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Hyperspace More Nodes Is All You Need: Nicolas Schlaepfer
Takeaway
A decentralized peer network plus a fine-tuned planning DAG model can give power users an editable agentic workflow over diverse open models.
Summary
- Hyperspace is a decentralized AI network using community-contributed personal-computer resources rather than centralized GPUs.
- Existing AIOS product (Windows/Mac, built on llama.cpp) routes inference across the peer network.
- New Hyperspace product fine-tunes a planning model that emits agentic DAGs in JSON from a user query, then renders them in a React-Flow node editor for user editing.
- Uses Qwen 2 Instruct as reasoner and Llama 3 70B as summarizer per node, with Puppeteer + Beautiful Soup for in-house web scraping to markdown.
- Pitches diverse open-source models as the answer over a single closed monolithic model, exposing core agent primitives (memory, planning, code execution, file system).
agentsdecentralizedplanning
Original description
Hyperspace is launching a new kind of agentic planning model, alongwith a breakthrough new AI application for power users. This is meant to run on the Hyperspace peer-to-peer AI network: the world’s largest and most advanced Uber-like network of open source models running on consumer devices (with over 15,000 nodes registered so far). It’s time to put a dent in the universe. Recorded live in San Francisco at the AI Engineer World's Fair. See the full schedule of talks at https://www.ai.engineer/worldsfair/2024/schedule & join us at the AI Engineer World's Fair in 2025! Get your tickets today at https://ai.engineer/2025 About Nicholas AI Software Engineer | Prompt Engineer | Passionate about AI & Team Collaboration