Nexvion Copilot
The AI screen guide that never needs a tutorial.
What it does
Nexvion Copilot is a zero-shot visual AI guide built as a lightweight Chrome extension. Instead of switching tabs to read outdated documentation or scrub through videos. Our smart Ghost Cursor visually highlights exactly where to click next across any web dashboard in real time—with strict single-tab privacy.
The live AI screen guide that never needs a pre-made tutorial. DoraHacks 2.0 MVP Launch.
Real-time visual assistance and a smart Ghost Cursor guide over any web app. Get up and running with your zero-shot AI screen guide in under 30 seconds. Click download above to get your Nexvion-Copilot.zip package, then unzip it to a folder. Go to Chrome and paste chrome://extensions/ in your search bar. Enable Developer mode . Click "Load unpacked" in the top left corner, select your extracted folder, and your copilot is ready! Watch Nexvion Copilot guide you through unfamiliar software, pointing and instructing in real time without ever taking control of your mouse. We are validating this MVP for the DoraHacks 2.0 hackathon. Drop your feedback, feature requests, or email if you want to…from nexvion-copilot.vercel.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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