papers/zoo-foundation-mission/sections/07-impact-metrics-global-reach.tex

\section{Impact Metrics \& Global Reach}


\subsection{Conservation Impact}

\begin{itemize}
    \item \textbf{Species Genomes Digitized}: 73 (47 elephants, 14 coral species, 8 amphibians, 4 primates)
    \item \textbf{Genomic Data Stored On-Chain}: 218 terabases (218 trillion base pairs)
    \item \textbf{Conservation Organizations Partnered}: 18 (WWF, WCS, Rainforest Trust, etc.)
    \item \textbf{Countries with Active Projects}: 34
    \item \textbf{Endangered Species Monitoring}: 420 species via AI-powered camera traps/bioacoustics
\end{itemize}

\subsection{Educational Impact}

\begin{itemize}
    \item \textbf{Gym Users}: 87,000+ globally
    \item \textbf{Educational Institutions}: 190+ (universities, bootcamps, research labs)
    \item \textbf{Student Projects Enabled}: 12,000+ (course projects, theses, dissertations)
    \item \textbf{Scholarships Funded}: 240 students in developing nations received compute credits
    \item \textbf{Open-Source Contributors}: 1,200+ developers improving Gym codebase
\end{itemize}

\subsection{Research Impact}

\begin{itemize}
    \item \textbf{Papers Citing Zoo Research}: 340+ (Google Scholar)
    \item \textbf{Novel Architectures Published}: 7 (HLLM, Zen-Reranker, training-free GRPO)
    \item \textbf{Open-Source Repositories}: 28 (Gym, Zoo Network node, HLLM reference)
    \item \textbf{Conference Presentations}: 45 (NeurIPS, ICLR, ICML, ACL)
    \item \textbf{Models Released}: 14 fine-tuned conservation models (genomics analysis, species identification)
\end{itemize}

\subsection{Economic Impact}

\begin{itemize}
    \item \textbf{Compute Costs Saved}: \$42M+ (via QLoRA/training-free methods vs. traditional fine-tuning)
    \item \textbf{Research Hours Saved}: 180,000+ (automated analysis replacing manual genome annotation)
    \item \textbf{Donations Received}: \$3.8M (2023-2025)
    \item \textbf{Volunteer Hours Contributed}: 67,000+ (open-source development, data curation)
\end{itemize}