You know you’re in for something different with an article that contains this line: “as 256 bytes is becoming the new 4K, there has been ever more need to play decent music in the 256-byte size class. ”

In just a single line of code, Finnish artist and coder countercomplex, working with other contributors, is creating “bitwise creations in a pre-apocalyptic world.” What’s stunning is to listen to the results, even if you have trouble following the code – the results are complex and organic, glitchy but with compositional direction, as though the machine itself had learned to compose in its own, strange language.

This is, naturally, the opposite of the musical coding in the previous post: in place of human-readable languages representing abstractions atop other abstractions, this is pure algorithm transformed into music. Geeky, yes, but it also says something about musical composition and thought independent of the computer. It is as compact an expression of a human musical idea as one could imagine.

I recommend reading the whole blog post (and following the blog for new developments). Embedded in this whole exercise are thoughts about musical algorithms, the history of chip and 8-bit music and the demoscene, and, most interestingly, the question of whether digital music might yet yield “new” (or at least largely unknown) discoveries:

Hasn’t this been done before?

We’ve had the technology for all this for decades. People have been building musical circuits that operate on digital logic, creating short pieces of software that output music, experimenting with chaotic audiovisual programs and trying out various algorithms for musical composition. Mathematical theory of music has a history of over two millennia. Based on this, I find it quite mind-boggling that I have never before encountered anything similar to our discoveries despite my very long interest in computing and algorithmic sound synthesis. I’ve made some Google Scholar searches for related papers but haven’t find anything. Still, I’m quite sure that at many individuals have come up with these formulas before, but, for some reason, their discoveries remained in obscurity.

Algorithmic symphonies from one line of code — how and why? [countercomplex]

But can you dance to it?

Matt Ganucheau contributed to this story from San Francisco.

Composing with rules instead of playing notes directly, composer Richard Garrett has built a series of generative, algorithmic, ambient note makers and processors in Ableton Live and the Max for Live add-on. (And yes, user-generated content continues to be a rationale for why many people would purchase Max for Live in addition to Live itself.)

With loads of useful controls for duration, start, and voicing – and the ability to feed events into anything you like – the results in your own work could sound very different than what you see hear. But whatever your musical aspirations, you can check out the work in action in a demo video (top) and tutorial on how to work with the interface (bottom). And – provided you own Max for Live – it’s all free.

In another interesting twist, this isn’t necessarily just for making self-generating music. The event generator also has an input, so it could accompany live playing or otherwise respond to events.

Here’s how creator Richard describes the work:

I just thought I’d let you know about nwdlbots, my suite of algorithmic (generative) devices for the composition of music within Ableton Live. They include event generators, pitch and velocity selectors and control devices for interaction with each other and with other MIDI tracks and input devices.

As well as generating events at random, nwdlbots can respond to activity on other MIDI tracks in Live, or to input from a MIDI instrument. In effect, nwdlbots control the density of a piece by reducing their activity when things get too busy. They also have some rudimentary ideas about harmony and can follow a chord sequence.

The first set of nwdlbots are available for free download at sundaydance.co.uk. Also on the site: documentation and videos

By the way, this and many other conversations are now happening on LinkedIn:
Ableton Live Users @ LinkedIn [invite group]

nwdlbots (“noodlebots”), free download at Sunday Dance Music

“Noodling” sounds like a great description – and I know many of us musicians do enjoy a good noodle.

What makes music software popular? Simple recording, DJ, and remix apps unsurprisingly do well. But perhaps as a testament to the importance of individual music expression, some stranger entries do, too. And those less-typical software creations can give you new ways of exploring music creation and performance. Just take Nodal.

GarageBand sits comfortably at the top of the sellers list on Apple’s App Store. But, at least briefly, a generative composition tool has rocketed to second place. Nodal 1.7, available for both Mac and Windows, is unlike most music production tools. In place of linear track arrangement, clusters of graphical nodes represent musical structure, awaiting real-time experimentation. In a network you create, “virtual players” produce patterns by traversing a geometric map defining pitch, rhythm, and sequence.

Nodal and tools like it have always been able to create musical machines from simple elements, letting the user define an arrangement and then set it in motion. But Nodal 1.7 is a major release in that it allows MIDI control, so that you can actually “play” the structure and not just sit back and let it roll.

This isn’t just for ambient music lovers, either – sync features mean you can use Nodal just as easily in rhythmic pieces or even dance music.

Developer Peter Mcilwain tells CDM:

We think new features make [Nodal 1.7] a serious composing tool. Firstly, it can be synced to other applications. Next, individual networks can be triggered (like clips in Ableton) from MIDI notes. The velocity levels in these networks can be scaled according to the velocity of the triggering note. Also, the edges or connections between nodes can now contain MIDI controller curves. This is all demonstrated in [the YouTube clip at top].

The triggering aspect means that you can perform with a generative system in a very intuitive way. Also, I have been working on a piece for a flute ensemble in which I create a triggering score in Logic. This information is then sent to Nodal. Nodal then sends back MIDI which is rendered and recorded in Logic. I’m finding this a fascinating and natural way to work.

Nodal has slipped a bit since Peter first contacted me, but seeing this among the top Mac App Store apps to me is tremendously satisfying. Peter tells us they’re not giving up their day jobs, but it’s nice just to get to support great software.

Nodal: Generative Music Software

I’d love to hear more about Nodal here, especially if you’re making interesting stuff with it. Of course, to discuss with other Nodal users, your best bet is the Nodal discussion group:

Support | Nodal Google Group

The development team – Jon McCormack, Alan Dorin, Aidan Lane, Jon McCormack and Peter McIlwain of Monash University’s Centre for Electronic Media Art in Australia – have published technical papers, too:

Nodal R&D / Technical Papers

Nodal fans / users … or other folks doing development … we’d love to hear from you.

For more generative goodness, see also:

Intermorphic and Noatikl / Mixtilk, a cross-platform system that also includes mobile tools for iOS, from the same team that collaborated with Brian Eno and worked on the landmark SSEYO Koan system.

Hans Kuder’s Tiction uses graphical nodes as does Nodal, and, built in Processing, works on any OS (including Linux). Unfortunately, I’m not sure what happens to Hans or the tool; if anyone knows, let us know.

There are probably others I’m forgetting as the coffee settles in, so chime in in comments.

Tired of top 40 hits? Pooped on podcasts? Sapped on streams?

What if your radio could generative music that was never-before — and never-again — heard, all from dynamic, algorithmic software?

PatchWork Radio does that with Pd patches. It’s not a new idea, but the radio station here, at least, is modular – not just one patch but any number of patches can be transformed into radio, thanks to some Python scripting. Creator David Guy John notes:

I’ve recently just started up an internet radio station using PureData to stream generative music. The system will load and unload randomly chosen PD patches, synthesize all the audio in real time and then stream the results out.

You can listen to the stream at http://radio.rumblesan.com and more info is available at http://www.rumblesan.com/?p=265

I’m hoping to try and recruit some help to build patches for it as it’s a bit of a daunting task to do just on my own so if you could let people know about it I’d be really grateful.

So, who’s in – does this generate (ahem) some interest or ideas, and might you want to contribute?

It seems fitting that the kind of musical worlds imagined by artists like Brian Eno now can be deployed anywhere in the world, not just generated in one iteration, but in endlessly-transformable versions.

(But can you dance to it?)

Let’s start with what’s really important: Chris McCormick’s squeakyshoecore tunes may well make you tap your All Stars and smile. The words “algorithmically-generated acid” and mention of the multimedia patching environment Pd might not suggest feel-goody, cheery, geeky-sounding electronic grooves, but that’s exactly what’s come out. These robots know what they’re doing.

And yes, even a tune named after Chris’ favorite fractal can be good summer fun.

Behind the scenes, Chris’ music is produced generatively using algorithms created in the free and open source visual patching and programming environment Pure Data. The patches actually began as a scene for the iPhone/iPod touch interactive music environment RjDj, but you can now grab all the patches, try them out, and learn them, all with an explicit GPLv3 open source license.

GarageAcidLab

It’s not just about sitting back and letting the robots do the work, either; you can control the results live with a MIDI controller.

Check out the tunes, which are themselves available under a Creative Commons license (BY-NC-SA):
http://sciencegirlrecords.com/chr15m/squeakyshoecore/
On Archive.org / CC-licensed download page

And read the blog:
http://mccormick.cx/news/tags/squeakyshoecore

And great work, Chris. I hope that soon we can work with Chris and others to get some more information for newcomers to Pd on making their own musical creation and performance tools.

Swarm Music Album Black Allegheny from Evan Merz on Vimeo.

We’ve heard albums made by singular compositional minds and by bands. What would an album sound like if composed by swarm intelligence, by computer evolutionary models of individual agents or bots? That’s the question asked by composer Evan Merz in his new, full-length album “Black Allegheny.” (At top: the composer explains in a video.)

Western musical and creative tradition is steeped in linearity, from the forward motion of the music staff to the mythos of Aristotle’s Poetics.

So, maybe it’s little wonder that generative music – music that may not have linearity, or a beginning, middle, and end – hasn’t exactly been a big hit with the kids. Pioneers like Brian Eno have helped spread the gospel of generative music, but apart from lots of interesting experiments, there hasn’t been a lot of actual musical content. If you were to make a stack of generative music albums, your listening list would be fairly short.

All of that could be about to change. Programming code, the essential medium in which such models can be developed, is more accessible than ever. It’s also more visual, thanks to the popularization of tools like Processing, which can help make the abstract rules of generative music easier to grok. Merz, for his part, has taken on the challenge with his own Java-based software.

Saying the bots “compose” the music may be a little misleading. Generative music needs rules to operate. Before Eno, there was John Cage, whose “chance” compositions were as much defined by choices of materials as by ranges of indeterminacy. Merz makes a nod to Cage’s notion of a “gamut,” a collection of raw musical elements used as the input in the chance system. Here, though, Merz is aided by something Cage didn’t have: a swarm of intelligent “agents” can navigate those materials via simple rules, giving the music form and substance. Because they aren’t aware of the big picture, the music evolves more naturally, rather than being subjected to an over-arching narrative.

Or, as Merz puts it, “the tiny ant on the ground knows only what it sees around it.”

So, that’s the theory — what does the music sound like? Far from “ennui,” as Merz puts it, to me the results are organic. The structure is emergent from its materials, sounding almost like a natural physical process, like watching ice melt. The content ranges based on the gamut; like a lot of generative music, some sounds a whole lot like Brian Eno’s work. Others borrow from minimalist composers (Reich’s music itself might be seen as partially generative), and others take on an edgy urgency. The models that determine the bots are based on a popular, simple mathematical predator/food model, one often used in these works. Sometimes, you might imagine that evolutionary struggle playing out in the music.

You can read more about the process of developing this tool and the compositional ideas behind it at Evan’s blog:
Black Allegheny, Swarm Generated Music [Computer Music Blog]

For more explorations of sound and composition, check out Noise for Airports, which recently featured the work:
http://noiseforairports.com/

And you can stream the album or buy it for yourself for the light price of US$5 — though I’d like to see a software release, since that would mean each playback could be different. (Eno released an album in software form in the 90s, though tracking down the software now is evidently impossible – anyone with tips?)
Black Allegheny @ Bandcamp [Stream / download purchase]

Swarm Controlled Sampler – Becoming Live from Evan Merz on Vimeo.

Fractals, those wacky self-similar, rough geometries that resemble so many patterns in nature, were once all the rage. Ravers and digital artists embraced them, only to get bored with them, apparently. To billions of years of evolution and natural phenomena, they’re still cool. And to me, there’s still plenty to talk about when it comes to thinking how fractals might be all the rage.

Composer Terran Olson, a musician with a long resume that includes work with the Ives Quartet and Quartet San Francisco, takes on the idea of fractals in a new article. Writing for our friends at Rain Pro – makers of music and visual pro PC laptops – Terran explores how fractal patterns could be applied to sound.

Exploring Audio Fractals

The results are fascinating: they’re a kind of fractal synthesis. Of course, that gets at the heart of the question: just how do you map a visual pattern like a fractal – or anything else visual – to music? The answers aren’t always intuitive. The biggest question is whether to work at the scale of sound (Terran focuses on individual samples and impulses), or to deal with musical patterns. I knew I had read a fractal article in Electronic Musician; sure enough, in 1999 EM did a story on fractals that focused instead on pitch mappings. (Bonus: Bach even comes up.)

Fractals and Music

Composer Gustavo Diaz-Jerez penned that story, and the results tend toward algorithmic music. Many of the tools are now gone, though some survive (Csound) and other tools (Max/MSP, Pd, SuperCollider, Reaktor, ChucK) could certainly fill in.

And, of course, for a truly high-level musical approach to fractals, skip the individual sounds or individual notes and write a whole song, like Jonathan Coulton’s brilliant fractal ode, “Mandelbrot Set.” (It should also help anyone needing to, erm, brush up on their fractal theory.)

Sadly, neither of these articles is especially useful as how-to – great on theory, but not so practical if you haven’t tried these things before. That begs for a new tutorial. Are you working with fractals these days? I’d love to hear what you’re doing.

Composing music is not unlike programming – and either, at their best, can be expressive. In the early days of IT (before “IT” was even a term), many computer programmers came from a musical background. (And even early in the computer age, there was more call for software than symphonies – and more pay.)

But what if you could program music easily, using musical syntax in a programming language? That’s the question asked by languages like Velato. The commands actually aren’t as esoteric as you might expect; they include references to standard pitch and commands like “Change root note.” The language expresses notes, mapped to the alphabet, a bit like teaching the computer solfege. Using additional expressions, you can transform notes and generate musical materials.

The results sound a bit like an academic-sounding ragtime. And yes, they do sound as though they were generated by a computer. (Have a listen to a .MID file.)

For more on Velato:
Velato wiki page @ Esoteric Languages
A compiler built in .NET (Windows-only, though if you really wanted to I imagine you could quickly port to Mono or other environments)
An introduction [Rottytooth blog]

Creator Rottytooth is Daniel Temkin of New York. Along the same lines is Fugue, which specifies notes as intervals (oddly, the same way I learned atonal sightsinging, but that’s another story).

So, what use is all of this? Creating languages for music could be a first step to being able to write compositionally-useful generative music algorithms. That could allow composers writing for games, installations, performance, or software to create interactive music that generates itself without sounding like a bunch of random notes. And having an elegant, musical language to do so could allow you to sketch ideas with just a few keystrokes.

In fact, I’d argue that sitting with a big, monolithic music editor, you might actually spend more time and effort than a reduced language, once you learn it. I’m not sure these are mature enough to use yet, but the idea is fascinating. And who knows, maybe you’ll someday see this as a scripting option in the sequencer you already use.

Previously:
Code Your Own Sequencer? Archaeopteryx Generates MIDI with Ruby

Thanks to Grant Michaels, via Twitter, for the tip. (Grant’s Twitter feed includes lots of other goodies, too.)

I’m going to make this a minimalist post because I’ve said what I’ll say about Kodu, the one really cool part of Microsoft’s keynote yesterday, on Create Digital Motion. (Am I the only person who wishes Sparrow had just done the whole keynote?)

But have a look at the shot above. One of the complaints about generative and algorithmic music software (and music software in general) is that the interface has been so complex. Clearly, there are many other ways to design these interfaces, and in turn, to shape the way we use these to compose and perform music. Forget for a moment that games are “games,” and this this thing is “for kids,” and I think you’ll agree – there are lots of areas to explore, and lots of potential.

It doesn’t even require some futuristic music software. Imagine more complex rules in Ableton Live’s follow actions, made graphically.

Excuse me, I’m going to pick up some Tinker Toys to think about interactive design.

You Know, For Kids: Game Design, World Creation as Microsoft Research Previews Kodu [Create Digital Motion]

PS, I believe now more than ever that Music and Motion deserve separate sites, but have a look and I think you will find some overlap.

Better support for music and audio is still evolving (as well as lots of stability and compatibility improvements), but I have faith open-source coding tool Processing [site | on cdmu | on cdmo ] could yield wonderful new visual interfaces for music. Daniel Piker has the latest addition, inspired by a recent post here:

FizzyNumberMusicMaker at Open Processing, a site for sharing Processing sketches – warning, makes sound immediately!

Built on the Game of Life ideas from our friend wesen (of ruin & wesen), this project uses colored cells to trigger elaborate washes of piano sound. He writes:

If the cell’s state is not just simply on or off, but a number in a range then you get all sorts of interesting musical runs and trills. You can also clearly see the connection between the colours and the sound.

The headline sums up the experience of using it. Ah, I remember countless hours spent with a desktop Yamaha GM unit and my old Roland Sound Canvas SC-55. But even if the sound of a thousand attacking General MIDI pianos makes you hide under your desk, you ought to be able to see how a simple interface can yield lots of different results. I can’t wait to see what’s next. Previously:

Build Your Own Game of Life Sequencer in Processing: Video Featuring rwmidi

Since then, I’ve gotten to hang out with wesen in Berlin. Basically, rwmidi has a little ways to go. The biggest issue is how to schedule events. Processing is set up to base timing on framerate, which doesn’t work all that well for music applications, which require greater accuracy. There’s also the tantalizing possibility of figuring out a way to slave Processing sketches to MIDI clock – so you could have Ableton Live running, then pull up a Processing sketch, for instance. wesen is working on those problems, but if you’ve seen good solutions outside the (somewhat limited) Java APIs, let us know.