11–20 of 49 posts
Try expressing feelings and stop using that word that has absolutely nothing to do with machine learning.
The very very very basic Idea of machine learning is at opposite with art.
These things have nothing to do together.
Re: the latest Performance RNN, discussing their "best sounding" output. > Note that this isn’t a performance of an existing piece; the model is also choosing the notes to play, “composing” a performance directly. The performances generated by the model lack the overall coherence that one might expect from a piano composition; in musical jargon, it might sound like the model is “noodling”— playing without a long-term…
I really don't understand the point of this. Do we need a computer to help us add to the vast store of music nobody ever listens to? Reminds me of Douglas Adams's electric monks
Part of me agrees, but at the same time computers can explore spaces far faster than we can. Perhaps it will end up like Go where an AI exploring music will lead to new inspiration for humans.
Art is not putting up data until it brings up something "cool". It's the expression of mind. Miyazaki has a clear expression about the subject https://www.youtube.com/watch?v=BfxlgHBaxEU and I'm really deeply sadden that people doesn't get this before hand. Try expressing feelings and stop using that word that has absolutely nothing to do with machine learning. The very very very basic Idea of machine learning is at…
Re: the latest Performance RNN, discussing their "best sounding" output. > Note that this isn’t a performance of an existing piece; the model is also choosing the notes to play, “composing” a performance directly. The performances generated by the model lack the overall coherence that one might expect from a piano composition; in musical jargon, it might sound like the model is “noodling”— playing without a long-term…
Re: the latest Performance RNN, discussing their "best sounding" output. > Note that this isn’t a performance of an existing piece; the model is also choosing the notes to play, “composing” a performance directly. The performances generated by the model lack the overall coherence that one might expect from a piano composition; in musical jargon, it might sound like the model is “noodling”— playing without a long-term…
My take (as someone working in the area) on how/why we are encouraged by this progress: The model is unconditional i.e. any concept of form at all was learned directly from data, with no real structural hints to what it should learn. Generally you get much stronger "global structure" the more prior information you provide either in the model itself or in the input/targets (such as chord constraints, etc.). This is on…
Art is not putting up data until it brings up something "cool". It's the expression of mind. Miyazaki has a clear expression about the subject https://www.youtube.com/watch?v=BfxlgHBaxEU and I'm really deeply sadden that people doesn't get this before hand. Try expressing feelings and stop using that word that has absolutely nothing to do with machine learning. The very very very basic Idea of machine learning is at…
We think of these models as being ways to extend artistic expression... like guitar pedal or cameras or drum machines. Perhaps ML will give rise to something new and aesthetically interesting in this direction.
If you really want to build a tool used by producers then it would be required to be a VST in the first place.
But then I really doubt (as an amateur composer) than any artist could get anywhere with this.
How can I transmit my feelings trough a bunch of data i've no control over ?
I really don't understand the point of this. Do we need a computer to help us add to the vast store of music nobody ever listens to? Reminds me of Douglas Adams's electric monks
IMO, the end game of this sort of thing would be to, one day, have an app that can generate endless new music just for you, based on your taste.
I really don't understand the point of this. Do we need a computer to help us add to the vast store of music nobody ever listens to? Reminds me of Douglas Adams's electric monks
I think the non-research value will be like the value of chess computers to chess communities. It enriches the community, helping them develop their craft, but the community is still a community of humans.
http://theconversation.com/how-computers-changed-chess-20772
I can think of a few ways machines have beaten humans before, but where human experience is still valued in a way the machine achievement isn't. Modern weapons are valued for what they do, and they can beat any human, but the human practice of martial arts is still valued despite that fact. A player piano with a roll performed by Rachmaninoff will deliver an excellent reproduction of a historic performance, but I'd still rather listen to my friend play, even if what I'm hearing comes down to objectively worse key pressing.
Earlier quoted context omitted.
We think of these models as being ways to extend artistic expression... like guitar pedal or cameras or drum machines. Perhaps ML will give rise to something new and aesthetically interesting in this direction.
You are building a "smarter" arpegiator. If you really want to build a tool used by producers then it would be required to be a VST in the first place. But then I really doubt (as an amateur composer) than any artist could get anywhere with this. How can I transmit my feelings trough a bunch of data i've no control over ?
As an amateur composer as well, I have found uses for these types of models even without plugins / with "data I have no control over" for small flashes of interesting motifs/progressions that I rework, modify, and expand on my own. Inspiration comes in many forms.
[0] https://github.com/tensorflow/magenta-demos/tree/master/ai-j...