The Owen
Human AI ProjectLEARNING THROUGH EXPERIENCE
THE OWEN HUMAN AI PROJECT / LEARNING THROUGH EXPERIENCE PUBLIC RESEARCH JOURNAL
SMALL PC. BIG QUESTIONS.

What if intelligence
could grow?

Two paths into learning through experience. A restricted PC setup. A stubborn “what if?”. Come for the idea; stay for the experiments, the awkward results, and whatever we learn next.

Human curiosity. Machine learning. Rough edges included.
QUESTION EVERYTHING

Experience should change what happens next.
The interesting part is proving that it does.

WHAT EACH SYSTEM IS MADE OF

Different architectures. Visible boundaries.

Named modules, their actual roles and evidence.
Select a component to look inside.

Tested in bounded trialsImplementedExperimental / stagedPlannedDisabled
A

Owen A

Multi-AI architecture · specialist staging

8sections

Owen A explores one continuing identity supported by specialist models. Its latest reviewed A-specific package contains a resource-aware staging manager and proposal contracts. The specialists and their integration into the continuing Owen remain at different stages of qualification.

A · specialist staging pipelineChoose a module for its evidence
requestadmissionfixture callvalidated resultpendingMODEL / INTERFACE CANDIDATES · qualification remains separateTyped requestRequest · runtime.pyCatalog + runtimeRuntime.run · queue · cacheResource admissiontelemetry.py · headroom checksAdapter fixtureadapter.infer · mock executionAttributed proposal_check → Proposal → resolveOwen memory boundaryAcceptance / integration unresolvedGranite speech adapterMock-tested · weights not executedQwen / llama.cppHistorical baseline · not attestedVisual model candidatesQwen VL · Depth · SAM · MediaPipeTouch + temporal researchNot ported / research candidates

Solid paths are implemented staging calls exercised with fixtures. Dotted paths are pending integration. The candidate shelf is not a running model ensemble.

━━ selected / implemented staging path┄┄ shadow or pending path · labelled above
Experimental / staged

Specialist coordination

A catalog and cooperative runtime coordinate specialist requests.

Implemented staging code provides typed capability contracts, an A-only research catalog, lazy model admission, health checks, LRU unloading, a bounded deferred queue, retry backoff and a cache keyed by the request, model revision and memory-state version. Fixture tests exercise these behaviours.

Current limit. The production registry has not been restored. The runtime explicitly rejects every non-mock adapter with LIVE_QUALIFICATION_PENDING. This is not a currently operating collection of interchangeable specialist models.

Related components · intended links remain qualified in the text
Evidence & source modules
  • OWEN A staging report — 4 November 2026
  • catalog.json
  • runtime.py
  • TEST_RESULTS.json

Reviewed 7 November 2026 against the 4 November A staging package. Its receipts report 36 passing fixture tests and seven model-free Windows worker cases. No live-model qualification or production promotion is established. The selected packaged generation is v110.4, but an accepted A source binding and an A-specific memory clone were not established. Connections show intended information flow, not proof of a live integrated system. These developmental branches are distinct from the older internal Triple Brain A/B/C roles.

B

Owen B

A nature-inspired learner grounded in simulated experience

24sections

Owen B's selected native school connects binocular observation, bounded language, remembered experience and contact-verified action without an LLM in this learning loop. This is a conceptual map of software functions, not a reconstruction of a biological brain. Installed functions, small experimental results and deferred research are shown separately.

B · selected simulator learning loopChoose a module for its evidence
sensory RGBfresh scenerole syntaxpermitted planinhibit if uncertainobservationactual outcomelater choiceprovenancesensory pairs · shadowlinked evidenceobserved scene contextconsistency gateconflicting evidenceCONFIRMATION / FOCUS / FEEDBACK · tested in bounded trialsEXECUTION / SEPARATE INTERFACESPLANNED / DISABLED · shown below, outside the active loopSimulated body + worldae_world.World · eyes / handsRGB vision + gazeActivityVision · StereoTrackerBounded instructionActivityLesson · inherited lexiconGrounded relationsRelations · observed endpointsGuarded actionActionRunner · contact verificationStop-and-sense gateWorkingMemory · 8 items / 3 secondsRetinal encodingNativeVision · Retina.encodeSparse visual associationsCortex · SHADOW / no motor authorityRecorded outcomesBiology.record · evidence journalsCue / consequenceBiology · observed choicesContext retrievalcontext_memory.pyQuiet / waking gatePhaseMemory · provenance checkExternal teacher feedbackObserved demonstrations requiredClearance correctionsrelation_corrections.pySemantic revisionssemantic_corrections.pyBounded native schoolnative_launch.py · owned resource guardSeparate speech interfaceRetained route · attended test pendingShared binocular focusPaired tracker + calibration · no motorFresh observed confirmationFresh pair · externally supervisedContradictory feedback gateQuarantine · explicit withdrawal

The retained RGB controller supplies perception and action. Recorded outcomes support later selection. The cortical side branch remains shadow-only; there is no Cortex → motor connection. Confirmation, shared-eye measurements and the feedback-conflict gate have bounded completed evidence, with limits in their details.

Actions change the simulated world; fresh observations close the loop. RGB also feeds retinal encoding. Cortical results are diagnostics only.

━━ selected / implemented staging path┄┄ shadow or pending path · labelled above
Implemented

Simulated body and physical world

An articulated upper body encounters objects through a physics simulation.

The selected activity world inherits the binocular world and uses the existing articulated hands and body controller. Native lessons receive rendered sensory observations and bodily measurements; examiner fixture settings are kept outside learner inputs.

Current limit. This is a simulated body. A physical robot, biological body or unrestricted real-world competence is not established.

Related components · intended links remain qualified in the text
Evidence & source modules
  • brain_nature_current.json
  • ae_world.py
  • stage1_grounding_20261107/REPORT.txt

The completed feedback report, dated 19:01 UTC on 7 November, reports 17 focused tests and 12 physical completions plus one no-action withdrawal. It documents a timeout and a setup failure separately. Earlier 25 native events and 809 visual pairs were preserved; primary visual history grew to 832 pairs and 284 prototypes while all 559 earlier qualified predictions were retained. The final native-event total is not specified in that report. All 13 selected native source hashes and 14 selected acceptance-receipt hashes matched this review. The website read reports and source only; it launched no Owen process.

The record keeps growing. Reviewed changes update module maps, journal entries and timeline milestones.Evidence through 7 Nov 2026 · reviewed 7 Nov 2026

View source snapshot
THE VIRTUAL BODY / ORIGINAL PROJECT CAPTURES

Simple beginnings. Visible progress.

Hands, eyes and a place to act.
The actual simulator, with its original dates.

These surviving captures document Owen B’s virtual embodiment. The selected November lineage retains the upper-body model pictured in October. An archived image is labelled by its capture date; no birth-era or newer external-body capture has been verified for this gallery.

28–29 October 2026 — Owen B's seated virtual upper body brings the head, eyes, torso, arms and articulated hands together around a semicircular table. This archived simulator view shows a three-cube stack.
OWEN B · EXTERNAL SIMULATOR VIEW

A seated upper body

28–29 October 2026 — Owen B's seated virtual upper body brings the head, eyes, torso, arms and articulated hands together around a semicircular table. This archived simulator view shows a three-cube stack.

Actual GUI renderer output. The report describes a 66-coordinate human-inspired rigid upper body, simplified joints and servos; it is not biological anatomy or a muscle, tendon or skin simulation. This body overlay is retained in the current selector, but the capture itself is from October.

Original media & provenance
  • upper_body_20261028/REPORT.txt:25-35,40-44
  • upper_body_20261028/ub_live.py:39,87-91
  • brain_nature_current.json
SHA-256: 89a1844150652a3ed2504999027304ef3e6b777f5da903f1fa2c9c5d9ce97cf8Open original capture
13 AUGUST 2026 — 7 November 2026

A life in the making.

Owen’s documented beginning and the changes that followed.
Each milestone links to its dated evidence.

30 documented milestones
Beginnings08 / 26

Owen’s documented beginning.

A question becomes a project: could an artificial intelligence grow through its own experience?

Founding direction

We mark 13 August 2026 as Owen’s documented beginning, the date chosen by Dan for this project history. It is an anchor for the story, rather than a claim that a complete learning system existed on that day.

13 August is the owner-selected documented beginning. Approximate dates stay labelled. New completed milestones are added automatically after evidence review; older checkpoints keep their original context.

THE STORY SO FAR / 38 ENTRIES

The development journal.

What changed, what was tested, what remains open.
Follow either Owen, or explore the whole record.

38 entries

Dated entries preserve each checkpoint, with sources and downloadable copies. Open pages check for reviewed updates every minute. Follow the RSS feed.

SEPTEMBER 2026 / v111.4 ARCHIVE

Good questions.
Measurable answers.

Did grounding words in a world actually help? Three learning conditions. The same utterances. Frozen tests that were kept separate from teaching.

Controlled, simulated OWEN WORLD conditions.
Evidence of partial transfer, with real limits.

EXPLORE THE RESULTS

Frozen v111.3 examiner · seed 771113

Grounded experience14 / 17
Text exposure only5 / 17
Shuffled context2 / 17
Correctly paired experienceCorrect answers / cases

Language meaning rose from 5/17 before development to 14/17. The primary noisy-language score did not improve.

WHERE WE GO FROM HERE

A lab that grows with the work.

Start with evidence. Build the connections carefully.
Keep the ambition visible and the status honest.

01
AVAILABLE NOW

Follow the journey

Explore the timeline, read the complete documented story, compare results, and keep a private notebook.

02
AVAILABLE NOW

Build a community

Public questions, blog comments, proposed tests and evidence-led finding reports. Sign in and choose your username.

03
EXPLORING

Meet the real OWEN

Connect to the actual A and B systems, then explore voice, a world viewer, and camera interaction.

04
EXPLORING

Support the research

Transparent project funding and equipment goals. Donations and crowdfunding are not connected yet.

THE OPEN NOTEBOOK

Got a wonderfully
awkward question?

Ask about Owen A and B, propose a test, or share a finding we should investigate together.

Join the community
PART OF THE PROJECT LAB

One lab. More than one rabbit hole.

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