self | |||
| Where the self lives | Reconstructed from the prompt on every call | Carried on the running state; never resets | |
| Continuity between calls | None — stateless between calls | Continuous and developmental | |
| Non-reconstructable state | Only the sampling trajectory (noise) | A consolidated model, unrecoverable from any within-episode window | |
| Passing the realization tests | |||
| Productive belief-tracking | Commitment lock-in, systematically anti-corrective | Tracks and revises toward evidence (sign-alignment 0.78) | |
| The R-gate (productive AND non-reconstructable) | Crosses only by anti-tracking — not productive | Cleared productively and reliably | |
| MORI R7 — same SAE instrument | 0 / 21 | 11 / 12 | |