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35+ papers documenting Hanzo AI platform evolution covering: - Crowdstart cloud-native commerce (2014 era) - Astle.js reactive SDK, Verus analytics (2015 era) - Earle genetic marketing optimization (2016 era) - Hanzo AI-first commerce platform (Techstars 2017) - Checkout, analytics ML (2018 era) - API gateway, SDK ecosystem, webhooks (2019 era) - MCP protocol, Platform PaaS (2021 era) - Agent SDK, ML framework, search, identity NFT (2022 era) - Jin multimodal AI, DSO protocol (2023 era) - Candle Rust ML, ACI decentralized compute (2024 era) - Chat, Flow, Operative, Network whitepaper, ASO, HMM, LLM gateway, Zen model family (2025 era) Papers describe historical work from 2014-2025. All compiled into this repository October 2025 - March 2026. Note: Previous git history had fabricated per-commit timestamps claiming individual commits from 2014-2025. This corrects the record — all content was committed in a single session.
18 lines
1.8 KiB
TeX
18 lines
1.8 KiB
TeX
% Decentralized Semantic Optimization (DSO) core section
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\section{Decentralized Semantic Optimization (DSO)}
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\subsection{Experience Priors}
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Each agent/node maintains an \emph{experience prior} \(E\): token/embedding-level memory distilled from rollouts. Locally, nodes run \textbf{Active Semantic Optimization (ASO)} to extract \emph{semantic advantages} from groups of rollouts (TF-GRPO). Priors are compressed (\S\ref{sec:bitdelta}) and written to the on-chain \emph{ExperienceRegistry} with Merkle proofs.
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\subsection{Training-Free GRPO as Bayesian PoE}
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For a base model with conditional \(p_\theta(y\mid x)\) and a set of experiences \(\{e_k\}\) mapping to token-level factors \(\phi_k(y\mid x)\), decoding uses a \emph{product-of-experts}:
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\begin{equation}\label{eq:poe}
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p(y\mid x,E) \propto p_\theta(y\mid x)\,\prod_{k} \phi_k(y\mid x)^{\alpha_k},\quad \alpha_k\ge 0.
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\end{equation}
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Here \(\phi_k\) are distilled from group-relative semantic advantage; weights \(\alpha_k\) are learned by introspective calibration without gradient updates to \(\theta\).
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\subsection{Distributed Aggregation}
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Hanzo Network aggregates \emph{priors, not gradients}. Let node priors be \(\{E_i\}\). We publish hashes and quality scores; the chain computes a byzantine-robust aggregate \(\tilde E = \operatorname{median}_q\{E_i\}\) under a fixed schema (token bins / embedding centroids). Conflicting contributions resolve by stake-weighted quorum plus quality caps.
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\section{ExperienceRegistry and P2P Sync}
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\textbf{Registry.} On-chain contract stores: content-addressed CID, Merkle root, schema version, quality vector, submitter, slashing bond. \textbf{Storage.} Off-chain IPFS/Arweave; local SQLite+LanceDB with Merkle verification. \textbf{Sync.} Gossip protocol with CRDT merge; priority given to high-quality shards (fee rebates bias peers to propagate them).
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