Mnexium AI
Persistent, structured memory for AI Agents
What it does
🧠 𝐌𝐧𝐞𝐱𝐢𝐮𝐦 = persistent memory for LLM apps. Add one 𝐦𝐧𝐱 object and get chat history, semantic recall, and user profiles that follow users across sessions and providers. 🔄 Works with 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 and 𝐂𝐥𝐚𝐮𝐝𝐞 — same memories, any model. Switch mid-conversation without losing context. ⚙️ No vector DBs or pipelines. A/B test, fail over, and route by cost — your memory layer stays consistent.
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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! I wanted to share something I built over the last few weeks: isometric.nyc is a massive isometric pixel art map of NYC, built with nano banana and coding agents. I didn't write a single line of code. Of course no-code doesn't mean no-engineering. This project took a lot more manual labor than I'd hoped! I wrote a deep dive on the workflow and some thoughts about the future of AI coding and creativity: http://cannoneyed.com/projects/isometric-nyc
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