https://news.ycombinator.com/item?id=37159338
Reception wasn't great to say the least.
[0] https://www.theverge.com/2014/5/7/5690590/spotify-removes-si...
I was ranting, immaturely, to my ML educated friend recently about how terrible modern discovery algorithms are ("if ML is so powerful why does Spotify exclusively serve up the steamiest of dog sh$t?") when he explained this to me.
His response was "they aren't optimizing their discovery algorithms for your enjoyment, they optimize them for profit."
Is this actually true? I don't know. I don't think consumer file hosting services would be viable at their present price points if they were storing every single file byte-for-byte.
Certainly some of the value capture belongs to the company, but if you're not particularly concerned about security it seems like a win-win.
If you are concerned about security, encrypt your files and everyone else with deduplicated files will subsidize the cost of your service.
It's likely referring to iTunes Match which is a paid service that allowed you to upload your own MP3 files to Apple who would then serve it to you alongside any purchased/streamed music.
I believe that by default (but able to be disabled) your songs would be "upgraded" to the master-quality equivalent in Apple Music if they were identical. But then over time artists have been replacing those song with different versions/mixes.
Every distributed object store I've ever seen takes your data, chunks it into a fixed size, hashes it and then distributes copies on multiple nodes.
So deduplication is intrinsic to the architecture and not some business decision layered on top.
Apple pays the same rate to everyone and for all music, and for what it's worth it is well known that Apple pays much more than Spotify does to artists.
It is incredibly difficult to guess what related music people will like, and some people will like the selections, others won't. Apple recently added a "Discovery" station that tries to guess music you might like but don't listen to and I am a big fan of it, while many others absolutely hate it. Eh.
Has popular sentiment turned against Spotify’s algorithms? I thought their recommendation system was their most-respected feature – in my own experience at least, Discover Weekly continues to be Spotify’s moat.
That's more than can be said for Tidal. My recommendation playlists generally contain tracks and artists I already listen to (sometimes from completely unrelated genres), sprinkled with what seems to be random tracks from the "more like this" section of said artists.
Still not enough to compensate for the shit stream quality and ever increasing price of Spotify though...
What drives me absolutely bonkers is the number of foreign language songs in Spotify's recommendation engine for me. No matter how many times I say "never play this song again" to every foreign language song, give it about 5-10 more songs and it'll play another one.
I've never knowingly listened to a foreign language song
Still in 2016, I could start with a song in genre X and then let Spotify autoplay for hours staying in genre X. I discovered some new bands I liked. Then circa 2017 or 2018 something changed. After a couple of songs, Spotify would switch to genre Y, and break my flow.
I stopped paying for Spotify, and switched to Youtube, then Youtube Music. Youtube Music still does the good old thing, plays random songs staying within the genre I started with.
Maybe Spotify is optimizing for profit, but my money they lost.
So in practice it is not very user friendly since you can't pause it.
But this behavior should be controllable by the user.
I don't think "private mode" in applications is a good alternative most of the time to more direct controls like:
- An opt-in mode for training the algorithm.
- An ability to after leaving a phone on overnight to clear a bunch of songs out of your recommendations.
- An ability to mark a song that you like as irrelevant without blocking it.
- An ability to import and export recommendation lists and then to "pause" or "freeze" your recommendation training.
- An ability to freeze/fork/revert your recommendation profile.
- The ability to have multiple recommendation profiles.
- etc...
Going into a special mode to preemptively avoid a program from acting unpredictably and doing unpredictable things is bad UX, we should just call it bad UX. One of the big reasons that bad UX exists is because companies aren't using recommendation algorithms to benefit the user, and so they don't want users to be in control of them or to be able to easily turn them off or tune them. The recommendation engines are there to push Spotify's interests even when those interests don't align with the user. Bad UX and bad recommendation controls are in some ways a feature for the company, not a bug.
If the recommendation engine was presented in a way that consumers could easily control and if the majority of even casual users felt confident interacting with it and regularly turned it off, then that would be treated as a software defect to be fixed. Modern recommendation UX has more in common with advertisements or the popups websites put in front of content to force you to make an account, in the sense that you're not really supposed to take advantage of any opt-outs that the companies begrudgingly supply.
Perhaps only until they get the market position they desire...
all under the disguise of 'objective and smart algorithm analysing data' even though it seems that they will always use data to fit their own need, it feels like a digital feudal system
it surely does.
and quite an interesting take on the declaration of independence of cyberspace.
They couldn't even have gotten to the point of confusing white noise and leaves rustling with podcasts and other "content" to make a buck off, if it wasn't for that first step. And that view of users as a resource, as people who need to be told what they want, permeates so much of tech... like a giant elephant shitting all over an otherwise quite elegantly made couch.