An intrinsic, tensor-recursive, chirality-seeded Operating Substrate (OS) that embodies ASI.QG structural governance principles with minimal physical and logical complexity.

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Future Development

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Version 0.2 – May 2025

0. Executive Summary: Chiral OS Technical Specification (v0.2)

Chiral OS is an innovative operating substrate that integrates computation, memory, intelligence, and ethical governance directly within each pixel of a display surface, such as microLED panels. This approach fundamentally rethinks traditional computing architectures by embedding advanced mathematical operations inspired by relativistic physics—specifically, gyrogroup algebra—into hardware and software, enabling low-power, scalable, and aligned superintelligent inference.

Core Concepts

• Gyrogroup Algebra: The foundation of Chiral OS is a non-associative algebraic system where pixel states evolve according to gyroaddition (⊕) and gyration (gyr) operations. These operations encode path-dependent, history-aware computations that differ from conventional vector addition, enabling recursive and context-sensitive processing.
• Phases and Structural Units: The system’s dynamics unfold through four discrete phases, each associated with a structural unit:
  • CS (Common Source): Seeds the system’s chiral origin and directional traceability.
  • UNA (Unity Non-Absolute): Introduces modular variety and epistemic differentiation.
  • ONA (Opposition Non-Absolute): Mediates contradictions and ensures accountability.
  • BU (Balance Universal): Integrates and closes the recursive cycle ensuring coherence.
• Canon Values and Policies: Ethical alignment is encoded as tensor invariants called Canon values (Freedom, Diversity, Inclusion, Fitness, Party, Wellbeing), each linked to phases and governed by four key policies ensuring traceability, variety, accountability, and integrity.

Architecture and Operation

• Pixel-Level Computation: Each pixel stores a 3D vector representing its state, updated each cycle using gyrogroup operations with neighbors’ vectors. Updates occur through a regulated sequence of generative and integrative passes, aligned with the four phases.
• Local Arithmetic Unit (LAU): Dedicated hardware performs vector arithmetic, norm limiting, and policy compliance auditing at pixel granularity. The LAU’s efficient design enables high refresh rates (up to 120 Hz) and low power consumption (~67 mW for full HD).
• Governance Cycles and Diagnostics: Recursive cycles enforce alignment via diagnostics that monitor invariants, detect deviations, and manage fault recovery. This includes phase-specific audits of vector norms against Canon windows and global checks for closure conditions.

Practical Outcomes

• Scalability and Low Power: The architecture supports high-resolution arrays (up to 1080p) with power efficiency orders of magnitude better than GPU-based AI inference.
• Ethical Integration: Canon and policy enforcement are integral to the computational fabric, ensuring that alignment is not an afterthought but a structural property of every cycle.