『Signal Notes』のカバーアート

Signal Notes

Signal Notes

著者： Nick Creighton
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Dispatches from a 13-site AI empire — what actually works in production, what fails, and what nobody tells you about building with AI.(c) 2026 Aevorn LLC 経済学
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  • Local Rag With Ollama Tutorial

    Local Rag With Ollama Tutorial
    2026/06/22
    The hype around local AI often crashes into the reality of ten-gigabyte downloads and cooling fans spinning like jet engines. It’s a promise of privacy that feels violently out of reach. In this episode, we bypass the academic noise and hardware meltdowns. We are deploying an offline Retrieval-Augmented Generation system that breathes life into your documents without sending a single byte to the cloud. No API keys. No monthly invoices. Just a clean, efficient stack running on a standard laptop. It is the sound of productivity, reclaimed from the chaos of complex tutorials. Get the written walkthrough at [Link] Listen to build your local archive.
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    13 分
  • Ai Agent Frameworks Eval 2024

    Ai Agent Frameworks Eval 2024
    2026/06/22
    The carnival rides are shutting down. The demos are over. Building AI agents in 2024 on nothing more than a loop and a prayer isn't just risky—it's a structural failure waiting to happen. We’ve seen the infinite loops. We’ve burned the API credits. We’ve watched hallucinations compound into total system collapse. This is the shift from hype to reliability. We strip away the magic to look at the frameworks that actually keep production systems running when things get weird. It’s time to stop hoping your prompt works and start building a house that stands. Read the companion blog post. Press play and let’s ship.
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    15 分
  • Fine-Tune Llama 3 706B Model Locally

    Fine-Tune Llama 3 706B Model Locally
    2026/06/15
    The hum of a server. The click of a terminal. Forget the API; this is about running the colossal Llama 3 model yourself. A 706B parameter AI, in-house, offline. Host Nick Creighton maps the frontier of true data privacy, where your internal documents and codebases never leave your control. This is the blueprint for building a private AI data center, covering the hardware reality check and the parallel power of fine-tuning and RAG. Ready to ship it? Listen here. Read the companion post: [Link to blog post]
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    17 分
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