I wrapped iOS 27's on-device AI into an offline live captioning app
Using TestFlight is a great way to help developers test beta versions of their apps.
What it does
Help developers test beta versions of their apps and App Clips using the TestFlight app. Download TestFlight on the App Store for iPhone, iPad, Mac, Apple TV, Apple Vision Pro , Watch, and iMessage. Mic Captions turns spoken audio into easy-to-read captions in real time. Use your iPhone or iPad microphone to follow conversations, lectures, meetings, tv shows, and other spoken content. Mic Captions can also translate captions, save sessions for later review, replay recorded audio alongside the transcript, and help you navigate saved content with Topics and Words. Help developers test beta versions of their apps and App Clips using the TestFlight app. Download TestFlight on the…from testflight.apple.com
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Hi there! I would like to share my side project. I work on iOS app that helps to use our devices more mindfully. There is a huge update coming and it is available now! TestFlight -> https://testflight.apple.com/join/feQ9YDI0. App use Apple's Shortcuts automation to "lock" selected apps on which you want to spend less time. You can unlock selected apps for a limited period by adding usage intention to the app. Additionally, the app has an iOS 14 Widget that reminds add intention right on the home screen, keywords daily limits, additional intention check like "captcha"(to…
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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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Life & fun · 10d ago · louisabraham.github.io
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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