This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Dawn Chorus is a listening-walk bird bingo that runs entirely on my laptop.
The screen is the shortest part of the experience. A "Grass Ratio" card compares the minutes I spent outside with the seconds I spent on screen. It's for anyone curious about the sounds around them, including places with no signal.
Real test: I walked 30 minutes on DATE. BirdNET found 10 species, including 5 of the 12 bingo birds, and I confirmed Myna, House Crow, Rock Pigeon myself. Screen time: 2 minutes.
A short captioned walkthrough: the bingo card, airplane mode, the walk with the screen dark, then the results.
Put your phone away. Listen to the morning.
Dawn Chorus is a listening-walk bird bingo that runs entirely on your own laptop. You get a checklist of the birds likely to be near you this week, you go for a walk with your phone recording in your pocket and the screen off, and when you get back an open-source model tells you who was singing. A local language model then writes you a short field-journal page about the walk.
Built for the Hacktoberfest Open-Source AI Challenge, Week 1: "Touch Grass". The idea: the screen should be the shortest part of the experience.
The story, real walk results and demo video are in the DEV post: Dawn Chorus on DEV Two lessons shaped the design:
One caveat: Gemma is replaceable by almost any small local model. BirdNET is the part a general closed API couldn't replace offline. Its weights are also non-commercial.
I planned the project with Claude and built it with Antigravity, testing each round myself and sending back what failed. [[OPTIONAL: paste your DevRelay session link, or delete this section]]
Best Use of Gemma: Gemma 3 (4B) runs locally through Ollama and writes the field journal, fully offline, with a check that keeps its output honest.