Magenta Real-Time Music Generation Locally on iPhone, Without the GPU
Last Thursday, Deepmind released Magenta Realtime 2 , an open source music generation model. They said it could run on Mac, but not iPhone. As a v̵i̵b̵e̵ ̵c̵o̵d̵i̵n̵g̵ ̵a̵d̵d̵i̵c̵t̵ agentic AI maxxi and person who has melted iPhones before (link at bottom), I took that as a personal challenge and made it my weekend project. On Saturday, I got it to run for 10min straight on an iPhone 12 Pro from 2020 without melting the phone or - shockingly - touching the GPU. How? I chopped the model up into 5 pieces and set them each to run on different parts of Apple's system on a chip (SoC). My past…
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In the maker’s words, at launch
Last Thursday, Deepmind released Magenta Realtime 2 , an open source music generation model. They said it could run on Mac, but not iPhone. As a v̵i̵b̵e̵ ̵c̵o̵d̵i̵n̵g̵ ̵a̵d̵d̵i̵c̵t̵ agentic AI maxxi and person who has melted iPhones before (link at bottom), I took that as a personal challenge and made it my weekend project. On Saturday, I got it to run for 10min straight on an iPhone 12 Pro from 2020 without melting the phone or - shockingly - touching the GPU. How? I chopped the model up into 5 pieces and set them each to run on different parts of Apple's system on a chip (SoC). My past experience taught me that if you can actually leverage it, the iPhone's NPU is incredibly powerful, and power efficient. If you're doing sustained real-time generation for long periods of time on a device without a fan, you gotta use the neural engine or else you will melt the device. See: https://accelerateordie.com/p/we-melted-iphones-for-science The Apple Neural Engine has a ton of constraints, the main one being that it only accepts fixed shape inputs, and only supports some architectures -- which is why I chopped the model up into pieces. But it works! And I wrote zero lines of code by hand. Back when I was running VC-backed companies, I would have needed a small team of grumpy greybeard engineers to do this and it would have taken 2-6 weeks. Now I can feed my own nerd fetish and do this stuff myself. Next up: I'm building an iPhone app that ties into your heart rate, movement data, location etc to generate a real-time soundtrack to you life. What a time to be alive! update: Demo video of it running on my iPhone 15 Pro: https://x.com/mattmireles/status/2064849702156415214?s=46
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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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