Man i love last.fm even though it's been technically superseded (for most people) by Spotify's recommendation features. It just fit so well in the zeitgeist of 2000's indie scene, microblogs, early social media.
I don't think the recommendation engines behind Spotify, Youtube Music, etc compare to the recommendations I got from last.fm over the years. The algorithmic ones seem to have a bunch of issues that bug me as a long time music listener and someone with a large music library.
- their memory is short as hell so you can listen to something for a while, stop and then it'll suggest it to you later as something to "discover"
- they are way too biased towards recently listened music and will replay things over and over if you're not actively managing your queues.
- because they're so based on what you have listened to (recently) they suggest things that are extremely obvious music no one is "discovering"
- they suggest the "top" songs from artists, albums, etc, it's very hard to get it to play a "deep cut"
- if you have a large library you'll inevitably hit playlist song limits and other things silently. Each service handles this differently, Youtube Music seemingly kicks things out of my library or liked playlists each time I add something else.
I've literally just gotten in the habit of never using the autoplay features and just starting whole albums from start to finish again because the algorithms annoy me so much. Youtube Music has been getting worse about it too where now it often ignores the music you chose to start a playlist and starts playing things you've listened to recently regardless of it doesn't match the genre/vibe at all.
Cannot call lastfm algorithm advanced in any sense. Just opened Amon Tobin page: "similar artists: Kid Koala and DJ Kush", which is an impressively shallow understanding of the last 20 (!!) years of his life, and this happened with almost every artist on the platform, because the average sum of tastes of every listener does not exist in reality. E.g. in the case of Amon Tobin, Kid Koala is the average of similarities between early albums and recent releases, which is just not true, his music cannot be averaged throughout his career. I love my Web 2.0 youth, but the average similarity algorithm doesnt deserve praise. Its not better, its nostalgia and lack of faang-style unlimited greed which confused with better quality
I'm 90% sure that music labels pay to "put their thumbs on the scales" with these recommendation algorithms in order to push their "hot" artists. I wonder how many of these problems are a result of that.
We can never know for sure if this is or isn't the case, so our only hope for stuff we can be confident isn't this way is with foss / self host able solutions
I just think it's beautiful that I can see all the music I've listened to since 2005 (back when it was still called Audioscrobbler, before the Last.fm rename). And I never stopped scrobbling in all that time!
I love these kinds of stats and being able to see how my taste has changed across more than 20 years, since I was a teenager.
I do miss the old community forums they had integrated back in the day, though.
Same. I have one or more gaps in there which I wish I could go back and correct. I feel like integration with the service is a must for any music thing I pick up, the most recent being this year, resurrecting my old iTunes library via Navidrome.
As a long-time user, I do enjoy seeing how my tastes have changed over the years and which artists and albums I play the most. I also tend to agree that the Last.fm recommendation engine was perfectly fine for my use case compared to the algo that Spotify uses now. https://www.last.fm/user/wyclif
Spotify recommendations are biased because user incentive and theirs don't align. They pay different royalties to different artists, they optimize earnings. Also, they take money to promote music and shove it down your throat.
Pretty much all the machine learning recommendation engines that emerged in the Netflix era were doomed to collapse under their own weight over time for non-mainstream users because the some limited number of mainstream modes dominate as most statistically "optimal" across the total user pool. These algorithms are best in the early days, when they're still exploring the content space for good novel fits but eventually get trapped into deep, boring grooves that work really well for tons of non-discriminating users with similar tastes.
Separately, in real commercial terms, they're all fundamentally poisoned by business model objectives of highlighting cheap content or servicing partnership/advertising deals, etc. And that problem also becomes more and more prominent as the companies running them grow and become more influential and as they need to squeeze harder and harder for revenue growth.
It was basically just a long, winding, wildly expensive road back to broadcast radio programming.
It was a good run for a while, but we're long due for a new model.
Absolutely, you're hitting the same conclusions I've reached. The algorithms are optimized for the lowest friction users that just replay the same music they like over and over again and accept whatever the popular music is. If you're a user that likes music discovery you're fighting against the system to get what you want.
The sad thing is that before Spotify bought the Echo Nest[1], they had hosted some of the coolest discovery demos for non-mainstream (in my case ambient/IDM) where you would feed it a youtube video URL and it would make a really compelling radio playlist based off it. i found so many artists i still listen to today by just sticking a video in there in the morning and coming back to the tab when something incredible popped up.
When Spotify bought TEN i considered moving my listening over, but the radio button we ended up with in Spotify and Youtube Music are huge disappointments in comparison, so corporatist and flattened to 1.5 dimensions, I always wondered how the magic was lost.
Bandcamp's feed (especially once you trick the UI in to showing you how to follow tags) is usually interesting to leave running but limited in its own way by the artist pool lacking mainstream tentpoles to jump off of.
Yep, member since May 21 2005 here, still scrobbling with Spotify. Don't think I've ever used any of the radio features on the site, really; even back in the 00s all I used were the WinAmp/Foobar plug-ins.
last.fm is one of my very favorite services. It's rough around the edges in some parts, but I've gotten incredible value from it. A couple of websites built on it that I check out from time to time:
- https://lastfmviz.netlify.app/ - shows what you've been listening to as a grid of album covers. You can scroll down as long as you want. It's cool to look back and remember where I was when listening to specific music.
- https://lastfmstats.com/ - generates tons of rankings, line charts, racing bar charts, etc. A couple I like: "Artist streaks" (I listened to Pavement tracks 122 times in a row in August 2023), "Unique artists in a single month" (225 in July 2025) and "Unique weeks per artist/album/track" (good to identify what you're always listening to vs. what you listened to heavily in a specific time)
- https://pmcdonough8133.github.io/last.timer/ - shows your listening rankings by hours, minutes instead of just scrobble count. This really should be a default feature in the site, as some artists have average track length 2-3x times of others.
The middle one is fascinating. The first track I ever scrobbled is by an artist I have yet to listen to again in 22 years. Much of the longest gaps is taken up by bands I found or started to like due to Rock Band which came out around that time. Man I miss that too, we had 30 or 40 people over right after it came out and turned the house into a karaoke dive, right down to having to kick them off the couch the next morning.
If you're a Spotify user, you can get even more precise data by downloading your listening data. The website I linked gets data from MusicBrainz and tries to fill in the gaps with an average, but even then it gets some things wrong.
E.g. Fishmans - Long Season is a 40 minute song, but the website's considers it as divided into 4-5 parts. And you don't have to listen to the full song to get a scrobble.
In the Spotify data you get the exact number of seconds you listened to it. And it is surprisingly complete and easy to use too. With LLMs I bet you can load it into pandas and construct queries for any insight you want in seconds.
Last.fm used to be special, but this was a long time ago. Just tried to login, recovered the password and seems that its just a tracker nowadays. In the past I could listen to music and drop a comment, meet new people, etc.
It still has comments on albums/songs/artists, but most of the conversations are a bit dead.
I've still been using it since it's the best service (in my opinion) for simply tracking everything you listen to. Spotify does track the same thing but they don't really let you view the information the same way. For example, there's no way to view the list of your top artists ever like there is with last.fm (I just checked mine, it's: https://www.last.fm/user/[your username]/library/artists).
Hopefully the developers being unchained from CBS/Paramount can only mean good changes are coming to last.fm in the near future.
Came here to say the same. I don't even know what this product is anymore. The website makes it sound like its about music but there is no music? I'm lost.
The last time I paid for LastFM was some time in 2009...but the home page just isn't clearly telling me what the service offers.
Originally, it kind of worked like radio; it curated music for you, you could like, comment or skip tracks. It'd reinforce the algorithm, and you'd start finding great artists. I liked the Blues catalogue a lot, even though I was listening to reggae, ska, punk, etc. It just seemed they had the best music catalogue. I remember checking how big the catalogue was, comparatively with others, which was much smaller, but much, much better!
Today, we have Generative AI, generating an incomprehensible number of songs that no one will ever listen to.
I don't remember if I had to pay for Last.fm or not back then, but I'd definitely pay to have access to that old system.
I still use last.fm via Spotify. It is wild to see my entire listening history from 11th grade to present (20 years!). Always fun to poke through and see changes from one year or life phase to the next.
one of the very first programming projects I took on was to figure out how to scrobble the records that I was playing. It was my first exposure to so many things: Ruby, FFIs, audio processing, audio fingerprinting (I think I used echo nest ?). Ended up going to local meetups to ask for advice.
last.fm is one of those services that is from the pinnacle of the open web.
There's still a ton of value in the historical recommendations on last.fm's site. What its future looks like, I'm not sure. I'd love to know who is going to operate it now that it is independent.
I'd recommend ListenBrainz for folks interested in similar tracking and some recommendations with clearer ownership.
For my own historical interests, I have a Navidrome plugin writing to my own API and surface charts across time periods by querying the postgres database it writes to.
Another alternative is listenbrainz [0], which is also self-hostable [1]. A smaller, lightweight, single user selfhostable alternative, and more about just the stats is Koito [2], and finally because obviously you want to scrobble everywhere at once, you can self-host Multi Scrobbler to scrobble to and from multiple sources at once. Yes, I like scrobbling ;)
I hope that means it will improve now. There's such a rich space of features that they could do. Had some hope with their experimental Labs but I remember being underwhelmed and not seeing anything about it recently.
I have a history going back to 2012, which is great. I've always worried Spotify would stop working with last.fm, I wonder if this makes it more or less likely.
This is very exciting. The music landscape is just as chaotic as it was back in 2007 (when CBS acquired Last.fm) if not even more complex these days. Can't wait to see what's next. <3
I really only ever used it so that a girl I liked would be able to see what I was listening to. She commented on my page. We ended up getting together for a few years. I miss my youth.
Sitting at 239,447, next to no scrobbling from 2017-2022, and I deleted my old account because of a piracy panic, so nothing before 2008. https://www.last.fm/user/YoshiSlen
I think Last.fm might have been a better friend finding and dating app than any of its contemporaries or anything that came after. Seems like everyone in this thread or anyone I know IRL has a story of making a good connection with someone via it. I know I'll always cherish the people I got to know on there.
Downside of it is like all Metabrainz projects they seem to intentionally go and make everything as utterly ugly as possible. It feels like someone there intentionally thinks up ways to make the worst UX possible.
I remember Last.fm's value proposition was 1) discovery and 2) community. (1) is (mostly, for most people) covered by "feed" algorithms of Spotify and YouTube.
I wonder how they're going to position themselves now.
As someone who used to hang out on various music forums...a human recommendation based on careful analysis of your last.fm scrobbles was infinitely more useful and accurate than anything Pandora/YouTube/Spotify/Tidal ever recommended me. Humans can infer not just what you like, but what you don't like.
Community largely died out already by 2012. Originally Last.fm enabled a lot of IRL socializing, connecting hipsters who lived in the same town and listened to the same music. Changes in music-listening habits, the atomization of tastes in a world where so much was available, and CBS not having a clue what to do with the site -- that killed Last.fm except for just a way to track one's own plays.
Last.fm & in particular audioscrobbling has been such an amazing joy to have in the world. Music is so important to me, and it's amazing having this system to help see over time what friends and I myself enjoy.
These days, for auduiscrobbling, I recommend folks use either teal.fm (which alas is somewhat DIY or find-a-friend for their API service) or rocksky.app. There's a better credible exit, as it's based on atproto/Bluesky protocols, and a richer world of apps & interconnectivitiws emerging.
"The company has generated an operating loss for the year to 31 December 2024 of £690,252 (2023: profit of £1,509,544) and revenue of £2,215,381 (2023: £1,960,340). As at 31 December 2024, net liabilities were £45,506,488 (2023: £44,855,202)."
"The financial statements have been prepared on a going concern basis on the grounds that Paramount Global has confirmed that it will continue to provide financial and other support to Last. FM Limited at least for the next twelve months and thereafter for the foreseeable future to enable Last.FM Limited to continue to meet all its liabilities as they fall due."
I wonder what their financing plan is, and what shape this independence will take, whether Paramount is retaining a minority ownership take? Seems like they might just be able to scrape break even based on current revenue.
Anyone else music listening habits change in the past six months to listening to one owns AI Slop? My slop (been a real hobby songwriter of melodies & lyrics since a kid..decades ago) has the most meaning to me it’s just not me singing. Now it sounds pro and some ppl when I’m playing it actually like it vs. my own rough demos (guitar, vocal and added drums/bass via GarageBand). I actually don’t care if others hear my slop as it’s all my own ideas…words and melodies which have way more meaning then Listening to another’s music/songs.
- their memory is short as hell so you can listen to something for a while, stop and then it'll suggest it to you later as something to "discover"
- they are way too biased towards recently listened music and will replay things over and over if you're not actively managing your queues.
- because they're so based on what you have listened to (recently) they suggest things that are extremely obvious music no one is "discovering"
- they suggest the "top" songs from artists, albums, etc, it's very hard to get it to play a "deep cut"
- if you have a large library you'll inevitably hit playlist song limits and other things silently. Each service handles this differently, Youtube Music seemingly kicks things out of my library or liked playlists each time I add something else.
I've literally just gotten in the habit of never using the autoplay features and just starting whole albums from start to finish again because the algorithms annoy me so much. Youtube Music has been getting worse about it too where now it often ignores the music you chose to start a playlist and starts playing things you've listened to recently regardless of it doesn't match the genre/vibe at all.
I love these kinds of stats and being able to see how my taste has changed across more than 20 years, since I was a teenager.
I do miss the old community forums they had integrated back in the day, though.
I posted asking if anyone wanted to go with me since I didn't want to go alone, and she sent me a message.
Good times.
Pretty much all the machine learning recommendation engines that emerged in the Netflix era were doomed to collapse under their own weight over time for non-mainstream users because the some limited number of mainstream modes dominate as most statistically "optimal" across the total user pool. These algorithms are best in the early days, when they're still exploring the content space for good novel fits but eventually get trapped into deep, boring grooves that work really well for tons of non-discriminating users with similar tastes.
Separately, in real commercial terms, they're all fundamentally poisoned by business model objectives of highlighting cheap content or servicing partnership/advertising deals, etc. And that problem also becomes more and more prominent as the companies running them grow and become more influential and as they need to squeeze harder and harder for revenue growth.
It was basically just a long, winding, wildly expensive road back to broadcast radio programming.
It was a good run for a while, but we're long due for a new model.
When Spotify bought TEN i considered moving my listening over, but the radio button we ended up with in Spotify and Youtube Music are huge disappointments in comparison, so corporatist and flattened to 1.5 dimensions, I always wondered how the magic was lost.
Bandcamp's feed (especially once you trick the UI in to showing you how to follow tags) is usually interesting to leave running but limited in its own way by the artist pool lacking mainstream tentpoles to jump off of.
[1]: https://en.wikipedia.org/wiki/The_Echo_Nest
- https://lastfmviz.netlify.app/ - shows what you've been listening to as a grid of album covers. You can scroll down as long as you want. It's cool to look back and remember where I was when listening to specific music.
- https://lastfmstats.com/ - generates tons of rankings, line charts, racing bar charts, etc. A couple I like: "Artist streaks" (I listened to Pavement tracks 122 times in a row in August 2023), "Unique artists in a single month" (225 in July 2025) and "Unique weeks per artist/album/track" (good to identify what you're always listening to vs. what you listened to heavily in a specific time)
- https://pmcdonough8133.github.io/last.timer/ - shows your listening rankings by hours, minutes instead of just scrobble count. This really should be a default feature in the site, as some artists have average track length 2-3x times of others.
If you use Spotify, another site I've had loads of fun with is https://explorify.link/.
I've wanted to build something like this for a long time, cool (and unsurprising, really) to see it's already done!
Swans is my number 30 by scrobbles but 4 by playtime, which makes total sense.
E.g. Fishmans - Long Season is a 40 minute song, but the website's considers it as divided into 4-5 parts. And you don't have to listen to the full song to get a scrobble.
In the Spotify data you get the exact number of seconds you listened to it. And it is surprisingly complete and easy to use too. With LLMs I bet you can load it into pandas and construct queries for any insight you want in seconds.
I've still been using it since it's the best service (in my opinion) for simply tracking everything you listen to. Spotify does track the same thing but they don't really let you view the information the same way. For example, there's no way to view the list of your top artists ever like there is with last.fm (I just checked mine, it's: https://www.last.fm/user/[your username]/library/artists).
Hopefully the developers being unchained from CBS/Paramount can only mean good changes are coming to last.fm in the near future.
https://github.com/Yooooomi/your_spotify
The last time I paid for LastFM was some time in 2009...but the home page just isn't clearly telling me what the service offers.
Today, we have Generative AI, generating an incomprehensible number of songs that no one will ever listen to.
I don't remember if I had to pay for Last.fm or not back then, but I'd definitely pay to have access to that old system.
CBS Coporation (owned by Paramount) bought last.fm in 2007
Just declaring themselves independent without details doesn't provide much context. I feel like Michael Scott just declared bankruptcy.
last.fm is one of those services that is from the pinnacle of the open web.
I'd recommend ListenBrainz for folks interested in similar tracking and some recommendations with clearer ownership.
For my own historical interests, I have a Navidrome plugin writing to my own API and surface charts across time periods by querying the postgres database it writes to.
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edit: maybe they saw my message or fixed a bug? signup now works everywhere for me.
Huge opportunity to allow folk to own their own (meta)data. /fingerscrossed
[0]: https://listenbrainz.org/
[1]: https://github.com/metabrainz/listenbrainz-server
[2]: https://github.com/gabehf/Koito/
[3]: https://github.com/FoxxMD/multi-scrobbler/
I really only ever used it so that a girl I liked would be able to see what I was listening to. She commented on my page. We ended up getting together for a few years. I miss my youth.
I wonder how they're going to position themselves now.
These days, for auduiscrobbling, I recommend folks use either teal.fm (which alas is somewhat DIY or find-a-friend for their API service) or rocksky.app. There's a better credible exit, as it's based on atproto/Bluesky protocols, and a richer world of apps & interconnectivitiws emerging.
"The financial statements have been prepared on a going concern basis on the grounds that Paramount Global has confirmed that it will continue to provide financial and other support to Last. FM Limited at least for the next twelve months and thereafter for the foreseeable future to enable Last.FM Limited to continue to meet all its liabilities as they fall due."
I wonder what their financing plan is, and what shape this independence will take, whether Paramount is retaining a minority ownership take? Seems like they might just be able to scrape break even based on current revenue.
Your request was blocked To protect our website, our security firewall has flagged this request as potentially unsafe.
Please try clearing your cookies and refreshing the page. If the problem persists, try again later or on a different computer network.
Error 406
:)
I think this is fantastic change and wish them the best, this is probably just a small hickup I experienced and I wil try again later.
BTW, I recently cancelled my youtube premium, it was just too expensive. Never was subscribed to Spotify, so I need different ways to listen to music.
I’ve been telling close friend about this and then I see this verge article saying in not the only one https://www.theverge.com/ai-artificial-intelligence/937059/n...