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>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 th

>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-plagiarism/499985/ https://www.theatlantic.com/science/archive/2016/09/music-pl...

wpietri 9y ago
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.
YeGoblynQueenne 9y ago
>> 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).

wpietri 9y ago

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.

YeGoblynQueenne 9y ago

>> 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).