The Bones of PearlOS
Quickly sharing this overview. To get an OS nervous system rather than a typical AI web stack, we made the architectural choice to have voice, interface, and system state as independent services coordinating through a shared mesh - giving us the "bones" of PearlOS.
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- PAPearlOS –An open source OS companion that learns and evolves around youFeb 2026 · github.com · ▲6

- WSWhat should the GUI for AI agents look like?Jul 2026 · marbleos.com · ▲139
Hi HN! We’re Akilan and Miguel, the creators of MarbleOS. The inspiration for Marble comes from the GUI work at Xerox PARC, the 1984 Macintosh, and later NeXTSTEP, which became the foundation for Mac OS X. Before GUIs, interacting with a computer was limited to strange terminal commands: C:\> DIR C:\> COPY FILE.TXT A: You had to remember the command, syntax, paths, and parameters. The GUI made those capabilities visible. Instead of remembering commands, you could point at files, drag them, click buttons, and select actions from menus. It didn't necessarily make entirely new things possible;…

OzBrain, a shared brain for knowledge between agents and your team15d ago · ozbrain.com · ▲93I think agent-first chat interfaces will be a primary software modality and busy dashboard/UI will go away. I’m not sure who exactly wins it, but I want my knowledge to grow/go with me. A lot of the “knowledge” ie research, analysis, reasoning will be done by agents as the primary user. Our current notes tools & tasks management systems were built for humans… I don’t care what the 17th thing on my bug backlog is. I want to conduct agents that can execute for me and do great work. What I built OzBrain to do: + Create a central place for agent reasoned knowledge to live + Be agnostic…
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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…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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