Mnemosyne v3: Layer-0 Deterministic Governance Protocol for Generative AI
Description
Formal technical specification of the Mnemosyne v3 protocol, introducing the KS (Knowledge Seed) Entropy Layer and Fixed6 Deterministic Arithmetic for AI IP Sovereignty.
Abstract
Generative AI systems produce content probabilistically. Enterprise applications — AAA gaming IP, global ad-tech networks, film VFX — require deterministic identity preservation. “Similar” is legally insufficient. This paper formalizes the Mnemosyne v3 Protocol: a zero-trust, fail-closed verification layer that sits downstream of any generative model and enforces cryptographically provable compliance through the Ψ (Psi) Theorem, the KS (Knowledge Seed) domain separation standard, and a three-tier governance codex. We present the complete formal specification, the economic model (“Rework-Hour Arbitrage”), and the implementation architecture across four runtimes (Rust, Python, TypeScript, JavaScript).
The Mnemosyne Thesis
We do not attempt to improve generation. We verify it. Mnemosyne operates as a Layer-0 Deterministic Governance Protocol — a cryptographic toll booth positioned between the generative model and the production pipeline. The model generates. The Gate verifies. The frame either receives a signed Evidence Pack or it does not exist.
Files
WHITEPAPER.pdf
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Additional details
Related works
- Is derived from
- Preprint: https://zenodo.org/records/18869318 (URL)
- Is supplement to
- Software: https://github.com/Mnemosyne-Protocol/Mnemosyne-Core/releases/tag/v2.0.0-gameforge (URL)
Dates
- Issued
-
2026-03-05Mnemosyne Application Layer (v2.0): Deterministic IP Fidelity for Gaming & Ad-Tech
Software
- Repository URL
- https://github.com/Mnemosyne-Protocol/Mnemosyne-Core
- Programming language
- Rust , Python , JavaScript , TypeScript
- Development Status
- Active