PlugClaw – Private AI agent hardware for any phone or PC
PlugClaw is a thumb-sized private AI computer. Plug it into any device to instantly deploy a secure AI workforce that operates apps, runs workflows, and automates tasks end-to-end - while keeping your data isolated under your control.
What it does
PlugClaw Thumb-sized AI Computer That Gets Things Done Turns any phone, tablet or computer into an AI workstation. Actually Does Things Plug-and-Play Private by Design Buy now Buy now What You Really Need Is an AI That Gets Things Done AI is amazing, until you ask it to actually do something. Too much friction . Getting an AI to actually do work requires too much setup The privacy tax . Handing your important data to AI feels risky Chatbots can't act . AI generates text, but it doesn't press buttons or send emails for you. PlugClaw is built to fix all three. Hunting for APIs, writing scripts, worrying about permission. It's a part‑time job. Cloud models are powerful but risky; local models…from plugos.net
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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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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
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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