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all alternatives →- TAThe App I Built to Help Manage My Diabetes2024 · apps.apple.com · ▲185
Hi HN, I’m Joshua, a student, and I’m excited (and a little nervous) to share something deeply personal that I’ve been working on: Islet, my diabetes management app powered by GPT-4o-mini. It’s now on the App Store, but I want to be upfront—it’s still very much in its early stages, with a lot more to go. I was diagnosed with Type 1 diabetes while rowing competitively, and that moment changed everything. It wasn’t just the practical challenges of managing insulin, carb counts, and blood sugars; it fundamentally shifted how I see myself and the world. It forced me to slow down, prioritise my…
- MYManage your blood glucose via SMS2018 · ▲5
Hello HN! I'm building a service that lets users log their blood glucose via SMS and share that data with loved ones. I'd love some feedback. Site: https://glucolog.herokuapp.com/ Features: -Simply text readings to (909) 757-0084 and get feedback. No app required -Users and followers receive daily progress updates -Followers receive reminders if a user hasn't been logging -Simple charts to visualize progress -Data sharing with a user's endocrinologist and/or physician Background: My father has Type 2 diabetes and it has been a struggle helping him manage it. He tried…
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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
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New Google Calendar▲1,045Google is launching a new look + new features for Calendar
Work · 2017 · support.google.com
