> I started working on recommender systems in 2016 during my undergrad, specifically doing music recommendation (I was dissatisfied with the quality of Pandora/Spotify recommendations). I spent about five months in 2019 trying to make a music startup based on that.

Hi! I'm very interested in this domain, I have long been dissatisfied with the results for music recommendation across almost every platform (and the respective apps, but I digress). So frequently it seems my own personal preferences are washed away in the breadth of ML and algorithmic recommendation systems, that no matter what I begin listening on, I will invariably find myself within the mainstream for that genre/artist. It also seems to me that many algorithms can't properly deduce that I would want songs centered around a specific year, and instead seem to draw from what's "popular" in the genre regardless of the time period the song is starting from.

As an example, I can begin a GPM station based on I Gotta Feeling, a song from 2009. When I start a playlist like that, I nearly never am rewarded with a song from that time period. I tried it just now, it immediately jumped to Roar by Katy Perry, a song from 2014 with an entirely different vibe.

I supposed my question is, how meaningful are the music recommendations Findka produces?

I would love to talk more about the music startup you were pursuing, and what you accomplished there, as well as any roadblocks you may have faced. I have been whittling down an idea for a music startup myself and can't help but wonder where that road led for you.

Also your site link is broken/not resolving.