mirror of
https://github.com/hanzoai/papers.git
synced 2026-10-29 07:34:31 +00:00
zeekay
0d1d121451
Fix shared/ include paths to ../shared/ for 55 subdirectory papers so
that hanzocover.sty and lstlang.tex resolve when building from each
paper's own directory (the build pattern used by latexmk per paper).
Build fixes:
- hanzo-operative/sections/03-screen-understanding-pipeline.tex: move
\COMMENT from after \FOR{...} onto the \STATE line so the algorithmic
env doesn't mis-parse.
- hanzo-network-architecture (abstract + sections 04, 12, 13): escape
unicode mu (U+03BC) as $\mu$ for pdflatex.
- ntt-transform/sections/08-benchmark-results.tex: same mu escape.
All 55 Tier-2/3 papers now build clean with latexmk -pdf.
73 lines
2.7 KiB
TeX
73 lines
2.7 KiB
TeX
% Hanzo Tokenomics: Token Economics for AI Infrastructure at Scale
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\documentclass[11pt]{article}
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\usepackage{../shared/hanzocover}
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\usepackage{amsmath, amssymb, amsthm}
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\usepackage{mathtools}
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\usepackage{bm}
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\usepackage{graphicx}
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\usepackage{booktabs}
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\usepackage{hyperref}
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\usepackage{enumitem}
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\usepackage{xcolor}
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\usepackage{float}
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\usepackage{multirow}
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\usepackage{tikz}
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\usepackage{pgfplots}
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\pgfplotsset{compat=1.18}
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\hypersetup{colorlinks=true,linkcolor=black,citecolor=blue,urlcolor=blue}
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\newtheorem{definition}{Definition}
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\title{HANZO TOKENOMICS\\[0.3em]
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{\large Token Economics for\\AI Infrastructure at Scale}}
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\author{
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Zach Kelling \\
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\textit{Hanzo Industries Inc (Techstars '17)} \\
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\texttt{[email protected]}
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}
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\date{March 2026}
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\begin{document}
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\hanzocoverpage
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% ============================================================================
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% ABSTRACT
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% ============================================================================
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\begin{abstract}
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We present the token economics of the \textbf{HANZO} token, the native asset of
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Hanzo Network---an AI Chain Infrastructure (ACI) Layer-1 purpose-built for
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decentralized AI compute markets, model serving, and semantic learning. HANZO
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serves four functions: (i) payment for AI compute (inference, training,
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fine-tuning) across the platform, (ii) staking collateral for inference node
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operators, (iii) governance over model selection, infrastructure upgrades, and
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treasury allocation, and (iv) fee reduction and revenue sharing for long-term
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holders. We detail the token distribution (1 billion fixed supply), vesting
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schedules, utility mechanisms, deflationary dynamics (25\% fee burn), and the
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economic model that aligns infrastructure providers, model developers, application
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builders, and end users. Production data from 14 months of Hanzo Platform
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operation (2,800+ applications, 47M inference requests) informs the demand model.
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We prove that the burn-and-stake equilibrium converges to a stable token velocity
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under mild assumptions on compute demand growth, and compare the HANZO model to
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competing AI token designs (FET, RNDR, TAO, AKT).
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\end{abstract}
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% ============================================================================
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\input{sections/01-introduction}
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\input{sections/02-hanzo-platform-overview}
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\input{sections/03-hanzo-token}
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\input{sections/04-token-distribution}
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\input{sections/05-utility-mechanisms}
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\input{sections/06-revenue-model}
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\input{sections/07-vesting-schedule}
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\input{sections/08-inflation-and-deflation}
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\input{sections/09-token-governance}
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\input{sections/10-zen-model-economics}
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\input{sections/11-defense-enterprise}
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\input{sections/12-comparison-to-other-ai-tokens}
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\input{sections/99-conclusion}
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\end{document}
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