This is not about AI, the author is mostly just pointing out that Spotify was not designed for classical music.

This is a product issue. Spotify DJ is essentially “shuffle with some voice interludes”. There’s probably some non-AI code in there to explicitly prevent it from playing an album end to end.

Besides, AI is not one thing. It’s weird to generalise “This beta spotify feature doesn’t serve me, hence AI is useless”. For example, when the author says “if it can’t do this, how could it compose music?”, that’s a category error.

Honestly the whole post and tone are just baffling. It’s mixing up all sorts of opinions and trying to put them under one umbrella, and about 50% of the text is just name dropping specific classical pieces.

I happen to agree that the Spotify DJ feature is terrible, but I think this is a very ineffective way of presenting the argument.

Same thing I saw in AI-assisted coding. People complaining how AI- enabled some XYZ security risk, it's bad, it's crap. This could be true, but why ignore the fact that you create a full blown native Mac app, with a single sentence? That should be good for at least a few things. Right?

I listen to a lot of DJ mixes on YouTube (Hör Berlin is great, for example) and part of the appeal is what this particular DJ picks: what kind of music are they listening to in the country they’re from, how are they interpreting it, what are they mixing it with, etc. For some DJs there’s also kind of a personal visual brand, like musicians themselves.

The idea of an anonymous AI picking an optimized list of music kind of defeats the purpose.

I usually listen to dublab (los Angeles, cologne, and Barcelona) and nts1 (usually London) and nts2 (location rotates). They have 1 or 2 hour DJ sessions (live or recorded) and your hear some music that you normally wouldn't be exposed to and sometimes you hate it but usually not.

The term DJ is synonymous with modern, electronic music, anyway.

It appears that Spotify's engines use a mix of these licenses to reduce costs. Since AI isn't explicitly user-made selections, it's quite possible that the AI playlist generator is limited to a radio license model for playback, simply to save money (considering the additional cost of providing AI).

I really had to push to keep reading past this part.

But this piece doesn’t really say anything surprising anyway. Spotify isn’t for classical music. There are other services that are.

> Am I naïve in expecting Artificial Intelligence to be smart? Is my interpretation of the word “intelligence” too literal? And when an AI behaves stupidly, who’s to blame? The programmers or the AI entity itself? Is it even proper to make a distinction between the two? Or does the AI work in so mysterious a way that the programmers need no longer take responsibility?

IMO this is a programming/prompting failure - not a failure in the general capability of 'AI'.

We can prove that an AI can understand this with a basic prompt:

https://chatgpt.com/share/69b67906-0e18-8012-9123-718fc6422c...

This is a minimal base prompt, with no fine-tuning, with the same user prompt, which shows that an AI will respond correctly by default. Presumably either the AI they are using is a weak model, or their prompt is encouraging the model against this (e.g. maybe the prompt says 'return one song based on the suggestion, and then songs from similar artists after')

> I’ve heard people claim that an AI can compose music. But how can that be when it can’t even grasp basic concepts in music?

Trying to infer the underlying capability of AI to generate music based on a badly-prompted Spotify DJ feature is always going to have it's limits. The proof of 'can AI compose music' will be in the eating of the pudding. AI models have already been able to compose classical music to some extent, and can grasp music theory, so after this point it's just going to be a matter of quality/taste.

Every time someone calls an LLM "AI", their brain faults a little more.

This is the profession of marketing's greatest success: inflicting so much damage on the rest of the world.

I wish more people would ask themselves those questions.

Sadly Charles himself didn't appear to conclude that yes, it's naïve to expect AI to be "smart" (whatever that means) and yes, he and many other people get hung up on the word "intelligence" in AI, a field that's been called that since the 1950s.

I’ve been wondering if AI could be used to compose a set that rivals real DJs, but it seems like a difficult problem. First it needs to select tracks that fit well together, and stitch them together to ramp up and ramp down energy over time. Then it needs to layer the tracks, which requires an intuition for what sounds good and I’m not sure can be done algorithmically. It also needs to do engaging transitions which are appropriate for the moment - also difficult.

Classical is a harder (or at least different) problem and it's why specialist apps like Apple Music Classical exist.

But for classical music: Apple Music Classical is where it’s at, it understands the relationship between composer, work and recording.

Which I really should have anticipated since I generally dislike music radio "DJ"s too and Spotify's AI DJ is trying to be like one.

In particular it would do things like start playing tracks with no bearing on anything I'd ever listened to, like local South African music which is very far from universally preferred here. I also got the feeling it was pushing "promoted" tracks with little regard to what I would likely like, just like real life radio stations.

I also don't care to have some voice interrupting the music all the time.

I was hoping it would kind of be like their other "radio"s, but it would be more explorative to finding more "similar" tracks to what I have listened to, without seeming to get stuck in a repeating play list.

I suppose it's a cool gimmick for people who are prefer the broadcast radio experience.

Presumably a pop DJ would also mess this up. It's like going to an Indian restaurant and asking what Dim Sum they recommend.

The only reason a human would be able to do this task is that they might be trained in how to find classical music, and they have spent some time learning what is what in that world.

But a Spotify AI is of course going to be trained on the prevailing classification system only.

> The use of the word “song” for instrumental music — that is, music that is not sung and hence is not a song — is borderline illiterate.

This guy comes across as incredibly obnoxious. It's shit like this that gives classical music a bad rap as stuffy and unapproachable.

But yes, Spotify and the like are terrible for classical music. Apple Music has a separate app for this, which does a pretty good job and addresses most of these complaints.

There are apps specifically dedicated to classical music and there are many youtube channels for classical music, with sheet music[1], with visualizations[2], with videos of concerts.

Spotify and it's drop-in competitors were never good for classical music. This article is just another rant on this issue, by someone to whom classical music is so important, a pillar of western civilization, but not important enough to look for other ways to listen.

[1]: https://www.youtube.com/@AshishXiangyiKumar

[2]: https://www.youtube.com/@smalin

Perhaps file a ticket for the devs and go back to listening to the albums without AI

That being said, Spotify is probably not the best product if you listen to classical. If classical were all I listened to, I would probably still have an offline collection in a Media Monkey library as my main source of listening.

Real DJs don't follow playlists. They work within constraints — energy, tempo, crowd — and let the set emerge. Better boundaries, not more rules.

Songza was able to do this properly years ago which customized playlist based on your mood but Spotify just doesnt get it.

It shows up in all Spotify-generated playlists, so I refuse to listen to them. I assume their shitty AI recommendations are similarly filled with cancer.

I wouldn't be surprised if creating a truly great AI DJ was also hindered by this kind of legal shackles.

Doesn’t that sound ridiculous?

Since I’ve switched from Spotify to Apple Music, Apple’s recommendations are lousy and I miss discovering new artists and songs. Several of my cult favorites were Spotify suggestions I never would have found otherwise.

Are there any good recommendation engines, or people mostly just use Spotify for that?

I’d be sad if I had to switch back to Spotify but it is what it is.

Instead they're just thin veils around paid-promotion.

Why do people who hate AI think that every use of the term AI is referring to the exact same software program?

Some things just aren’t meant for shuffle and genres that haven’t been properly digitized are definitely one.

The Echo Nest was one of the most interesting music-tech companies ever built: a music intelligence platform spun out of MIT that analyzed audio, metadata, web text, artist similarity, genre structure, and playlist construction. Spotify bought them in 2014 specifically to strengthen music discovery and recommendation. At the time, Spotify said the deal would let it use The Echo Nest's "in depth musical understanding and tools for curation", and even said the Echo Nest API would remain "free and open" for developers.

https://en.wikipedia.org/wiki/The_Echo_Nest

https://news.cision.com/spotify/r/spotify-acquires-the-echo-...

If you ever used the old Echo Nest APIs, Remix SDK, demos, Music Hack Day projects, or Paul Lamere's experiments, that was a golden era. Echo Nest had open APIs for artist similarity, track analysis, playlisting, "taste profiles", ID mapping across services, and beat/segment-level music analysis. Paul Lamere's whole ecosystem of demos came out of that world: Boil the Frog, Sort Your Music, Organize Your Music, playlistminer, and later Smarter Playlists. His GitHub still points to a lot of that lineage, and his blog is still active. In fact, he posted just this month about rebuilding Smarter Playlists after ten years of use.

https://github.com/plamere

https://musicmachinery.com/

The sad part is that the open developer platform mostly did not survive the acquisition. By 2016, developers were being told that the Echo Nest API would stop issuing new keys and then stop serving requests, with migration to Spotify’s API instead. Community discussions at the time also noted that some Echo Nest capabilities, especially things like Rosetta-style cross-service mapping, were not really carried over.

https://github.com/beetbox/beets/issues/1920

That's also why Spotify's current AI DJ is so frustrating. The problem is that "AI DJ" is not the same thing as a system that deeply understands musical structure, discography semantics, performance history, or classical work/movement hierarchy. It's a recommendation + narration layer, not a true MIR-native musical intelligence system.

If you're interested in the research side of this field, the conference is ISMIR: the International Society for Music Information Retrieval, which is literally dedicated to computational tools for processing, searching, organizing, and accessing music-related data. That community is still very active. The ISMIR site describes MIR exactly in those terms, and the 2010 Utrecht conference included Paul Lamere's tutorial, "Finding A Path Through The Jukebox -- The Playlist Tutorial."

https://ismir.net/

https://news.ycombinator.com/item?id=36482468

>gffrd on June 26, 2023 | parent | context | favorite | on: Show HN: Mofi – Content-aware fill for audio to ch...

>Yes! It was "Infinite Jukebox," created by Paul Lamere ... it was awesome because it would analyse a track, then visualize its "components" and you could watch as the new "infinite" track looped back on itself and jumped from point-to-point in the original track to create an everlasting one. He created some excellent products from the Rdio API, and later Spotify ... and I believe his analysis engine ended up being the foundation upon which Spotify's _play more tracks like these_ capability is based.

>Looks like he's moved over to publish on Substack -- there's a recent(ish) post reflecting on 10 years of Infinite Jukebox:

https://musicmachinery.substack.com/p/the-infinite-jukebox-1...

>rahimnathwani on June 26, 2023 | next [–]

>However, that wasn't the end of the Infinite Jukebox. An enterprising developer: Izzy Dahanela made her own hack on top of mine. To make it work without using uploaded content, she matches up the Echo Nest / Spotify music analysis with the corresponding song on YouTube. She hosts this at eternalbox.dev. It runs just as well as it ever did, 10 years later.

>DonHopkins on June 28, 2023 | parent | context | favorite | on: Show HN: Mofi – Content-aware fill for audio to ch...

>I was working on some music retrieval stuff in 2010, so I joined the EchoNest developer program and played around with their web apis that let you upload music and download an analysis that you could use in all kinds of cool ways. They had an SDK with some great demos and example code. I discussed it with Eric Swenson and Paul Lamere, and had the chance to hang out with Paul Lamere and Ben Fields at ISMIR 2010 (the International Society for Music Information Retrieval conference) in Utrecht, where they gave a tutorial about playlisting:

https://ismir2010.ismir.net/program/tutorials/index.html#tut...

Finding a path through the Jukebox: The Playlist Tutorial:

https://musicmachinery.com/2010/08/06/finding-a-path-through...

>Tutorial 4: Finding A Path Through The Jukebox -- The Playlist Tutorial. The simple playlist, in its many forms -- from the radio show, to the album, to the mixtape has long been a part of how people discover, listen to and share music. As the world of online music grows, the playlist is once again becoming a central tool to help listeners successfully experience music. Further, the playlist is increasingly a vehicle for recommendation and discovery of new or unknown music. More and more, commercial music services such as Pandora, Last.fm, iTunes and Spotify rely on the playlist to improve the listening experience. In this tutorial we look at the state of the art in playlisting. We present a brief history of the playlist, provide an overview of the different types of playlists and take an in-depth look at the state-of-the-art in automatic playlist generation including commercial and academic systems. We explore methods of evaluating playlists and ways that MIR techniques can be used to improve playlists. Our tutorial concludes with a discussion of what the future may hold for playlists and playlist generation/construction.

>[...]

Some of the most interesting Echo Nest descendants are still around in one form or another. Paul Lamere's current/public projects include Smarter Playlists, and his GitHub still highlights SortYourMusic, OrganizeYourMusic, playlistminer, and BoilTheFrog. Glenn McDonald’s Every Noise at Once is another major descendant of that tradition: an enormous map of music genre space. Glenn's own site still describes it as an "inexorably expanding universe of music-processing experiments", and the public genre pages now explicitly say they're a long-running snapshot based on Spotify data through 2023-11-19. After Spotify's layoffs in 2023, TechCrunch reported that Glenn lost access to the internal data needed to keep Every Noise fully updated, which is why it now feels more archival than alive.

Back in 1998 when I was working on The Sims 1, I proposed in my review of the design document something I called "Moody Music": essentially a soundtrack plus a synchronized semantic/emotional control track that could affect gameplay over time. The idea was that music wouldn't just decorate the simulation; it would change it: influencing mood, motives, relationships, skills, timing, and even triggering events at specific musical moments. I wrote that up in my review of the 1998-08-07 Sims design document, along with the broader idea of letting the game recognize a player's own CDs and fetch associated "moody tracks" from the network.

Don’s review of The Sims Design Document, Draft 3 – 8/7/98:

https://donhopkins.com/home/TheSims/TheSimsDesignDocumentDra...

>I have some ideas about how the music could effect the game, that I will write up more completely later. In a nutshell, the people in the house could have a cd or record collection to choose from, each record an object that has the sound (audio wave and/or midi) and a “moody” track synchronized with the music. Playing the music also plays the moods into the environment that the people pick up on. Music can subtly effect how people react to the environment, objects, and each other. It can effect their motives and even their skills temporarily. For example, you might be able to clean the house better and faster if you put on some up tempo bouncy music. The player should be able to assume the role of disc jockey on the radio, and play from another larger library of music and commercials, that effect the peoples moods and buying habits. The TV of course is another source of mood altering temporal media, with commercials and shows that should effect different people differently. But the most important part of this idea is instead of the game effecting the music that’s played, the music effects how the game plays! The ultimate way for the user to effect the game via music, is to insert one of their own CD’s into their real computer’s CDROM drive, and the game would recognize it, and start playing it (maybe with a simple cd player interface to select the song). There could be a database associating the unique ID number of the CD with a table of contents and “moody” tracks that tell how the song effects the peoples emotions over time, with "percussion" events at dramatic moments of the music that can trigger arbitrary events in the game (like provoking a fight that was brewing, or triggering an orgasm at just the right place in the song). We hire monkeys to listen to well known CD’s, and enter time synchronized tracks with semantic meanings in Max (like note tracks, and user defined numeric tracks) or some other timeline editing tool). Put the database up on the web for instant retrieval, so when somebody sticks in a new CD, it downloads our “moody” tracks that go with it, and it starts playing and effecting their game! Streaming emotions over the net! Eventually there should be an end-user tool so people can record their own responses to music as moody tracks they can use in our games. This mechanism could be used in all kinds of games, to varying degrees of effect. I’m not saying that music should be the only way to control the game – it’s more like a subtle background effect, but there certainly could be a scenario where you try to accomplish some task (like taming a wild beast) by using only your musical taste and timing. The real bottom line benefit is that you get to listen to your OWN cd collection of music you want to hear, instead of being driven crazy by the repetitive music bundled with the game.

In hindsight it was quite adjacent to MIR, affective computing, adaptive soundtrack systems, and some of the ambitions that Echo Nest represented. That's why I was so excited about The Echo Nest in 2010 when I was working with Will Wright at the Stupid Fun Club on a music spatial organization and navigation system called MediaGraph.

MediaGraph Music Navigation with Pie Menus Prototype developed for Will Wright's Stupid Fun Club

https://www.youtube.com/watch?v=2KfeHNIXYUc

>This is a demo of a user interface research prototype that I developed for Will Wright at the Stupid Fun Club. It includes pie menus, an editable map of music interconnected with roads, and cellular automata.

>It uses one kind of nested hierarchical pie menu to build and edit another kind of geographic networked pie menu.

> [list of 20 classical artists] I’m aware that many people are unfamiliar with this musical tradition, but it forms one of the sturdiest pillars of what we casually refer to as “western civilization.”

> Unfortunately, this tradition is not much respected

> The use of the word “song” for instrumental music — that is, music that is not sung and hence is not a song — is borderline illiterate.

This writeup is insufferably pretentious. It almost reads like a caricature of someone that listens to classical.

Prompted playlists is a beta feature designed to cater to most users. They are likely using a heavily quantized model, fine tuned on common use cases.

Is it really surprising that it doesn't cater to the fringes of Spotify's user base from the get-go?

Clearly the author believes that their taste in music is the superior one, and so Spotify not designing their product experience around their tastes is "appalling."

Then you get absurd rants like this:

> I’ve heard people claim that an AI can compose music. But how can that be when it can’t even grasp basic concepts in music?

Almost like these are two completely separate models, in two completely separate products.

2. This author is truly insufferable and arrogant.

3. Apple Music Classical exists.