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Bylines, paper authorship, correspondence addresses and the founder blurb under each post named an individual. They name the organisation that published the work instead: the brand on posts and pages, the research byline on papers, and research@ in place of a personal address. Both are what these repositories already used elsewhere — nothing new was coined. Co-authors are untouched. Where a paper named someone else alongside, they stay named; only the one byline changed. Bibliography entries, running heads, PDF metadata and affiliations move with it, so a citation still resolves to whoever the cited paper names. Sample and fixture data uses the placeholder name these tests already use elsewhere, so no assertion changed meaning.
51 lines
2.5 KiB
TeX
51 lines
2.5 KiB
TeX
\documentclass[11pt,twocolumn]{article}
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\usepackage{../shared/hanzocover}
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\usepackage[utf8]{inputenc}
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\usepackage{amsmath,amssymb,amsfonts}
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\usepackage{graphicx}
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\usepackage{hyperref}
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\usepackage{algorithm}
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\usepackage{algorithmic}
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\usepackage{listings}
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\input{../shared/lstlang}
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\usepackage{xcolor}
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\usepackage{cite}
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\title{\textbf{Hanzo Network: A Decentralized AI Compute Platform with Post-Quantum Security and Physics-Inspired LLM Routing}}
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\author{
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Antje Worring, Hanzo AI Research\thanks{Corresponding author: [email protected]} \\
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\textit{Hanzo Industries \quad Lux Industries \quad Zoo Labs Foundation} \\
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\texttt{[email protected]}
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}
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\date{Version: v2025.09 \\ September 2025}
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\begin{document}
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\hanzocoverpage
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\begin{abstract}
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We present Hanzo Network, a decentralized compute platform that integrates blockchain consensus, confidential computing, and advanced AI inference routing into a unified architecture. The system introduces four core innovations: (1) \textbf{HLLM (Hamiltonian Hidden-Markov LLM)}, a physics-inspired routing framework that combines regime detection with Hamiltonian dynamics for optimal model selection; (2) \textbf{Post-Quantum Cryptography (PQC)} integration with NIST FIPS 203/204 compliance and five-tier privacy model supporting GPU TEE-I/O; (3) \textbf{Unified Runtime Abstraction} enabling seamless orchestration across Docker, Kubernetes, WASM, and Firecracker runtimes; and (4) \textbf{Compute DEX (Decentralized Exchange)} with on-chain resource accounting and AI token mining. Benchmarks demonstrate 9M+ blocks/second consensus throughput with sub-100$\mu$s PQC operations. The system supports 20+ LLM providers, native Qwen3 embeddings with 4096 dimensions, and blockchain-integrated compute metering. This architecture enables practical decentralized AI infrastructure with quantum-safe security guarantees.
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\end{abstract}
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\input{sections/01-introduction}
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\input{sections/02-system-architecture}
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\input{sections/03-hllm-physics-inspired-llm-routing}
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\input{sections/04-post-quantum-cryptography}
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\input{sections/05-unified-runtime-abstraction}
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\input{sections/06-consensus-and-state-management}
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\input{sections/07-ai-inference-integration}
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\input{sections/08-unix-style-api}
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\input{sections/09-security-analysis}
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\input{sections/10-performance-evaluation}
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\input{sections/11-related-work}
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\input{sections/12-discussion}
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\input{sections/13-conclusion}
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\input{sections/15-version-history}
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\input{sections/16-api-reference}
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\input{sections/17-configuration-reference}
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\input{sections/99-acknowledgments}
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\end{document}
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