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50 lines
1.9 KiB
TeX
50 lines
1.9 KiB
TeX
\section{Comparison with Centralized Platforms}
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\begin{center}
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\small
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\begin{tabular}{lp{3cm}p{3cm}}
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\toprule
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\textbf{Aspect} & \textbf{Centralized (OpenAI/Anthropic)} & \textbf{Zoo Network} \\
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\midrule
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\textbf{Ownership} & Corporate & Community (DAO) \\
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\textbf{Transparency} & Proprietary black box & Fully auditable via Arweave \\
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\textbf{Governance} & Internal decisions & Token-based voting \\
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\textbf{Fine-tuning Cost} & \$10,000+ per task & \$18 per task (Training-Free GRPO) \\
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\textbf{Data Privacy} & Centralized logs & Federated + ZK proofs \\
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\textbf{Vendor Lock-in} & High (API dependencies) & None (self-hostable) \\
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\textbf{Censorship Resistance} & Single point of failure & Decentralized nodes \\
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\textbf{Interpretability} & None (weight updates) & Human-readable experiences \\
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\textbf{Composability} & Limited (API only) & Full (open experiences) \\
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\textbf{Economic Model} & Subscription & Contribution-based rewards \\
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\bottomrule
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\end{tabular}
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\end{center}
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\subsection{Performance Comparison}
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\begin{center}
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\begin{tabular}{lrrr}
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\toprule
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\textbf{Method} & \textbf{AIME24 (\%)} & \textbf{AIME25 (\%)} & \textbf{Cost (USD)} \\
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\midrule
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GPT-4 Turbo (OpenAI) & 74.3 & 68.1 & \$10 per 1M tokens \\
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Claude 3.5 Sonnet & 78.9 & 71.2 & \$15 per 1M tokens \\
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Fine-tuned Qwen3-32B & 80.0 & 67.9 & \$10,000 setup \\
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\textbf{Zoo (Training-Free GRPO)} & \textbf{82.7} & \textbf{73.3} & \textbf{\$18 setup + \$0.02/query} \\
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\bottomrule
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\end{tabular}
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\end{center}
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Zoo achieves state-of-the-art performance at 99.8\% cost reduction.
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\subsection{Decentralization Metrics}
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\begin{itemize}
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\item \textbf{Node Count}: Target $\geq 100$ GPU nodes across 20+ geographic regions.
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\item \textbf{Token Distribution}: No single entity holds $> 5\%$ of KEEPER.
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\item \textbf{Governance Participation}: Target $\geq 30\%$ turnout on major proposals.
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\item \textbf{Nakamoto Coefficient}: Minimum number of nodes to control 51\% of compute. Target $\geq 20$.
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\end{itemize}
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