Discy - AI Life Tracker
Build better habits, achieve goals with AI
What it does
Discy is an AI-powered life tracker designed for continuous self-improvement. Track habits, goals, focus and personal progress in one place, with photo proof, smart reminders, finance tracking, notes and an AI coach. Available on iOS, Android, Windows and the web.
Build consistent habits with photo proof, goals and OKRs, smart reminders, finance tracking, notes and an AI coach. Available on iOS, Android, Windows and web.
Discy is your connected discipline system for habit streaks with photo proof, goals and OKRs, projects, money, notes and AI coaching. Habits, goals, projects, money, notes and reflection — connected in one system and supported by AI. Check in daily, keep your streaks alive, and attach photo evidence — so past-you cannot lie to future-you. Category-aware reminder times and per-habit schedules that survive reboots — delivered when they help. Real Key Results and Key Actions with deadline alerts and progress charts — not just another to-do list. Bring OKRs, habits, notes and tasks into one project hub with kanban, timeline and gallery views. Track spending across wallets, tag the emotion…from discyhabit.com
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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, August 2026
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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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