AGI OS
SCILOOP / SELF-IMPROVING VISUAL ENGINE

Current Best Engine

Design → optimize → generate → test → learn → evolve.

Ready for a concept
EVOLUTION LOOPAwaiting run
1Design Flow
2Optimize
3Generate Engine
4Generate Experience
5AI Score
6Human Test
7Telemetry
8Improve
PROMOTED CANDIDATE
C0000
Engine V0 · not promoted
0.0overall score
GENERATED LEARNING EXPERIENCE
01Encounter reality
02Open question
03Commit prediction
04Manipulate variable
05Run model
06Observe result
07Find pattern
08Build hypothesis
09Test again
10Update confidence
11Discover rule
12Compress explanation
13Transfer challenge
14Independent mastery
STATE MACHINEExecutable learning logic
S01Encounter realityadvance / observe
S02Open questionadvance / observe
S03Commit predictionadvance / observe
S04Manipulate variableadvance / observe
S05Run modeladvance / observe
S06Observe resultadvance / observe
S07Find patternadvance / observe
S08Build hypothesisadvance / observe
S09Test againadvance / observe
KNOWLEDGE GRAPHA new concept
ObjectA new concept92%
PropertyA new concept characteristics76%
RelationA new concept connections69%
ProcessA new concept changes over time73%
VariableObservable variables64%
RuleTestable rule to discover58%
UnknownOpen question41%
VISUAL LANGUAGEReplaceable primitive mapping
ObjectA new conceptRepresent object as an observable change
MotionA new concept characteristicsRepresent property as an observable change
TimeA new concept connectionsRepresent relation as an observable change
RelationshipA new concept changes over timeRepresent process as an observable change
ForceObservable variablesRepresent variable as an observable change
EnergyTestable rule to discoverRepresent rule as an observable change
ProbabilityOpen questionInvite a prediction
SIMULATION PIPELINEAdapter-ready execution
  1. 1Initialize learner stateready
  2. 2Commit predictionready
  3. 3Run modelmodular adapter
  4. 4Observe resultmodular adapter
  5. 5Test againmodular adapter
  6. 6Update confidencemodular adapter
  7. 7Evaluate telemetrymodular adapter
  8. 8Compare predicted vs human resultsmodular adapter
Run 0awaiting simulation
SCORING BREAKDOWNAI prediction vs human result
Understanding48
Retention52
Attention39
Prediction accuracy37
Transfer learning43
Mastery probability52
Overall engine score55
Predicted 0Human —Delta —
OPTIMIZATION HISTORYPromoted engine versions

Run Optimize & Promote to create Engine V1.

EVOLUTION TELEMETRYCurrent vs previous best
Current engine——
AI / human gapAwaiting human testConnect real learner telemetry to improve scoring
The engine stays domain-independent. Only the loaded knowledge graph changes.
GENERATED LEARNING EXPERIENCE / V1

Gravity, felt before it is explained

The promoted engine turns an unknown concept into a short prediction → simulation → discovery loop.

understanding signal0%
1curiosity
2prediction
3simulation
4transfer
5mastery
apple
pull toward Earth
Earth
CURIOSITY

Something is holding everything down.

Look at the apple. Before we explain anything, make a guess about what will happen when it is released.

visual language activeObject · Motion · Force · Context · Interactionno prior knowledge required