That's like saying we've had abakuses since forever therefore these computers will never be revolutionary. Quantitative change by orders of magnitude is qualitative change.

Imagine a world where you ask your smartphone to make you a death metal song about fishing and feminism in Australia and to use Freddy Mercury voice and jazz harmonies and it does that on the fly and generates something objectively good.

Wouldn't that be revolutionary for music? Because it's entirely possible in the next decade. Probable even.

To be honest, that doesn't sound _that_ revolutionary for music. Because I'm pretty sure if you went digging, you could already find somewhere on Spotify a pretty decent death metal song with a vocalist who sounds like Freddy Mercury and jazz harmonies (I will concede, the specified subject matter is unlikely). Would you go looking for that, though? Probably not, because musical tastes and interests aren't about wanting a very specific set of attributes in a song. It's about tribalism, cults of personality, senses of belonging, nostalgia etc. The world is not short of good music, or variation in styles of good music, and what causes songs to be popular is not the objective quality of the music.

Put it another way. If an AI could generate new Beatles music on the fly, making it sound exactly like the Beatles, with the same creativity of lyrics, tight harmonies, beautiful melodies, would Beatles fans go out in their millions to buy them? No. In the same way that the same dusty demos from the 60s found in an attic somewhere became valuable when it was discovered that they were Beatles demos. The music didn't change, it didn't get better or worse. The personal story attached to them was what mattered.

My point isn't that any particular generated song will be revolutionary. My point is that you can get any song you can describe. There will be billions of good quality songs made because billions of people will be able to produce a song just by describing it.

I expect new genres to be created almost immediately. And I'm not sure how real musicians can compete with that level of noise out there.

This only works if the sound and themes desired are vast enough for that. It's fine if a casual listener is a fan of something like anything house, pop, or electro. It's more difficult if your taste level is more obscure- a specific artist's style, or a specific juxtaposition produced from a one-off album. In that case there is quite literally not enough data to train on to produce further.

Even when there's not enough data to train on, it might still be possible to generate something in a desired rare style - provided this style is a mixture of several more common styles. Modern generative models are pretty good at interpolating.

That sounds more like a meme than something which would revolutionize music. It would be a funny gag, but what really determines if its good music or not is... if its good music or not. If my phone idea of "generate a death metal song" is to parrot what every other death metal song sounds like, it will be boring and not enjoyable to listen to.

The border between "parroting" and "generating something good" may be very hard to discern at some point.

> Generative music has been around for half a century,

If you start by referring to results from 50 years ago, have you tried listening to state of the art generative music systems lately? They can probably compose music better than 99% of humans.

But we mostly listen to music written by humans who are better at writing music than 99.9999% of humans.

Yes. And there was a time when we literally used paintings to assess progress in a mine. Cars didn't outperform horse carriages for certainly 10, arguably 30 years after their invention.

This "human music" > "ai music" will flip. Suddenly. And it will never flip back.

> This "human music" > "ai music" will flip. Suddenly. And it will never flip back.

Already starting to happen with ai lyrics I use for inspiration in creating EDM music ( i.e. https://TheseLyricsDoNotExist.com/ )

This shares the same foundation as the argument that ebooks will kill physical sales and solent will change how people see food, namely that we're all purely motivated by boiling every need we have down to the most fundamental version.

It never seems to play out that way at population scales

Have you been moved by any of that music though? Am I missing something?

Listen to some samples:

- https://openai.com/blog/jukebox/ (2020, quite good, but no classical music)

- https://openai.com/blog/musenet/ (2019 so not as good as the 2020 one, but showcases classical music)

There is no reason to assume that one cannot be moved by AI-generated music, as the AI has learnt from human-generated music and tries to mimick the styles.

While it's technically impressive and has a decent surface-level resemblance, none of the samples had any sense of direction or substance.

I can see this kind of tech taking over stuff like stock music that's automatically added to consumer holiday videos or played on the phone while you wait for a customer service agent.

That said, I'd expect the agent to be an AI long before generated music becomes independently musically relevant.

Yeah, it's very moving to see a human-made machine do such wonders. Fills me with awe, appreciation, and hope.

That's exactly it, though. This stuff is interesting because of the novelty of AI. The works themselves are not independently relevant (not yet, at least).

Elsewhere someone replied that art is interesting in a large part because of the personal story. How is this differemt?

99% of the time, I don't listen to music for the personal story of the artists involved. In fact, a lot of the music I listen to is made by artists that I know very little about.

Yes - the older music is better, because it was an exploration of nondeterminism in art, and not automated replication.

Doing what has already been done is rarely compelling.

Is there anything you'd recommend for SOTA music gen?

Here are some links:

[1] https://magenta.tensorflow.org/music-transformer

[2] https://storage.googleapis.com/magentadata/papers/music-tran...