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Comment by ryacko | Hacker News Reader

Soon even artists will be unemployed.

Just the opposite, I think. The promise of computers has always been to take over boring work so that humans can focus on the more interesting bits. Artists will always have something to do.

Entirely plausible hypothetical: what happens if Deepmind train a massive neural network on the entire Spotify catalog, weighted for Billboard chart position and Grammy nominations? What if that algorithm turns out to be as good at songwriting as AlphaGo is at the game of Go? Will anyone listen to human-written songs if AlphaSong starts producing superhumanly beautiful music? Will any of us listen to the same music if AlphaSong can analyse our personal playlists and produce an infinite number of songs that perfectly match our musical tastes?

In practical terms, the problem with learning songwriting, vs learning Go, is that the number of board positions in Go is finite whereas the number of songs that can be written is infinite.

With Go, then, the task of an AI player (like AlphaGo) is to search a finite space for those board states that allow it to win.

With songwriting- the task is not even clearly defined. Obviously, you're trying to generate songs people will want to listen to, so you have to search an infinite space for a set of songs that satisfy some criteria of "listenability", but what criteria are these? Popular songs range over wildly different music styles, from Black Metal to Medieval folk revivalist music through RnB and Arabic belly dancing music. What examples will we train our AI songwriter on? All music, ever? Specific kinds of music? Specific songs as exemplars of specific styles?

Or in other words, what exactly will our AI songwriter be trying to learn? It'd be looking into an infinite haystack filled with almost identical needles for a particular needle it's never even seen well enough to recognise.

>In practical terms, the problem with learning songwriting, vs learning Go, is that the number of board positions in Go is finite whereas the number of songs that can be written is infinite.

There are about 10^170 legal positions in Go. We think that there are about 10^82 particles in the observable universe. The space isn't infinitely large, but it's close enough.

The space of enjoyable songs is remarkably small. There are only 12 notes in the chromatic scale and 8 in the diatonic scale. The human range of hearing only covers about nine octaves. There are a relatively small pool of rhythms and harmonies that sound pleasing to most people. Accidental plagiarism is a very common problem in popular music - it's easy to unintentionally write a song that's almost identical to another song. The most common defence in music plagiarism cases is simply to find lots of prior art; the song that you've allegedly plagiarised is probably extremely similar to a lot of other songs.

Jazz musicians can improvise over unfamiliar chord progressions precisely because most music isn't particularly original. If you understand music theory, you can make fairly accurate guesses about what's coming next. Practically all music follows a similar set of understandable patterns, even across cultures.

https://www.theatlantic.com/science/archive/2016/09/music-pl...

>> There are about 10^170 legal positions in Go. We think that there are about 10^82 particles in the observable universe. The space isn't infinitely large, but it's close enough.

I don't understand why the number of atoms in the universe has anything to do with the tractability of Go, or anything else. I've heard of this idea before, but, for example, my computer can calculate the factorial of 106, that is 1.146281e+170 (1.146281 times 10 to the power of 170), in much less than a second. 10^170 means nothing on its own. And like I say, the point with Go AI is to try and not have to examine all possible board positions.

The other thing to keep in mind is that finite is always infinitely smaller than infinite- no matter how large it (finite) is. And infinite is always intractable, so if a problem is infinite you can't solve it, unless you can reduce it to a finite problem.

As to music- the number of combinations you're looking at is far larger than the number of permutations of the set of notes. A musical piece is actually a string from a language with the musical notes for symbols and some unknown set of rules that govern what is a well-formed string in the language (i.e. what is a musical piece and what is just noise). That language is probably context-free, or above- and certainly not finite. So, no, you can't hope to just machine-learn how to make a song just by training on a few examples.

These sort of infinite problems crop up all the time in human activities. It's no use trying to approach them without a full understanding of the tractability issue. I mean, that's why we have complexity theory in the first place- because some problems can't be solved in a general manner in the available time in the universe (and again that time has nothing to do with the atoms in the same universe).

I think you've made the mistake here of reducing music down to its tune. If you were right, people would be just as happy with a knock-off cover of a song as with the original. In fact, they'd be just as happy with a cheap MIDI version. That's demonstrably not the case.

I get where you're going with this, and think it's a great question. But I don't think it's as plausible as you do.

It's possible that a massive musical AI/idiot savant could eventually produce an infinite amount of pleasant background music sans lyrics. But for music people are actually listening to, I don't think we're anywhere close.

But even if you're right, it won't matter. When Prince and David Bowie died, people weren't primarily upset because there would be no new songs in a particular style. It was because they'd formed a deep emotional connection to the artist. To the artist's personality as expressed both through their music and through their presence in the world. As another example, hip hop and Latin music are valuable to me not just for the sounds, but for the window into cultures that I didn't grow up in. I don't just enjoy the tune.

What you're really talking about is not just AlphaSong, but something close to solving the Strong AI problem so well that you can create totally believable synthetic characters. At best you situate a synthetic mind in a real culture, which I think would end up like Vanilla Ice: extractive and disconnected from the tradition. Or do you make a bunch of synthetic minds generate their own synthetic culture? It would be interesting, but I'm not sure it would displace much.

Even if you're entirely right, though, that AlphaGo produced superhumanly good synthetic music, I suspect it won't matter much. Long ago the technology of photography produced superhumanly good synthetic image reproductions. Human art mostly turned away from strict representation, and human artists seized on photography and turned it into an art form in its own right. Synthetic instruments allow anybody to simulate a arbitrary number musicians, but people still go to the orchestra and still see live bands. We could eat take-out or go only to restaurants, but people still have dinner parties and enjoy cooking together. People are social animals.

> superhumanly beautiful music

The problem with your hypothetical lies in these three words: there's no such thing.

Art and appreciation of it is, in big part, a way to connect with the mind and feelings of other people, the artist and everyone else who appreciates the art. Most (not to say all) people wouldn't even consider buying a piece of art that wasn't made by another person, methinks.

Most of the records you hear on the radio are physically impossible. The timing is tighter than any human drummer is capable of, the intonation is more precise than any human singer. Every performance has been endlessly massaged using advanced DSP tools; a lot of what you hear is entirely synthetic, with no basis in real musical performance. We're so inured to these superhuman recordings that we've come to expect them.

You might need less artists or be able to create more games with the same number.

I would think it's actually engineering job that is more at risk. Artists and animators will visually create these games and AI will figure out the code.

One thing that bugged me about the 2009 Star Trek film was why Checkov runs over to take manual control of the teleporter to beam up Kirk as he’s freefalling towards the planet: surely a a machine at their level of technological sophistication would be able to calculate the trajectory and beam them up in real time without too much trouble.

For sure:

"The new, modified version, Creative Adversarial Networks (CAN), is designed to generate work that does not fit the known artistic styles, thus “maximizing deviation from established styles and minimizing deviation from art distribution,” according to the paper. For the training, they used 81,449 paintings by 1,119 artists in the publicly available WikiArt data set."

https://news.artnet.com/art-world/rutgers-artificial-intelli...

As I understand it, this would allow you to create a level of a game like Super Mario Brothers as usually and then it could use that to generate additional levels that work in the same way with the same set of rules.

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