Song Zero
The family tree behind every song.
What it does
Every song is the child of what came before it & the parent of what came after — but that lineage is invisible on streaming services that give infinite tracks & zero context. Song Zero starts with a single track & outputs a shareable package: - Spotify playlist. - Interactive family tree. - Researched blurbs. How it works: - Pick a song. - Research pipeline maps lineage. - Claims are fact-checked. - Shareable output. Who it's for: Curious audiophiles, music geeks, fans.
Trace the cultural lineage of any song. AI-researched, fact-checked, curator-reviewed musical genealogies with interactive visualization and Spotify playlist.
Every song is the end of a long line of influence. Song Zero is the liner notes for the streaming age — read the story behind a track, trace the roots that fed it, then discover the bands flying in the same orbit. // modern liner notes. cultural lineage. fact-checked. curator-reviewed. liam.mcmanus1945 traced the lineage of The Freezing Moon (Live in Leipzig) . racquel.wright29 traced the lineage of Everybody wants to rule the world . beerspitnight traced the lineage of Freaking Out the Neighborhood . thomasfrancis01 traced the lineage of Inner City Blues (Make Me Wanna Holler) . beerspitnight traced the lineage of Hope I Never Lose My Walletfrom song-zero.app
Does the same job
all alternatives →More ai this month
the category →
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.
AI · 16d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com


Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


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.
AI · 16d ago · simedw.com