OnceUponaBookshelf
Personalized bedtime stories, generated on-device
What it does
OnceUponaBookshelf is an iOS app that creates personalized bedtime stories, narrated aloud by a warm professional narrator, using on-device AI that keeps your child's data private. Stories generate on-device by default, with a cloud fallback only when a device can't run the on-device model. No user accounts, no ads, no tracking. Traditional Tales and the podcast directory stay free forever; a subscription unlocks unlimited new AI-generated stories.
OnceUponaBookshelf is an iOS app that creates personalized bedtime stories, narrated aloud by a warm professional narrator, using on-device AI that keeps your child
Their name. Their age. Whatever they love this week — read together, or narrated aloud by a warm storyteller voice. "The app is a fantastic way to share stories and perfect that you are able to personalize them for your child. Highly recommend and a bedtime must have in our house!" Three things set it apart from a chatbot open at the kitchen table. Stories generate on-device using Apple's on-device models. Cloudflare Workers AI is only a fallback for older devices, and even then nothing is stored afterwards. Stories can be narrated aloud by warm, professional storyteller voices from ElevenLabs — not a robotic text-to-speech voice — then saved to your device to replay anytime. A simple,…from onceuponabookshelf.app
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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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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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