Meet Thoth
Personal AI Sovereignty
What it does
A local-first AI assistant built for personal AI sovereignty. 20 integrated tools, long-term memory, voice, vision, habit tracking, messaging channels — all powered by a local LLM via Ollama. Your models, your data, your rules. Governments are spending billions to keep AI infrastructure within their borders. I asked myself: why shouldn’t individuals have the same sovereignty? So I built Thoth - a local‑first AI assistant designed for personal AI independence.
Does the same job
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- Thoth - Your Private AI ScribeJun 2026 · thoth-app.com · ▲7
Private AI meeting notes for your Mac. No cloud, ever.
- PSPacific Slate: a self-hosted, model-agnostic multi-agent AI assistant28d ago · pacslate.com · ▲5
I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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