Bestday Launch
Predict cravings. Break bad habits before they start.
What it does
Bestday is a predictive habit-change app that helps you understand craving and trigger patterns using sleep, mood, stress, energy and daily check-ins so you can get ahead of difficult moments.
Bestday app is a predictive habit-change app that helps you understand craving and trigger patterns using sleep, mood, stress, energy and daily check-ins so you can get ahead of difficult moments.
Bestday predicts your cravings before they hit. Armed with data about your sleep, mood, stress, and energy, you'll never be caught off guard again. 5 Daily Signals Tracked Every Day. See Patterns Others Miss. Ditch the willpower struggle. We help you swap old routines for better ones until a healthier lifestyle just feels like second nature. Our proprietary algorithm analyzes your biometrics and daily patterns to predict a craving before it hits, giving you a critical head start. Automatically map your emotional states and social habits to moments of risk, transforming vague patterns into clear, actionable insights. Perfectly timed, personalized notifications with proven coping strategies,…from bestdayapp.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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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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