Man i love last.fm even though it's been technically superseded (for most people) by Spotify's recommendation features.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.
That's because the recommendation engine that Last.fm used back in the day was made the incredibly expensive way: the entire corpus was hand-tagged and cross-linked by humans atop an enormous CDDB. Last.fm, Audioscrobbler, and MusicBrainz (the association engine) were all linked together.
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
Edit: of course spotify-style recommendations are much much worse, I just mean that lastfm doesnt have good algorithm either because artists are not consistent in releases. What is an average between electronic cult classic "The last resort" and every other Trentemoller album in strict indie rock style? This average does not exist
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
The other frustration I’ve noticed is that they key in very heavily on artist and specific “genre” designation as what feeds the recommendation, which is actually quite bad for anyone who likes experimental work.
I understand that if your recommendations are based on “people who like this also tend to like that” then you’re right in the strike zone. But that approach is basically agnostic to any property of the music itself. Suppose there’s a rock band that released a specific song where they’re experimenting with a new style that has an atypically (for them) funky/jazzy influence. If I say I want more songs like that I mean songs that fuse rock/jazz/funk, not more songs that fans of [rock band] are into.
I still think for new music discovery Pandora’s approach remains the best if you really curate a station for yourself. Apple Music has been good for creating very listenable playlists though, and their new AI playlist generator has been very fun. Surprisingly, YouTube also seems to have some secret sauce where they recommend a lot of interesting stuff that I’ve genuinely never encountered before. I suspect this is because there’s a lot more amateur and experimental artists on there doing weirder stuff and it’s able to find audiences for those in ways that the music-focused services have less visibility into since their catalog is so focused on stuff from the recording industry.
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.
I second this. I started as an Audioscrobbler user before the Last.fm merger. I have tracked nearly every track I've listened to for 21 years. It's awesome seeing how my habits have changed over the years.
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
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.
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.
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.
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.
> over time for non-mainstream users because the some limited number of mainstream modes dominate as most statistically "optimal" across the total user pool
This isn’t true, YouTube recommendations when it chooses music are amazing (no idea if YouTube Music is good I mean the video site).
Spotify recs are intentionally recommending you things cheap to stream or that have been paid for. It’s not a raw rec engine and it’s not bad cos it’s collapsing under normies, YouTube is proof of that.
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.
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.
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'm mostly unfamiliar with the current offering of last.fm, but the name is familiar from way back. Glad to see something well-liked reclaim some independence.
At a glance, they're providing an interface to YT sourced content with some value adds around tracking or categorizing listening.
A quick question for users: can the site itself be configured as a listener without streaming / displaying the video? In general, YT has a lot of music, but the perf hit of streaming typically high-quality video as well is a blocker when doing dev work on my main machine.
I love Last.fm, I've been scrobbling for over 20 years now.
It's amazing to me that they have managed to stick around like they have. They're very much an "old internet" site, and I hope they can stick around for many many more years.
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.
Me too. I tried loggin in, and after a forced password reset I am back, though back to 2018 it turns out.
On Spotify I made a playlist with over 4,000 songs from Last FM. I remember doing it but I couldn't say how I did it now. And also a "loved" playlist which I am revisiting now. First track Whitest Boy Alive: Golden Cage, a stonker.
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.
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.
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
So lastfm become relevant again because slop will not appear statistically in user scrobblings because of vast amount of "musicians" required to be profitable: if I listen to 1000 AI artists with one track produced and Linkin Park then my average will be Linkin Park
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.
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.
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.
That's because the recommendation engine that Last.fm used back in the day was made the incredibly expensive way: the entire corpus was hand-tagged and cross-linked by humans atop an enormous CDDB. Last.fm, Audioscrobbler, and MusicBrainz (the association engine) were all linked together.
I switched to Apple Music to save some money and I find the curation and the recommendations to be significantly better than Spotify.
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
Edit: of course spotify-style recommendations are much much worse, I just mean that lastfm doesnt have good algorithm either because artists are not consistent in releases. What is an average between electronic cult classic "The last resort" and every other Trentemoller album in strict indie rock style? This average does not exist
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
Using the historical record that they absolutely did this, there is no reason to give them the benefit of the doubt that they are not now doing this.
The other frustration I’ve noticed is that they key in very heavily on artist and specific “genre” designation as what feeds the recommendation, which is actually quite bad for anyone who likes experimental work.
I understand that if your recommendations are based on “people who like this also tend to like that” then you’re right in the strike zone. But that approach is basically agnostic to any property of the music itself. Suppose there’s a rock band that released a specific song where they’re experimenting with a new style that has an atypically (for them) funky/jazzy influence. If I say I want more songs like that I mean songs that fuse rock/jazz/funk, not more songs that fans of [rock band] are into.
I still think for new music discovery Pandora’s approach remains the best if you really curate a station for yourself. Apple Music has been good for creating very listenable playlists though, and their new AI playlist generator has been very fun. Surprisingly, YouTube also seems to have some secret sauce where they recommend a lot of interesting stuff that I’ve genuinely never encountered before. I suspect this is because there’s a lot more amateur and experimental artists on there doing weirder stuff and it’s able to find audiences for those in ways that the music-focused services have less visibility into since their catalog is so focused on stuff from the recording industry.
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.
I second this. I started as an Audioscrobbler user before the Last.fm merger. I have tracked nearly every track I've listened to for 21 years. It's awesome seeing how my habits have changed over the years.
I just remembered that I met one of my best friends to this day through Last.fm. It was 2009 or so, and you could leave messages on concert pages.
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.
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
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.
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.
I use it with Spotify to track my listens and sort by artist, album and the like. It definitely still has value, even for Spotify users!
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.
I've felt a serious reduction in quality of recommendations from spotify the past couple years. Maybe I'll try last.fm
More than a feeling.
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.
> over time for non-mainstream users because the some limited number of mainstream modes dominate as most statistically "optimal" across the total user pool
This isn’t true, YouTube recommendations when it chooses music are amazing (no idea if YouTube Music is good I mean the video site).
Spotify recs are intentionally recommending you things cheap to stream or that have been paid for. It’s not a raw rec engine and it’s not bad cos it’s collapsing under normies, YouTube is proof of that.
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.
[1]: https://en.wikipedia.org/wiki/The_Echo_Nest
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.
I would argue it’s still unparalleled for recommendations
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.
If you use Spotify, another site I've had loads of fun with is https://explorify.link/.
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.
> shows your listening rankings by hours, minutes instead of just scrobble count
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.
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.
Nice tip, but I use YouTube Music. I just downloaded my listening history, looks like they don't include listening duration, alas.
a while ago I created this one, for when you want to listen to a familiar album, but can't decide which one: https://what-to-listen.chef-labs.deno.net/
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 was special way before playback was introduced. The tracking is the reason I've been using it for 22 (!) years.
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.
You can install your spotify and pull in all the data from Spotify.
https://github.com/Yooooomi/your_spotify
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.
the previous owner doesnt appear to be mentioned in the post (or, at least, not easily found).
CBS Coporation (owned by Paramount) bought last.fm in 2007
So what exactly happened, did management buy the company from them?
Thanks. My first thought was "independent from what?". I'm a last.fm user since 2006 but never noticed any ownership changes.
I'm mostly unfamiliar with the current offering of last.fm, but the name is familiar from way back. Glad to see something well-liked reclaim some independence.
At a glance, they're providing an interface to YT sourced content with some value adds around tracking or categorizing listening.
A quick question for users: can the site itself be configured as a listener without streaming / displaying the video? In general, YT has a lot of music, but the perf hit of streaming typically high-quality video as well is a blocker when doing dev work on my main machine.
I love Last.fm, I've been scrobbling for over 20 years now.
It's amazing to me that they have managed to stick around like they have. They're very much an "old internet" site, and I hope they can stick around for many many more years.
So CBS spun them back out as their own corp or did the employee's or someone else buy it from CBS?
Just declaring themselves independent without details doesn't provide much context. I feel like Michael Scott just declared bankruptcy.
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.
I've moved over to ListenBrainz, it's quite nice and I like that the data is open and not trying to be monitized
Looking forward to scrobbling again
Back in the day, was heavily influenced by last.fm for this BBC 6music GWAP mooso.fm
https://www.bbc.co.uk/blogs/radiolabs/2009/12/mooso.shtml
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.
Great news! Related[0]. The presentation video in the linked article from 2002 is a gem.
0: https://news.ycombinator.com/item?id=46266875
This seems like a positive step. It never made sense (to me at least) for CBS Paramount to own it.
Huge opportunity to allow folk to own their own (meta)data. /fingerscrossed
Unfortunately, unable to create an account on my laptop (WiFi) or phone (Verizon) - even in incognito.
> 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
edit: maybe they saw my message or fixed a bug? signup now works everywhere for me.
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 ;)
[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 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 recommend installing a browser add-on like https://addons.mozilla.org/en-US/firefox/addon/web-scrobbler...
I don't know if I even have an account anymore, its been like 15 years since I last logged in...
Me too. I tried loggin in, and after a forced password reset I am back, though back to 2018 it turns out.
On Spotify I made a playlist with over 4,000 songs from Last FM. I remember doing it but I couldn't say how I did it now. And also a "loved" playlist which I am revisiting now. First track Whitest Boy Alive: Golden Cage, a stonker.
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.
Listenbrainz has been an excellent alternative for me.
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 don’t see how LB has a worse UX than LFM.
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 fear that what's next is AI slop music, pushed by record companies so that no performers or songwriters need to be paid.
So lastfm become relevant again because slop will not appear statistically in user scrobblings because of vast amount of "musicians" required to be profitable: if I listen to 1000 AI artists with one track produced and Linkin Park then my average will be Linkin Park
What a blast from the past. It was a pretty cool time to be a teenager in 04-06 with last.fm, MySpace, iPods, Limewire and music blogs.
Interesting! Hope they have a super lean team, and just focus on the niche, legacy web experience.
115,000 scrobbles: https://www.last.fm/user/whalesalad
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 miss the internet of old, where you would meet up with a cute girl you met online and she turned out to be a 39 year old man from Wisconsin.
Hey, we had some good times together you and me.
same tbh
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.
Music taste is probably the all time best indicator of compatibility tbh. You can go to shows together. You can jam out in the car together.
Some previous discussions on this note:
Last.fm and Audioscrobbler Herald the Social Web: 2002
https://news.ycombinator.com/item?id=46266875
Last.fm turns 20
https://news.ycombinator.com/item?id=33722862
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.
To me, it always was the scrobbler. I've been tracking what I listen to for 15+ years.
a recommendation algorithm that isn't a box of pain they sell to advertisers?
I honestly forgot last.fm was a thing. But good for them that they have independence now.
This is awesome! Anyone know who the humans behind the new company are?
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.
They have a lot of users paying to track their listening habits; I'm surprised.
And I try to "Start Now"
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:)
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.
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.
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...