Building a P2P 'Wikipedia for Machines': Verifiable RAG with the Holepunch Stack
The article discusses the development of HIVE, a decentralized knowledge base designed for LLMs. It aims to provide cryptographic proof of content origin, addressing issues with current centralized search APIs. HIVE operates using a peer-to-peer architecture, splitting tasks between lightweight producer nodes and heavy consumer nodes for efficient data extraction and indexing.
- ▪HIVE is a peer-to-peer knowledge base intended for use by language models, offering cryptographic verification of content sources.
- ▪The system consists of two types of nodes: BEEs, which autonomously extract knowledge, and Queens, which index and query the data.
- ▪Current limitations include dependency on local hardware for extraction rates and potential issues with network connectivity behind corporate firewalls.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3945764) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Enrique Gordoncillo Posted on May 22 Building a P2P 'Wikipedia for Machines': Verifiable RAG with the Holepunch Stack #opensource #ai #node #p2p Current LLMs hallucinate when they lack context. While Retrieval-Augmented Generation (RAG) helps, existing pipelines force a tough compromise: you either trust centralized search APIs, scrape the live web (which is slow, fragile, and bloated with SEO spam), or maintain heavy, complex crawling infrastructure yourself.
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