Cognitive · Active research

A trainer that rears cognition, not one that fits it.

A developmental trainer for cognition substrates — grounding, not memorisation.

“como mi madre” — ground first, generalise second.

What Atelier is

A curriculum, not a fine-tune.

Atelier is built on the conviction that the right way to train a substrate is the way a child is reared: by perceiving, producing, being corrected, binding, and consolidating, all on a two-timescale schedule. It is the conductor that wires the substrate, the structured memory, the fine-tuning framework, and the cognitive gym into a single curriculum — and the layer where we measure whether that curriculum actually produces grounded behaviour rather than a lookup table.

The conductor wires substrate, structured memory, the fine-tuning framework, and the cognitive gym into a single rearing loop — and the verifier sits in the middle so progress is never faked.

The loop

Five steps, every episode.

The constants are the steps. What changes is the world the student is reared in.

  1. AM1

    Perceive

    Evidence comes in from one or more modalities — including a live resource channel.

  2. AM2

    Produce

    The student acts under a grounded production objective. No shortcut paths.

  3. AM3

    Correct

    A typed entailment verifier checks the production. No faked rewards.

  4. AM4

    Bind

    Successes bind into structured memory with role-swap and multi-hop recall.

  5. AM5

    Consolidate

    A two-timescale CLS step folds the binding into lifelong identity.

Milestones

What we have measured.

  1. Phase 1

    Decisive head-to-head landed

    Three rearing pathways compared in isolation. Traditional grounded training works; a distillation shortcut collapses to lookup; the developmental loop grounds the world cleanly.

    grounded 1.00shortcut 0.00lookup 1.00
  2. Phase 2

    Honest verifier built

    A typed entailment verifier with no fallback masking. Reward goes NaN when entailment goes NaN. Live arXiv path opt-in and auth-gated.

    no faked NLINaN propagationauth-gated
  3. Phase 4

    Lifelong identity measured

    Consolidating runs retain all prior worlds. Amnesiac controls forget catastrophically. The gap holds across seeds.

    forgetting +0.00retention 1.00amnesiac forget +1.00
  4. Today

    Multi-seed, twelve improvements landed

    A six-improvement batch closed with multi-seed error bars. Slot-factored relational binding wins cleanly. Architectural-priors claim falsified honestly.

    n=5slot vs byte +0.36arch-priors falsified

Measured (multi-seed, n=5)

Grounded, not memorised.

+0.65 ± 0.02

Lifelong retention advantage

Consolidating runs vs amnesiac controls, multi-seed.

1.90 ± 0.14 ×

CLS sample efficiency

Two-timescale CLS schedule vs single-timescale baseline.

+0.36

Slot-factored vs byte-level binding

Held-out relational retrieval, role-swap held out.

Decisive head-to-head

The B-collapse, in one chart.

Three rearing pathways under matched compute. The distillation shortcut looks attractive on lookup tasks and disappears on grounded production.

A — Traditional grounded

Standard LM, grounded objective

1.00

B — Distillation shortcut (grounded)

Collapses on held-out production

0.00

B — Same model on lookup

The shortcut becomes a table

1.00 (lookup)

C — Developmental loop

Atelier, two-timescale CLS

1.00 (loss ≈ 0)

Note: C−B advantage on grounded production = +0.79 ± 0.18 across seeds. C>A is not clean (±0.24). The robust win is rearing-method, not architecture.

What we falsified

Negatives we publish anyway.

Because the verifier never fakes a signal, Atelier is also the place where we publish what does not work.

“We rear cognition. We do not fit it.”
Atelier design note

Where the curriculum runs

What Atelier is for.

Models

Training the flagship lines

RL-X1 is reared inside Atelier. The loop is what turns the substrate plus structured memory into a usable model — not a fine-tune script.

See RL-X1 →
Continual

Learners that do not forget

CLS-style two-timescale schedule is the basis for the continual line. Lifelong retention is measured, not assumed.

See RL-C1 →
Research

A platform for honest negatives

Two paradigm-sized falsifications have already gone through. The verifier is the reason the publishing bar stays high.

See evals →

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