
Making Music and Art Through Machine Learning - craigcannon
https://blog.ycombinator.com/making-music-and-art-through-machine-learning-doug-eck-of-magenta/
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pawy
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](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 opposite with art.

These things have nothing to do together.

~~~
ejfox
Art- and in fact, most creative endeavors often DO involve creating many
things until you discover something "cool".

With my personal experiments with generative art, I think of the machine
almost as a work assistant. I have a rough idea of what I'm going for, and the
ways to attempt it, and I teach that to my computer using code. But then I go
away from the computer and out into the world and drink coffee, sketch in my
notebook, and in the meantime my computerized assistant is back home working
on draft after draft of my latest piece of art.

I come home and I see what he's done, and most of it isn't great, but
occasionally there is a gem! I look at what he did for that gem and then
encourage him to do more of that, and then go back out into the world. I
highly disagree that machine learning is the opposite of art.

If you go to any traditional artist's studio you will often find notebooks
filled with discarded sketches and ideas. Paintings with color combinations or
techniques that weren't ideal. This is almost exactly the same process. And I
would argue that process is exactly what art is.

~~~
pawy
"most creative endeavors often do involve CREATING many things" ; not
generating them.

You've "selected" something you liked. You are no artist and should not call
your self like that. If you do, you will never inspire "simple" people.

At least if you do it would become the MacDonald of art.

Do nothing, sit and say to the bot if it fits you or not.

You're even worse than a DJ. The DJ actually works his selection and works his
transitions.

Sketches have been written out of artist mind. Not by some selection that fits
you or not.

Art is work.

~~~
ejfox
What is the difference between creation and generation?

What is the difference between me selecting the specific frame made by a
generative algorithm and photographer picking a specific moment in time to
capture a frame?

What's the difference between me using a generative algorithm and Michelangelo
using assistants to paint the Sistine Chapel?

~~~
pawy
Dedicating our life to find a meaning trough work.

Get interested in some artists and what they have achieved.

A humble human being would never call it self an artist.

That's the first mistake, and it's philosophical rather than technical.

I would say the tool it self is rather an piece of art. Not what it creates.

~~~
ejfox
I am really curious to hear your responses to the questions I raised

------
atarian
Here are some examples of music they've generated:

[https://magenta.tensorflow.org/performance-
rnn](https://magenta.tensorflow.org/performance-rnn)

------
circlefavshape
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

~~~
tachyonbeam
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.

~~~
QAPereo
That really sounds like the computer would have to _understand_ you and your
shifting moods better than most people could.

~~~
tachyonbeam
Which might actually be quite possible. At the very least, I'm sure machine
learning can have a better understanding of your general musical taste than
most of your friends do.

~~~
QAPereo
That's a pretty exciting prospect then, and I could imagine even a mediocre
implementation being almost catastrophically popular.

~~~
colecut
Spotify seems to implement this with custom play lists generated for you
daily, with those play lists broken down by different styles/moods

~~~
QAPereo
Personally, I find that Spotify doesn't "get" me in that way, not really.
Maybe it hits the broad center of a normal distribution, but I think a lot of
people lie outside of that. Even then, surely the challenge of curating
existing music which is heavily tagged is much less than composing it with a
mood or taste in mind. Just my gut feeling that.

------
bluetwo
A wide-ranging talk on computer generated art, music, stories, humor, etc.

I liked listening to it, but am disappointed by the field's disregard for
existing methods of structure. "We don't use rules".... well, rules have
helped mankind progress forward for hundreds of thousands of years.

Just because they don't easily transfer into your ML model doesn't mean they
are useless. Maybe the model needs to learn some new tricks.

~~~
kastnerkyle
There is a lot of interesting work going on in this area right now in the
research community - using ML for things like program synthesis, meta-
learning, and combining ideas from constraint satisfaction with ML approaches.

The rules based approach has (as you mention) years of history, so people are
currently exploring the green-ish fields of raw learning approaches with good
success on tasks where rules based approaches performed much worse or didn't
work at all (cf image recognition, speech recognition), and in some areas it
seems like the more you let the model learn / get rid of classical rules based
approaches (with enough data), the better it does. Whether that is true for
field X, not true _yet_ for field X, or will never be true for field X depends
on who you ask.

There is definitely a recent tide of models which are focused more on rule
learning, function generation, and so on. The general thing I see is that rule
based approaches with _good_ approximators/probability models to guide
heuristic or exact search can do crazy things - this is the story of AlphaGo
at a 10k foot level. People in the ML community are just more focused on the
_new-ish_ part (learning good probability/function approximators from data)
right now.

Just because rules aren't incorporated widely yet, doesn't mean they won't be
in the future. I am personally very interested in this direction, and a bunch
of work from Sony CSL (Pachet et. al.) has focused heavily on this idea in the
past.

As an aside, whenever you hear an ML researcher say "prior", it is generally
functioning as some kind of soft or occasionally hard rule - so maybe there
are more rules floating around than it seems. Soft rules aka priors are
generally (much!) easier for gradient descent style optimization and
incorporating directly into models, so we tend to have priors rather than hard
rules as seen in many other parts of computer science. Even the structure of
the model itself can be seen as a prior.

~~~
bluetwo
Thanks for the additional info.

------
stevehiehn
I heard a quote about automobiles: "When you remove the horse from the cart
you no longer have a horse & buggy" I suspect if convincing music can be
generated procedurally people will no longer put much value in a linear
composition. Its possible music will become interactive via interfaces like AR
and VR.

------
rememberlenny
I did something similar in relation to art.

Making physical art based on inspiration from machine learning processes:

[https://medium.com/@rememberlenny/digital-processes-
inspirin...](https://medium.com/@rememberlenny/digital-processes-inspiring-
analog-paintings-a358eb7801a0)

------
6stringmerc
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 structure.
> However, to our ears, the local characteristics of the performance (i.e. the
> phrasing within a one or two second time window) are quite expressive._

It's understandable to be encouraged by progress, but to my ears, it's not
really expressive other than the first thought that I had when listening to
the piece:

"That piano player is having a stroke, somebody should do something to help."

~~~
dougeck
I've used the same analogy. Its unconditional and produces no coherent
structure, but at least it captures some pianist-like timing and dynamics.
Magenta is a github project ... please do something to help! :-)

~~~
6stringmerc
Eh, asking a musician to write code is like asking a programmer to learn a
scale on an accordion. Either you're going to see the failures in your own
art, and be open to criticism, or ask for somebody to do it for you.

I'll put it thusly: As a broke-ass musician barely making ends meet, I'll be
more than happy to contribute if Alphabet pays off what's left of the mortgage
on my house.

Until then, I've only got the perspective that a project like this is trying
to take food off my plate, money out of my pocket, and replace me. If you want
my help, Son, you got to come better at me than with Altruism.

Otherwise, the best thing I can do to help is to say "This project is a heap
of shit and your time is better spent elsewhere" without tinging it with too
much condescension. Your child is brain damaged. Take it to Oregon.

