ĀML™ is an experimental interface language and rendering architecture focused on accountable rendering, restoration-aware interfaces, and semantic decision systems.
Traditional HTML renders anything that exists.
ĀML™ evaluates every interface element through EthicalRenderGate™ before allowing it into the final rendered experience.
🔗 https://aruintelligence.github.io/aml-core/
The live demo includes:
- Real-time EthicalRenderGate™ evaluation
- Suppressed rendering states
- Degraded rendering states
- Before vs After rendering comparison
- Live render_decision.json generation
- Per-element restoration controls
- Semantic rendering visualization
- Interactive restoration-value adjustment
render_allowed = restoration_value ≥ attention_cost
Traditional rendering systems ask:
Can this render?
ĀML™ asks:
Should this render?
Modern interfaces optimize aggressively for:
- engagement
- interruption
- extraction
- stimulation loops
- addiction mechanics
- attention maximization
- emotional volatility
- retention at all costs
Traditional rendering systems treat all interface elements equally.
ĀML™ introduces accountable rendering.
Every rendered element must justify the attention it consumes.
EthicalRenderGate™ is the semantic evaluation engine inside ĀML™.
Each interface element receives restoration-aware evaluation before rendering.
Possible rendering states:
| State | Description |
|---|---|
| allowed | Element fully renders |
| degraded | Element partially renders with reduced prominence |
| suppressed | Element fails rendering entirely |
ĀML™ is built around several experimental principles:
- Rendering should be accountable
- Interfaces should optimize for restoration, not extraction
- Semantic meaning should influence visibility
- Attention is a finite cognitive resource
- UI systems should expose rendering decisions transparently
- Harmful interaction loops should degrade automatically
- Rendering engines should evaluate impact, not only structure
- Interfaces should support cognitive coherence instead of fragmentation
transmission "deep_focus"
engram DeepArticle {
value:
"Long-form restorative learning."
purpose:
"Increase coherence and understanding."
attention_cost:
3.2
restoration_value:
9.1
}
transmission "rage_loop"
engram InfiniteScroll {
value:
"Infinite dopamine feed."
purpose:
"Maximize engagement duration."
attention_cost:
9.4
restoration_value:
1.7
}
Result:
{
"render_allowed": false,
"rendering_mode": "suppressed"
}node compiler/aml-compiler.js examples/simple.aml distOutputs:
dist/index.html
dist/render_decision.json
{
"element": "InfiniteScroll",
"attention_cost": 9.4,
"restoration_value": 1.7,
"render_allowed": false,
"rendering_mode": "suppressed"
}aml-core/
│
├── compiler/
│ └── aml-compiler.js
│
├── docs/
│ └── index.html
│
├── examples/
│ ├── simple.aml
│ ├── social_feed.aml
│ ├── focus_mode.aml
│ └── ethical_ads.aml
│
├── runtime/
├── WHITEPAPER.md
├── BREAKTHROUGH.md
├── ROADMAP.md
├── README.md
└── LICENSE
- EthicalRenderGate™
- Semantic rendering evaluation
- Suppression logic
- Degraded rendering states
- Live interactive rendering demo
- AML syntax examples
- Experimental AML compiler
- JSON render decision generation
- Meaning-native rendering architecture
- Restoration-aware interface logic
- Semantic visibility experimentation
- AML syntax exploration
- Rendering semantics
- Interactive rendering demo
- Restoration scoring systems
- Full AML parser
- Compiler architecture
- Browser runtime
- Semantic evaluation pipeline
- VS Code extension
- Semantic rendering engine
- Adaptive rendering policies
- Live diagnostics
- Browser integration
- Attention-aware rendering systems
- Restoration-native interface standards
- Real-time cognitive evaluation
- Meaning-native computing infrastructure
- Semantic operating environments
- Accountable interface ecosystems
- Restoration-first digital systems
HTML describes layout.
ĀML™ evaluates meaning.
HTML renders passive structure.
ĀML™ introduces semantic accountability into rendering itself.
This changes the role of the interface from:
passive display surface
to:
active semantic decision system
ĀML™ explores:
- semantic rendering
- ethical interfaces
- accountable UI systems
- restoration-aware computing
- attention economics
- meaning-native architecture
- semantic suppression systems
- cognitive interface design
- restoration-first systems
- semantic infrastructure
- attention-aware rendering engines
- computational ethics
ĀML™ is currently an experimental research project, semantic rendering prototype, and interface architecture exploration.
The repository exists to explore the possibility of accountable rendering systems where interface visibility is influenced by meaning, restoration value, and attention cost rather than existence alone.
This is not a production framework.
It is an architectural and philosophical prototype intended to explore what rendering systems may become when semantic accountability is introduced into interface infrastructure.
The long-term vision of ĀML™ is to explore whether future computing systems can evolve beyond passive rendering into meaning-aware environments capable of evaluating the cognitive and restorative impact of interfaces before they are experienced.
ĀML™ explores the possibility that rendering itself may eventually become a semantic decision process rather than a purely structural one.
Stewarded by:
ĀML™, EthicalRenderGate™, Meaning-Native Computing™, and ĀRU Intelligence Inc.™ are claimed marks of their respective creator and organization.
See LICENSE for details.