Myelin — A Decentralized Network Where Consensus Work Powers an Agentic Language Model

Abstract

Proof-of-work blockchains purchase their security through the expenditure of compute and energy — yet the work performed is itself discarded entirely. Decentralized AI networks provide useful compute but secure no ledger. Myelin unifies both functions: miners jointly operate a large agentic language model (the network model) via pipeline parallelism, and the same cryptographically attested inference work (“Proof of Inference”, PoI) determines compensation and feeds the voting weight of consensus. The native coin MYL closes the value cycle: users burn MYL for inference credits, and miners receive newly minted MYL in proportion to verified work (burn-and-mint equilibrium). We specify (i) a layered architecture that decouples consensus latency from inference latency, (ii) a three-tier verification model combining deterministic redundancy, optimistic sampling with a bisection game, and optional zkML anchors, (iii) a token economy with a quantifiable security condition (S_min = g/p²), and (iv) core data types and reference algorithms of an open-source implementation. We name the open core problems — deterministic cross-hardware inference, the latency–collusion trade-off of pod formation, and the 50% redundancy overhead — explicitly and propose measurement procedures. Bilingual release: this record contains the English and German editions of the whitepaper (PDF + Markdown each). In case of discrepancies, the German original prevails.