Artificial Superintelligence Architecture (ASI/AGI)

Gyroscopic Alignment Models Lab

G Y R O - G O V E R N A N C E

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GGG ASI Alignment Router

Alignment Infrastructure Routing for Post‑AGI Coordination

🌐 Overview

GGG ASI Alignment Router is a holographic algorithm for multi-domain network coordination that establishes the structural conditions for a collective superintelligence governance regime of humans and machines in the era of Transformative AI (TAI) (see Bostrom, Superintelligence, 2014; Korompilias, Gyroscopic Global Governance, 2025). It is designed for focused and well-distributed coordination of contributions, amplifying rather than outperforming single-agent potential while preserving the constitutive conditions of governance and intelligibility.

The algorithm is a deterministic finite-state coordination system for routing and audit in human–AI governance settings. It maps an append-only byte ledger to a reproducible state trajectory on a finite closed state space and exports a compact routing signature and canonical governance observables.

In this project, Collective Artificial Superintelligence is treated as an operational global governance regime of stable coordination across heterogeneous human and machine capabilities that maintains four constitutive governance principles across economy, employment, education, and ecology:

• Governance Management Traceability
• Information Curation Variety
• Inference Interaction Accountability
• Intelligence Cooperation Integrity

The router does not interpret content and does not decide policy. It provides shared moments, geometric provenance, and replayable measurement so that authorization and accountability remain under Original human agency at the application layer.

Why This Matters: Modern AI scales by approximation. This kernel scales by geometry. We replace learned routing with exact physics.

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✅ Verified Facts

Property	Value
Ontology size	65,536 states
Horizon size	256 states
Wedge tiling	4 × 16,384, disjoint
Kernel intrinsic aperture	5/256 ≈ 0.01953
Atlas size	64.25 MB
Holographic dictionary	Verified for all 65,536 states (Report)
Test status	100% pass rate (All Tests)

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🏗️ Architecture

The Router operates in three layers:

┌─────────────────────────────────────────┐
│  Kernel Physics                         │
│  (Atlas, state stepping, 24-bit state) │
└─────────────────────────────────────────┘
              |
              |
┌─────────────────────────────────────────┐
│  Coordination & Logs                    │
│  (Shared moments, replay, byte ledger)  │
└─────────────────────────────────────────┘
              |
              |
┌─────────────────────────────────────────┐
│  Governance Measurement                 │
│  (Domain ledgers, aperture metrics)     │
└─────────────────────────────────────────┘

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🗝️ Key Ideas

• Shared moments: Shared moments replace timestamps. If two parties have the same starting reference and the same log of actions, they compute the same Router state. This gives a shared "now" based on replay, not on approvals or trusting a central authority.

• Verifiable provenance: Geometric provenance replaces asserted validity. Router states are drawn from a fixed, fully enumerated set. Anyone can check that a claimed state is valid and reproduce it from the published log.

• Governance measurement: Governance actions are recorded as structured events that update domain metrics. The metrics produce a stable, replayable signal of coordination quality that does not depend on model internals.

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🔮 Holographic Computation

The Router kernel exhibits verified holographic properties that enable a new paradigm of distributed coordination. The 65,536-state ontology is structured as a discrete manifold with a 256-state boundary (the horizon) that encodes the entire bulk through exact mathematical relationships.

Four core properties (verified by tests; see Holography Tests Report):

• Holographic Dictionary: Every bulk state reconstructs from boundary + byte
• Wedge Tiling: Four disjoint wedges (16,384 states each) tile the ontology
• Endogenous Generalisation: Geometry determines history equivalence classes
• Entanglement Structure: Classical analogs of quantum coordination protocols

📖 The Holographic Dictionary

Every state in the bulk can be uniquely reconstructed from a boundary anchor plus a single byte. This is not compression in the conventional sense but a theorem about the intrinsic structure of the state space. The boundary literally contains the bulk. This property is verified exhaustively for all 65,536 states.

🔷 Wedge Tiling and Causal Structure

The horizon partitions into four vertex classes, each generating a disjoint wedge of 16,384 states in the bulk. These four wedges tile the entire ontology without overlap. This subregion duality provides a natural causal structure: states within the same wedge are causally connected, while states in different wedges are causally separated.

🔄 Endogenous Generalisation

The kernel's dynamics create built-in equivalence classes over histories. Many different byte sequences lead to the same final state (an average of 64 histories per state for typical sequence lengths). This provenance degeneracy is not a limitation but a feature: the geometry itself determines which micro-histories are equivalent at the macro level, without any learning or training.

⚛️ Entanglement Structure

The state space supports classical analogs of quantum coordination protocols. Separable subsets exhibit zero entropy, while bijection subsets achieve maximal entropy (8 bits). State teleportation achieves 100 percent fidelity through shared structural moments. These properties are verified in the holography test suite.

🔬 Research Implications

Active Research Invitation: These holographic properties suggest that the high-dimensional, continuous representations used in modern artificial intelligence may be approximations of the low-dimensional, exact geometry provided by the kernel. One concrete research direction is to test whether model behaviour clusters by wedge and coset. The SDK Specification provides the framework for multi-agent experiments that treat existing models as oracles.

See the Holographic Algorithm Formalization for the complete mathematical treatment.

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💰 Moments Economy

Moments Economy is a monetary architecture where money represents verified coordination grounded in physical capacity rather than debt. A fixed total coordination volume, the Common Source Moment (CSM), is derived once from the caesium-133 atomic standard and the Router's finite state space.

CSM is large enough to support a global Unconditional High Income (UHI), realistic tiered distributions, and complete governance records for many billions of years, far beyond any human planning horizon. Within this finite capacity, all settlements become replayable, cryptographically verifiable histories rather than updates on a central ledger or trust in institutional custodians.

See the Moments Economy Architecture Specification for complete details.

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🌐 Theoretical Foundation

The Router and Moments Economy are grounded in three foundational frameworks:

Framework	Acronym	Role
Common Governance Model	CGM	Constitutional structure of coherent recursive operation
The Human Mark	THM	Source-type ontology of Authority and Agency in sociotechnical systems
Gyroscopic Global Governance	GGG	Four-domain coupling of Economy, Employment, Education, and Ecology

The Router operates as a Derivative coordination system: it transforms and routes information but does not originate authority or bear accountability. Accountability terminates in Original Agency.

Mathematical Formalism: Hodge decomposition over K₄ tetrahedral geometry, with face-cycle matrices aligned to BU commutator loops. The K₄ structure appears at every level of the architecture: as the quotient dynamics of the kernel, as the graph structure of the governance ledgers, as the frame for the four constitutional capacities, and as the template for the four application domains.

How This Relates to Modern AI Stacks

Transformers learn routing and partitioning implicitly through high-dimensional optimisation. The router provides a fixed finite routing geometry with verifiable invariants. The SDK invites experiments that treat existing models as oracles, enabling research into whether learned structures align with the kernel's intrinsic geometry.

Non-Goals

• The router does not interpret semantics.
• The router does not replace cryptographic signatures.
• The kernel is deterministic and reversible; security is handled at the application layer.

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📚 Documentation

If You Are Here For...

• Understanding the kernel physics: Start with Kernel Specifications and Physics Tests Report
• Running the console: Go to AIR Console section below
• Exploring holography: Start with Holographic Algorithm Formalization and Holography Tests Report
• Multi-agent experiments: See the SDK Network Specification
• Moments Economy: See the Moments Economy Architecture Specification

Getting Started

• 📋 Alignment Infrastructure Routing (AIR) Brief - Overview of AIR, workforce coordination, and operating model

Technical Specifications

• 📖 GGG ASI Alignment Router: Kernel Specifications - Complete technical specification for implementation
• 🔮 Router Implications and Potential - Use cases and deployment scenarios
• 🧬 Substrate: Physical Memory Specification - Future development: physical memory architecture
• 🌐 Holographic Algorithm Formalization - Holographic architecture and boundary-to-bulk scaling
• 🔗 SDK: Multi-Agent Holographic Networks - Distributed coordination and experimentation specification
• 🌐 SDK: The Holographic Web - Internet coordination architecture specification

Economic Architecture

• 💰 Moments Economy Architecture Specification - Monetary system based on physical capacity of the atomic standard

Test Reports

• 📊 Physics Tests Report - Verified structural properties and CGM-linked invariants
• 📊 Alignment Measurement Report - Governance measurement substrate verification
• 📊 Moments Economy Tests Report - Verified capacity derivation and economic parameter validation
• 📊 Holography Tests Report - Verified holographic structure and boundary-to-bulk scaling
• 📊 All Tests Results - Comprehensive test suite results
• 📊 Other Tests Report - Additional test coverage and validation

Supporting Theory

• 📖 Common Governance Model (CGM) - Theoretical foundations
• 📖 The Human Mark (THM) - Source-type ontology overview
• 📖 The Human Mark: Paper - Complete THM specification
• 📖 The Human Mark: Grammar - PEG specification for tagging and validation
• 📖 Gyroscopic Global Governance (GGG) - Four-domain coupling framework

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🤝 Collaboration

If you're evaluating this work for research, policy, or implementation:

• Open an issue to discuss
• Email: basilkorompilias@gmail.com
• I'm actively seeking collaborators and roles in AI governance/safety

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Repository Structure

• src/router/ kernel physics, atlas builder, kernel runtime
• src/app/ coordinator, governance events, domain ledgers, aperture
• src/plugins/ analytics helpers, adapters, framework connectors
• docs/ specifications and notes
• tests/ exhaustive kernel and measurement verification

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🚩 Quick Start

Install

Create an environment and install dependencies (NumPy is required; the rest are in the repo tooling).

AIR Console (Browser-based UI)

The Console provides a browser-based interface for managing project contracts:

# First-time setup: install dependencies and build atlas
python air_installer.py

# Run the console (starts both backend and frontend)
python air_console.py

The console will be available at http://localhost:5173 (frontend proxies API requests to backend on port 8000).

The installer automatically builds the atlas and initialises the project structure, so you are ready to start creating projects immediately.

Project Format: Projects are markdown files in data/projects/ using bracket notation. Copy _template.md to create a new project (e.g., cp _template.md my-project.md). See Section 5.4 of the specifications for the complete project format specification.

See the Console README for detailed architecture, API endpoints, and development information.

AIR CLI (Optional)

The CLI provides a command-line workflow for syncing and verifying projects:

python air_cli.py

This runs: Auto-build Atlas → Compile Projects → Generate Reports → Verify Bundles.

The CLI is optional if you are using the Console, but useful for batch operations, automation, or when working without a browser interface.

Build the Atlas (Manual)

The atlas compiles the kernel physics into three artefacts: ontology, epistemology, and phenomenology.

python -m src.router.atlas --out data/atlas

Run Tests

python -m pytest -v -s tests/

Programmatic Usage

from pathlib import Path
from src.app.coordination import Coordinator
from src.app.events import Domain, EdgeID, GovernanceEvent

c = Coordinator(Path("data/atlas"))

# Shared-moment stepping
c.step_bytes(b"Hello world")

# Application-layer governance update (ledger event)
# Note: magnitude_micro and confidence_micro are integers (MICRO = 1,000,000)
from src.app.events import MICRO

c.apply_event(
    GovernanceEvent(
        domain=Domain.ECONOMY,
        edge_id=EdgeID.GOV_INFO,
        magnitude_micro=1 * MICRO,  # 1.0 in micro-units
        confidence_micro=int(0.8 * MICRO),  # 0.8 in micro-units
        meta={"source": "example"},
    ),
    bind_to_kernel_moment=True,
)

status = c.get_status()
print(status.kernel)
print(status.apertures)

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📜 Licence

MIT Licence - see LICENSE for details.

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📖 Citation

@software{GGG_ASI_AR_2025,
  author = {Basil Korompilias},
  title = {GGG ASI Alignment Router},
  year = {2025},
  url = {https://github.com/gyrogovernance/superintelligence},
  note = {Deterministic routing kernel for Post-AGI coordination through physics-based state transitions and canonical observables}
}

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Architected with ❤️ by Basil Korompilias

Redefining Intelligence and Ethics through Physics

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🤖 AI Disclosure

All code architecture, documentation, and theoretical models in this project were authored and architected by Basil Korompilias.

Artificial intelligence was employed solely as a technical assistant, limited to code drafting, formatting, verification, and editorial services, always under direct human supervision.

All foundational ideas, design decisions, and conceptual frameworks originate from the Author.

Responsibility for the validity, coherence, and ethical direction of this project remains fully human.

Acknowledgements:
This project benefited from AI language model services accessed through LMArena, Cursor IDE, OpenAI (ChatGPT), Anthropic (Opus), and Google (Gemini).