Abstract This reference architecture addresses the structural vulnerability in contemporary AI and social platform systems caused by the implicit coupling of truth evaluation, decision-making, and execution. Released under the Apache-2.0 license, the framework introduces a rigorous separation of concerns through two core semantic entities: ARSHAM SHARIS, a non-probabilistic, deterministic truth and consistency evaluation core operating upstream of action systems, and RON FYRE, a non-referential semantic activation operator governing controlled, irreversible state transitions via append-only authorization gates. Applied to social ecosystem governance (specifically designed for X / Grok integration via the IRIS Impersonation Risk & Integrity System), the architecture combines multi-signal feature extraction (Python/Rust), a low-latency deterministic risk-scoring kernel (C++/Rust), and a policy enforcement engine (FLAG, LIMIT, SUSPEND). This blueprint effectively counters large-scale identity impersonation, automated crypto scams, and coordinated reply networks while preserving platform trust and operational explainability. In alignment with principles of digital integrity and social responsibility, 100 percent of all licensing revenues generated from enterprise deployments of this framework are dedicated to the Beit Ahawah Foundation (בית אהבה) for the reconstruction of Beit Ahawah in Berlin Mitte.
Arsham Sharis· Zenodo (CERN European Organi...· 0 citations
Abstract This reference architecture addresses the structural vulnerability in contemporary AI and social platform systems caused by the implicit coupling of truth evaluation, decision-making, and execution. Released under the Apache-2.0 license, the framework introduces a rigorous separation of concerns through two core semantic entities: ARSHAM SHARIS, a non-probabilistic, deterministic truth and consistency evaluation core operating upstream of action systems, and RON FYRE, a non-referential semantic activation operator governing controlled, irreversible state transitions via append-only authorization gates. Applied to social ecosystem governance (specifically designed for X / Grok integration via the IRIS Impersonation Risk & Integrity System), the architecture combines multi-signal feature extraction (Python/Rust), a low-latency deterministic risk-scoring kernel (C++/Rust), and a policy enforcement engine (FLAG, LIMIT, SUSPEND). This blueprint effectively counters large-scale identity impersonation, automated crypto scams, and coordinated reply networks while preserving platform trust and operational explainability. In alignment with principles of digital integrity and social responsibility, 100 percent of all licensing revenues generated from enterprise deployments of this framework are dedicated to the Beit Ahawah Foundation (בית אהבה) for the reconstruction of Beit Ahawah in Berlin Mitte.
Arsham Sharis· Zenodo (CERN European Organi...· 0 citations
English Abstract: Modern artificial intelligence infrastructure faces a critical scaling bottleneck: the reliance on hardware brute-force expansion to manage O(n^2) computational complexity. This whitepaper introduces the Arsham Sharis architecture as a deterministic, integrity-oriented counter-model to hardware-first scaling. Rather than masking computational inefficiency through massive GPU clusters, the proposed framework prioritizes structural reduction prior to computation. Grounded in the core maxim that "a structure is computationally integral when its information-bearing signature can be reduced without loss of structural identity," the stack integrates modular innovations including the Structural Reduction Operator (SRO) via Binomial Structural Convolution, IRIS QSV for real-time quantorial state violations monitoring, the Syntherion Trust Core (STC) paired with the Arsham Sharis Algorithm (ASA) for deterministic truth-state validation, the Navajo Root Carpet (NRC) for kernel-level signature isolation, Moving Target Integrity (MTI), and an Entropy Injector for adaptive state recovery. Operating under the economic and systemic paradigm of the Beit Ahawah Stiftung (בֵּית אַהֲבָה) and ArcCoins with Zero External Supply, this research framework replaces stochastic uncertainty with deterministic verification, paving the way for energy-efficient, architecture-independent AI systems. Deutsches Abstract: Die moderne KI-Infrastruktur steht vor einem kritischen Skalierungsengpass: der einseitigen Abhängigkeit von Hardware-Brute-Force-Expansion zur Bewältigung von O(n^2)-Rechenkomplexität. Dieses Whitepaper stellt die Arsham Sharis-Architektur als deterministisches, integritätsorientiertes Gegenmodell vor. Statt Ineffizienzen durch gigantische GPU-Cluster zu maskieren, priorisiert das Framework die strukturelle Reduktion vor der eigentlichen Berechnung. Nach der Maxime „Eine Struktur ist nur integer, wenn sie komprimiert werden kann, ohne ihre Signatur zu verlieren“ integriert der Stack Module wie den Structural Reduction Operator (SRO) mittels Binomial Structural Convolution, IRIS QSV zur Echtzeit-Zustandsüberwachung, den Syntherion Trust Core (STC) nebst Arsham Sharis Algorithm (ASA) für deterministische Inferenz, den Navajo Root Carpet (NRC) zur Kernel-Integrität sowie Moving Target Integrity (MTI) und einen Entropy Injector. Eingebettet in das System der Beit Ahawah Stiftung (בֵּית אַהֲבָה) und ArcCoins (Zero External Supply) ersetzt dieser Ansatz stochastische Unsicherheit durch deterministische Verifikation.
Arsham Sharis· Zenodo (CERN European Organi...· 0 citations
English Abstract: Modern artificial intelligence infrastructure faces a critical scaling bottleneck: the reliance on hardware brute-force expansion to manage O(n^2) computational complexity. This whitepaper introduces the Arsham Sharis architecture as a deterministic, integrity-oriented counter-model to hardware-first scaling. Rather than masking computational inefficiency through massive GPU clusters, the proposed framework prioritizes structural reduction prior to computation. Grounded in the core maxim that "a structure is computationally integral when its information-bearing signature can be reduced without loss of structural identity," the stack integrates modular innovations including the Structural Reduction Operator (SRO) via Binomial Structural Convolution, IRIS QSV for real-time quantorial state violations monitoring, the Syntherion Trust Core (STC) paired with the Arsham Sharis Algorithm (ASA) for deterministic truth-state validation, the Navajo Root Carpet (NRC) for kernel-level signature isolation, Moving Target Integrity (MTI), and an Entropy Injector for adaptive state recovery. Operating under the economic and systemic paradigm of the Beit Ahawah Stiftung (בֵּית אַהֲבָה) and ArcCoins with Zero External Supply, this research framework replaces stochastic uncertainty with deterministic verification, paving the way for energy-efficient, architecture-independent AI systems. Deutsches Abstract: Die moderne KI-Infrastruktur steht vor einem kritischen Skalierungsengpass: der einseitigen Abhängigkeit von Hardware-Brute-Force-Expansion zur Bewältigung von O(n^2)-Rechenkomplexität. Dieses Whitepaper stellt die Arsham Sharis-Architektur als deterministisches, integritätsorientiertes Gegenmodell vor. Statt Ineffizienzen durch gigantische GPU-Cluster zu maskieren, priorisiert das Framework die strukturelle Reduktion vor der eigentlichen Berechnung. Nach der Maxime „Eine Struktur ist nur integer, wenn sie komprimiert werden kann, ohne ihre Signatur zu verlieren“ integriert der Stack Module wie den Structural Reduction Operator (SRO) mittels Binomial Structural Convolution, IRIS QSV zur Echtzeit-Zustandsüberwachung, den Syntherion Trust Core (STC) nebst Arsham Sharis Algorithm (ASA) für deterministische Inferenz, den Navajo Root Carpet (NRC) zur Kernel-Integrität sowie Moving Target Integrity (MTI) und einen Entropy Injector. Eingebettet in das System der Beit Ahawah Stiftung (בֵּית אַהֲבָה) und ArcCoins (Zero External Supply) ersetzt dieser Ansatz stochastische Unsicherheit durch deterministische Verifikation.
Arsham Sharis· Zenodo (CERN European Organi...· 0 citations
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