Louis Rouffaud
Glenn McDonald, the mastermind behind Every Noise at Once, is a pioneer disguised in strange titles. He’s a visionary who is rewriting the rules of music.
McDonald looks at music, and the larger ecosystem around it, differently. Not only does he envision new ways for us to understand and interact with music, he goes one step further and turns these ideas into reality.
Spotify Wrapped? That was him. Another one of his creations — Every Noise at Once.
What is Every Noise at Once?
Put simply, ENAO is a scatterplot of music data. From genres to artists, it’s a simple yet striking format showcasing the unbelievable amount of music we have today.
Only the combination of a Harvard educated data guru and the largest streaming platform on earth could lead to its development. All the world’s genres are there before you. A click away from dark minimal techno to bluegrass fiddle, this is the type of website which gets music nerds like us excited.
Pulled from the about section, ENAO is described as, “A long-running attempt at an algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 6,291 genre-shaped distinctions at Spotify.”
A mouthful for sure. As I’m looking through this universe of genres I’m wondering how is it all mapped?
The format of the scatterplot is as such: the farther down you go is more organic, up is more mechanical or electric. Left is denser and more atmospheric, right is spikier and bouncier.
Mastermind behind Every Noise at Once, Glenn McDonald
Glenn McDonald worked at Spotify for 10 years between 2014 and 2024 as a Data Alchemist. A job title which I’ve never heard of, and which makes me wonder if Glenn is some type of wizard.
Long before Spotify he had a love for music. As McDonald’s technical abilities grew, his curiosities around music have led to many websites, patents, and companies.
During my conversation with Glenn, I couldn’t help but notice a higher degree of intention from him. More of a visionary in the way he sees the world of music. Never thinking that things can’t improve and progress forward.
Why you should check it out
It’s no secret that Spotify has been using AI more and more. Often using machine learning models to help give users recommendations. AI alternatives have come with push back as users notice less new music being recommended and more repetitiveness overall. Glenn gives us his perspective,
“Much of what happens at Spotify is driven by metrics like retention and listening time. Especially over short-term tests, familiarity is the best predictor of listening time.
Yet over longer periods of time, it’s not necessarily true.
I think that’s what a lot of people experience is that these are songs I already like. Today that’s great. And tomorrow that’s good. A week from now, if that’s all that you’re playing I start to wonder —
where’s the new stuff?”
Spotify seems to be falling into the pivotal trap of our time, short-term thinking at the expense all things we hold dear. Though the platform is still an unmatched directory of music, your music search could get turbo charged with Every Noise at Once. It’s waiting to launch you to galaxies of undiscovered bangers.
How to use Every Noise at Once
Glenn advises the best way to use ENAO is by finding an artist you like while wandering through the website. From the artist you’ll be able to find associated artists and genres where you can follow certain sound elements which you enjoy.
As you continue down the rabbit hole, you’ll be able to “triangulate” the genres which incorporate these elements which speak to you.
When I ask McDonald about his favorite lesser-known function of the website, he mentions the opposite genre space.
“Keep scrolling down where it shows the artists in that genre and there’s a white on black version, which is the opposite side of the genre space. It’s like a hyperspace tunnel through the genre space to somewhere fresh and new.”
Feeling too lazy to go down the rabbit hole? Let the website command your music discovery for you. Just click scan at the top and it’ll sample genres while shuffling through the scatterplot.
How I use the visualization
With this, I’ve been finding the more rudimentary Ctrl+F (or Command+F for Mac users) useful. Using a specific keyword within a genre to find others like it. In my case, I’m using garage or liquid while looking for subgrenes of drum and bass.
Coming to the dnb region on the scatterplot, I find some familiar names like the rage-infused Raggatek and the more laid-back underground Amapiano.
As a particular fan of liquid dnb and UK garage, I’m curious to see what other genres I can find around these spectrums of sound. I stumble on liquid funk and press the name to get a sample. Digging further, clicking on the two arrows next to the genre brings me to the dedicated liquid funk page.
Seeing some familiar names on my rotation like Hybrid Minds and Pola & Bryson means I’m right on track. Using scan from the top menu, I get samples from randomly chosen artists and selecting any from playlist, intro, pulse or edge brings me to a Spotify playlist.
Some proper discoveries
In my research for more silky liquid dnb sounds, I‘m pleasantly surprised. Finding similar genres the likes of deep liquid and deep soul house. As for UKG, old school bassline, UKG revival, and modern jungle are all promising.
This really is the music lover’s dream. For the rest of the website, I’ll let you discover from here. Enjoy.
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The universe of the underground is thriving. Find your music niche in the Underground Sound Music section. Happy listening.
