VQV Signal
A 125M-parameter transformer model has been trained to autocomplete piano performances in real time on-device, processing about 108 notes per second on an iPhone 15. The app functions like GitHub Copilot but for MIDI piano input, continuing the music after a few played notes.
A 125M-parameter transformer model has been trained to autocomplete piano performances in real time on-device, processing about 108 notes per second on an iPhone 15. The app functions like GitHub Copilot but for MIDI piano input, continuing the music after a few played notes.
AI-assisted summary based on the listed source.
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,...
This demonstrates the potential for advanced AI models to run efficiently on mobile devices for creative tasks beyond coding, enabling real-time musical collaboration and composition without cloud dependency. It expands the scope of AI-assisted creativity directly on consumer hardware.
Hardware and robotics watchers may want to track whether this becomes a product, benchmark, or deployment signal.
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GitHub Copilot has a source-backed update with coverage spanning for developers.
125M-parameter model autocompletes piano performances on iPhone 15
125M-parameter transformer autocompletes piano on iPhone 15 in real time
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