Competition – Win one year’s free membership to Music Hackspace
Dom Aversano
We are giving away a year’s free membership – to enter, all you have to do is leave a comment on this page about at least one composer or musician who has greatly influenced your approach to computer music.
We want to know two things.
How has their music affected or influenced you?
An example of a piece of their music you like, and a short description of why.
Anyone who completes the above will be entered into the competition on an equal basis (you are welcome to list more than one person, but this will not improve your chances of winning) with the winner assigned at random and announced on Saturday 4th of November via the Music Hackspace newsletter.
To get the ball rolling, I will provide two examples.
Kaija Saariaho / Vers le blanc
I arrived somewhat late to Kaija Saariaho’s music, attending my first live performance of her music two years prior to her death this year, yet despite this, her music has greatly influenced me in the short time I have known it.
Although I have not heard the piece in full (since it has never been released) the simple 1982 electronic composition by Saariaho, Vers le blanc, captured my imagination.
The composition is a 15-minute glissando from one tone cluster (ABC) to another (DEF). Saariaho used electronic voices to produce this. The composition raises questions about what is perceptible. For instance, can the change in pitch be heard from moment to moment? Can it be sensed over longer time periods?
The piece made me question what can be considered music. Are they notes if they never fix on a pitch? can such a simple process over 15 minutes be artistically enjoyable to listen to? what would be the ideal circumstance to listen to such music? I experienced this music partly as an artistic object of study and meditation and partly as a philosophical provocation.
Burial / Come Down to Us
Burial’s idiosyncratic approach to technology gives rise to a unique sound. He famously stated in a 2006 interview that he used Soundforge to create his music, without the use of any multitrack sequencing or quantisation. This stripped-down use of technology gives the music an emotional directness and a more human feel.
I find his track Come Down to Us particularly inspiring. At 13 minutes long it uses a two-part binary form for the structure. The composition uses audio samples from a transgender person, and it was only after a few years of listening that it occurred to me that the form might describe the subject. At 7 minutes the entire mood and sound of the track changes from apprehensive to triumphant, potentially describing a person undergoing — or having undergone — a psychological or physical transition. Released in 2013, this was long before the divisive culture wars and undoubtedly intended simply as an artistic exploration.
Leave your comment below to enter the competition. Please refer to the guidelines above. The winner will be announced on Saturday 4th of November via the Music Hackspace newsletter.
Can AI help us make humane and imaginative music?
Dom Aversano
There is a spectrum upon which AI music software exists. On one end are programs which create entire compositions, and on the other are programs that help people create music. In this post I will focus on the latter part of the spectrum, and ask the question, can AI help us compose and produce music in humane and imaginative ways? I will explore this question through a few different AI music tools.
Tone Transfer / Google
For decades the dominance of keyboard interaction has constrained computer music. Keyboards elegantly arrange a large number of notes but limit the control of musical parameters beyond volume and duration. Furthermore, with the idiosyncratic arrangement of a keyboard’s notes, it is hard to work — or even think — outside of the 12-note chromatic scale. Even with the welcome addition of pitch modulation wheels and microtonal pressure-sensitive keyboards such as Roli’s fascinating Seaboard, keyboards still struggle to express the nuanced pitch and amplitude modulations quintessential to many musical cultures.
For this reason, Magenta’s Tone Transfer may represent a potentially revolutionary change in computer music interaction. It allows you to take a sound or melody from one instrument and transform it into a completely different-sounding instrument while preserving the subtleties and nuances of the original performance. A cello melody can be transformed into a trumpet melody, the sound of birdsong into fluttering flute sounds, or a sung melody converted into a number of traditional concert instruments. It feels like the antidote to autotune, a tool that captures the nuance, subtly, and humanity of the voice, while offering the potential to transform it into something quite different.
In practice, the technology falls short of its ambitions. I sang in a melody and transformed it into a flute sound, and while my singing ability is unlikely to threaten the reputation of Ella FitzGerald, the flute melody that emerged sounded like the flautist was drunk. However, given the pace at which machine learning is progressing, one can expect it to be much more sophisticated in the coming years, and I essentially regard this technology as an early prototype.
Google has admirably made the code open source and the musicians who helped train the machine learning algorithms are prominently credited for their work. You can listen to audio snippets of the machine learning process, and hear the instrument evolve in complexity after 1 hour, 3 hours, and 10 hours of learning.
It is not just Google developing this type of technology — groups like Harmonai and Neutone doing similar things and any one of them stands to transform computer music interaction, by anchoring us back into the most universal instrument, the human voice.
Mastering / LANDR
Although understanding how mastering works is relatively straightforward, understanding how a mastering engineer perceives music and uses their technology is far from simple since there is as much art as there is science to their craft. Therefore, is this a process that can be devolved to AI?
That is the assumption behind LANDR’s online mastering service which allows you to upload a finished track for mastering. Once it is processed, you are given the option to choose from three style settings (Warm, Balanced, Open) and three levels of loudness (Low, Medium, High), with a master/original toggle to compare the changes made.
I uploaded a recent composition to test it. The result was an improvement on the unmastered track, but the limited options to modify it gave the feeling of a one-size-fits-all approach, inadequate for those who intend to carefully shape their musical creations at every stage of production. However, this might not be an issue for people on lower-budget projects, or those who intend to simply and quickly improve their tracks for quick release.
In a desire to understand the AI technology I searched for more precise details, and while the company says that ‘AI isn’t just a buzzword for us’ I could only find a quote that does little to describe how the technology actually works.
Our legendary, patented mastering algorithm thoroughly analyzes tracks and customizes the processing to create results that sound incredible on any speaker.
While LANDR’s tool is useful for quick and cheap mastering, it feels constrained and artistically unrewarding if you want something more specific. The interface also feels like it limits the potential of the technology. Why not allow text prompts such as: “cut the low-end rumble, brighten the high end, and apply some subtle vintage reverb and limiting”.
Fastverb / Focusrite
Unlike mastering, reverb is an effect rather than a general skill or profession, making it potentially simpler to devolve aspects of it to AI. Focusrite’s Fastverb reverb effect uses AI to analyse your audio before prescribing certain settings for you based on this, which you can then go on to tweak. The company is vague about how their AI technology works, simply stating.
FAST Verb’s AI is trained on over half a million real samples, so you’ll never need to use presets again.
I use the plugin on a recent composition. The results were subtle but an improvement. I adjusted some of the settings and it sounded better. Overall, I had the impression of a tasteful reverb that would work with many styles of music.
Did the AI help significantly in arriving at the desired effect? It is hard to say. I would assume for someone with very limited experience using such tools, yes, but without someone confident with an effect, I doubt it saves much time at all.
I am aware however there is the potential for snobbery here. After all, if a podcaster can add a decent reverb to their show or a guitarist can add some presence to their recording easily, that’s no bad thing. They can if they want go on to learn more about these effects and fine-tune them themselves. For this reason purpose, it represents a useful tool.
Overview
LANDR’s Mastering service and Focusrite’s Fastverb are professional tools that I hope readers of this article will be tempted to try. However, while there is clearly automation at work, how the AI technology works is unclear. If the term AI is used to market tools, there should be clarification of what exactly it is — otherwise one might as well just write ‘digital magic’. By contrast, Google’s Tone Transfer have made their code open source, as well as describing in detail how they use machine learning, and the people involved in training the models.
I expect that the tools that attempt to speed up or improve existing processes, such as mastering and applying reverb, will have the effect of lowering the barrier to entry into audio engineering, but I have yet to see evidence it will improve it. In fact, it could degrade and homogenise audio engineering by encouraging people to work faster but with less skill and care.
By contrast, the machine learning algorithms that Googe, Harmonai, Neutone, and others are working on, could create meaningful change. They are not mature technologies, but there is the seed of something profound in them. The ability to completely transform the sounds of music while preserving the performance and the potential to bring the voice to the forefront of computer music could prove to be genuinely revolutionary.
What follows from the collapse of NFTs?
Dom Aversano
Almost a quarter of a century after Napster fired a torpedo into the record industry one might have expected stability to have returned, but the turmoil continues well into the new century without any signs of resolution.
The story is familiar. MP3 collections never felt like record collections, making them ripe to be superseded by full-catalogue music streaming. Streaming is unprofitable for the companies selling it and unsustainable for the musicians on it, so in a bid to save themselves, not music, the platforms are now transforming into rivers of algorithmically recommended muzak. Ironically, the oldest medium is in the healthiest state, vinyl, and while it is inspiring to know people still go out and buy records, it does not help solve the problem of digital music.
Given this context, it was always tempting to see NFTs — or non-fungible tokens — as the saviour of digital music. But with Sam Bankman-Fried now standing on trial and 95% of NFTs estimated to be worthless we should be asking, what went wrong?
It is beyond the scope of this article to explain what NFTs are — which has been done well elsewhere — but what can be said is the heavy nomenclature they carry can make it feel impenetrable and confusing: you have blockchain, minting, wallets, cryptocurrency, drops, Bitcoin, Metaverse, Web 3, smart contracts etc. The time required to make sense of this — much like an NFT — is a luxury few can afford, providing a wall of obscurantism that imbues the culture with an aura of mystique and intellectualism.
My experience took me down a winding path. Initially, I found NFTs interesting, as they seemed like an innovative method for digital ownership that could help fund the creation of new music and provide fans with a strong connection to their favourite artists, but as my research accumulated their appeal steadily diminished. A combination of too-good-to-be-true promises and scammy behaviour made it seem murky, if not at times actively sinister.
While I am not closed off to the possibility of something valuable emerging from this world (for instance, smart contracts seem genuinely interesting) based on the evidence, NFTs were always doomed to fail.
Here is why.
The torrent of terminology in this culture makes it easy to be blinded by the science and lose sight of the obvious — for instance, cryptocurrencies, despite the name, are not currencies. There is barely a thing on Earth you can buy with crypto. It is actually an asset untethered to economic activity, or simpler yet, an elaborate gambling token. Just as nobody wants to appear a philistine for not appreciating a certain art form, nobody wants to feel like a Luddite for not understanding a particular technology, but spend your evenings and weekends dispassionately breaking down the terminology and you’ll find little of substance remains.
Most people try to understand cryptocurrency in a purely technical sense and ignore the sociological of its emergence. Bitcoin arose shortly after the 2008 financial crisis when mistrust of banking was at an all-time high. At this time having a so-called currency circumventing banks was music to people’s ears, and the Hollywood superhero manner in which Bitcoin entered the world through a mysterious unknown figure called Satoshi Nakamoto only added to its anarcho-utopian appeal.
Blockchain sounds cooler than it is. Some blockchains create huge environmental damage, have very long transaction times, and are vulnerable to privacy breaches and theft. If you lose your password to your digital wallet or if it falls into someone else’s hands you may lose everything, without any recourse to institutional support or insurance. Most concerning of all, far from being a tool for honesty and transparency, cryptocurrency is regularly used by organised criminals as a tool for money laundering. For these reasons, blockchain has been referred to at various points as ‘a solution in search of a problem’.
Experts have much less faith in cryptocurrency than the public. An economist who famously predicted the 2007–08 subprime mortgage crisis, Nouriel Roubini, called crypto ‘a scam’ and a ‘Ponzi scheme’ that preys on young people, people on lower income, and minorities, and advises people to ‘stay away’, referring to those who run the industry as ‘crooks’ that ‘literally belong in jail’.
Even if none of the above really dents your belief in the validity of cryptocurrencies/NFTs/blockchains, there is a gaping flaw that is impossible to ignore.
NFTs have no intrinsic value.
I can put a photo of the Taj Mahal on a blockchain and link it to you, but that doesn’t mean you own a brick of it.
Writer and programmer Stephen Dhiel, who is a vociferous critic of cryptocurrencies, offered the following analogy about NFTs in a Twitter/X thread.
There is one comparable market to NFTs: The Star Naming Market (…) Back in the 90s some entrepreneurs found you could convince the public to buy “rights” to name yet-unnamed stars after their loved ones by selling entries in an unofficial register (…) You’d buy the “rights” to a name [sic] the star and they’d send you a piece of paper claiming that you were now the owner of said star. Nothing was actually done in this transaction, you simply paid someone to update a register about a ball of plasma millions of light years away. (…) NFTs are the evolution of this grift in a more convoluted form. Instead of allegedly buying a star, you’re allegedly buying a JPEG from an artist. Except you’re not buying the image, you’re buying a digitally signed URL to the image.
With NFTs now largely worthless, it’s hard to argue with Dhiel’s analysis. So where does this leave us?
Few genuinely innovative ideas remain, but a company called JKBX has proposed that people can buy royalty shares of their favourite musicians’ songs. The problem is, even if it worked, would it be healthy to have fans treating their favourite artists’ songs as investments? Would listening to All You Need is Love feel the same if you were waiting for your share of a royalty payment to come through? Is turning music into a weird stock market for royalties really the best thing we can dream up?
After nearly a quarter of a century of unsuccessfully trying to resurrect the 20th-century music recording industry for the 21st-century, perhaps it is time to ask, was this ever the right goal? MP3s, streaming, and NFTs, did not balance the boat, which still rocks about aimlessly on stormy seas.
Perhaps the original goal was never ambitious or imaginative enough, after all, why resurrect an old method of distributing music when you could create a new one? NFTs were attractive to people for many reasons, but a major one was they promised a new internet culture — Web 3, metaverse etc. — that could offer ordinary people economic dignity. That people found this appealing is grounds for hope, as it demonstrates there is an appetite for a radical departure from the stagnant and centralised world of the social media empires.
The question that remains is: can we imagine it and build it? And if not now, when? If music wishes to remain a relevant art form, it can’t afford another quarter-century of floundering.
Do you have thoughts on what you have read? If so, please leave your comments below.
Further information on cryptocurrency/NFTs/blockchain
The Missing Crypto Queen — Podcast by investigative journalist Jamie Bartlett
The Case Against Crypto — Essay by programmer Stephen Diehl
Crypto is dead — Debate between Yanis Varoufakis & Viktor Tábori
How to design a music installation – an interview with Tim Murray-Browne (part 2)
Dom Aversano
How to design a music installation - an interview with Tim Murray-Browne (part 2)
In the first part of this interview, artist Tim Murray-Browne discussed his approach to creating interactive installations, and the importance of allowing space for the agency of the audience with a philosophy that blurs the traditional artist/audience dichotomy in favour of a larger-scale collaboration.
In the second part of this interview, we discuss how artificial intelligence and generative processes could influence music in the near future and the potential social and political implications of this, before returning to the practical matters of advice on how to build an interactive music installation and get it seen and heard.
I recently interviewed the composer and programmer Robert Thomas who envisions a future in which music behaves in a more responsive and indeterminate manner, more resemblant to software than the wax cylinder recording that helped define 20th-century music. In this scenario, fixed recording could become obsolete. Is this how you see the future?
I think the concept of the recorded song is here to stay. In the same way, I think the idea of the gig and concert is here to stay. There are other things being added on top and it may become less and less relevant as time goes on. Just in the way that buying singles has become less relevant even though we still listen to songs.
I think the most important thing is having a sense of personal connection and ownership. This comes back to agency, where I feel I’m expressing myself through the relationship with this music or belonging to a particular group or community. What I think a lot of musicians and people who make interactive music can get wrong is since they take such joy and pleasure in being creatively expressive, they think they can somehow give that joy to someone else without figuring out how to give them some kind of personal ownership of what they’re doing.
As musicians it’s tempting to think we can make a track and then create an interactive version, and that someone’s going to listen to that interactive version of my track and remix it live or change aspects of it, and have this personalised experience that it is going to be even better because they had creative agency over it.
I think there’s a problem with that because you’re asking people to do some of the creative work but without the sense of authorship or ownership. I may be wrong about this because in video games you definitely come as an audience and explore the game and develop skill and a personal style that gives you a really personal connection to it. But games and music are very different things. Games have measurable goals to progress through, and often with metrics. Music isn’t like that. Music is like an expanse of openness. There isn’t an aim to make the perfect music. You can’t say this music is 85% good.
How do you see the future?
I agree with Robert in some sense, but where I think we’re going to see the song decline in relevance has less to do with artists creating interactive versions of their work and more to do with people using AI to completely appropriate and remix existing musical works. When those tools become very quick and easy to use I think we will see the song transform into a meme space instead. I don’t see any way to avoid that. I think there will be resistance, but it is inevitable.
In the AI space, there are some artists who are seeing this coming and trying to make the most of it. So instead of trying to stop people from using AI to rip off their work, they’re trying to get a cut of it. Like say, okay you can use my voice but you’ll give me royalties. I’ve done all of this work to make this voice, it’s become like a kind of recognizable cultural asset and I know I’m going to lose control of it, but I want some royalties and to own the quality of this vocal timbre
Is there a risk in deskilling, or even populism, in a future where anyone can make profound changes to another person’s creative work? The original intention of copyright law was to protect artists’ work from falling out of their hands financially and aesthetically. The supposed democratisation of journalism has largely defunded and deskilled an important profession and created an economy for much less skilled influencers and provocateurs. Might not the same happen to music?
The question of democratisation is problematic. For instance, democracy is good, but there are consequences when you democratise the means of production, particularly in the arts where a big part of what we’re doing is essentially showing off. Once the means of production are democratised, then those who have invested in the skills previously needed lose that capacity to define themselves through them. Instead, everyone can do everything and for this short while, because we’re used to these things being scarce, it suddenly seems like we’ve all become richer. Then pretty soon, we find we’re all in a very crowded room trying to shout louder and louder. It’s like we were in a gig and we took away the stage and now we’re all expecting to have the same status that the musician on the stage had.
I can see your concerns with that, but when it comes to music transforming from being a produced thing to being very quickly made with AI tools by people who aren’t professional. If you’re a professional musician there will still be winners and losers, and those winners and losers will in part be those who are good at using the tools. There will be those with some kind of artistic vision. And there’ll be those who are good at social media and networking, and good at understanding how to make things go viral.
It’s not that different from how music is now. It takes more than musical talent to become a successful artist as a musician, you’ve got to build relationships with your fans, you have to do all of these other things which maybe you could get away with not doing so much in the past.
Let’s return to the original theme of what makes for a good installation. What advice would you give to someone in the same position now that you were in just over a decade ago when starting Cave of Sounds?
In 2012 when we started building Cave of Sounds Music Hackspace was a place for people to build things. This was fundamental for me. People there were making software and hardware and there was this sort of default attitude of ‘we built it, now we’re going to show somebody’. We’re going to get up in the front of the room and I’m going to talk to you about this thing, and maybe I’ll play some music on it.
I find the term installation problematic because it comes from this world of the art gallery and of having a space and doing something inside the space where it can’t necessarily just be reduced to a sculpture or something. Whereas, for me, it was just a useful word to describe a musical device where the audience is going to be actively interacting with it, rather than sitting down and watching a professional interact with it. So that shift from a musician on a stage to an audience participating in the work.
I don’t think it necessarily has to begin with a space. It needs a curiosity of interaction. Maybe I’m just projecting what I feel, but what I observed at Music Hackspace is people taking so much enjoyment in building things, and less time spent performing them. Some people really want to get up and perform as musicians. Some people really want to build stuff for the pleasure of building.
How do you get an installation out into the world?
How to get exhibited is still an ongoing mystery to me, but I will say that having past work that has succeeded means people are more likely to accept new work based on a diagram and description. Generally, having a video of a piece makes it much more likely for people to want to show it. The main place things are shown is in festivals, more than galleries or museums. Getting work into a festival is a question of practical logistics: How many people are going to experience it and how much space and resources does it demand? And then festivals tend to conform to bigger trends – sometimes a bit too much I think as then they end up all showing quite similar works. When we made Cave of Sounds, DIY hacker culture and its connection to grassroots activism was in the air. Today, the focus is the environment, decolonisation, and social justice. Tomorrow there will be other things.
Then, there’s a lot of graft, and a lot of that graft is much easier when you’re younger than when you’re older. I don’t think I could go through the Cave of Sounds process today like I did back then. I’m very happy I did it back then.
What specifically about the Cave of Sounds do you think made it work?
The first shocking success of Cave of Sounds is that when we built it we had like a team of eight, and I had a very small fee because I was doing this artist residency, but everyone else was a volunteer on that project or collaborating artists, but unpaid. And we worked together for eight months to bring it together.
A lot of people came to the first meeting but from the second meeting, the people who turned up from that point forward were the eight people making the work who stuck through to the end. I think there’s something remarkable about that. Something about the core idea of the work really resonated with those people, and I think we got really lucky with them. And there was a community that they were embedded in as well. But the fact that everyone might made it to the end, just like shows that there was something kind of magical in the nature of the work and the context of that combination of people.
So a work like Cave Sounds was possible because we had a lot of people who were very passionate, and we had a diversity of skills, but we also had like a bit of an institutional name behind us. We had a small budget as well, but the budget was very small, and most of the budget did not pay for the work. The budget covered some of the materials, really, but a significant amount of labour went into that piece, and it came from people working for passion.
Do you have a dream project or a desire for something you would like to do in the future?
For the past few years I’ve been exploring how to use AI to interpret the moving body so that I can create physical interaction without introducing any assumptions about what kind of movement the body can make. So if I’m making an instrument by mapping movement sensors to sound, I’m not thinking ‘OK this kind of hand movement should make that kind of sound’ but instead training an AI on many hours of sensor data where I’m just moving in my own natural way and asking it ‘What are the most significant movements here?’
I’m slightly obsessed with this process. It’s giving me a completely different feeling when I interact with the machine, like my actions are no longer mediated by the hand of an interaction designer. Of course, I’m still there as a designer, but it’s like I’m designing an open space for someone rather than boxes of tools. I think there’s something profoundly political about this shift, and I’m drawn to that because it reveals a way of applying AI to liberate people to be individually themselves, rather than using it to make existing systems even more efficient at being controlling and manipulative which seems to be the main AI risk I think we’re facing right now. I could go on more as well – moving from the symbolic to the embodied, from the rational to the intuitive. Computers before AI were like humans with only the left side of the brain. I think they make humans lose touch with their embodied nature. AI adds in the right side, and some of the most exciting shifts I think will be in how we interact with computers as much as what those computers can do autonomously.
So far, I’ve been exploring this with dancers, having them control sounds in real-time but still being able to dance as they dance rather than dancing like they’re trapped inside a land of invisible switches and trigger zones. And in my latest interactive installation Self Absorbed I’ve been using it to explore the latent space of other AI models, so people can morph through different images by moving their bodies. But the dream project is to expand this into a larger multi-person space, a combined virtual and physical realm that lets people influence their surroundings in all kinds of inexplicable ways by using the body. I want to make this and see how far people can feel a sense of connection with each other through full-body interfaces that are too complicated to understand rationally but are so rich and sensitive to the body that you can still find ways to express yourself.
Cave of Sounds was created by Tim Murray-Browne, Dom Aversano, Sus Garcia, Wallace Hobbes, Daniel Lopez, Tadeo Sendon, Panagiotis Tigas, and Kacper Ziemianin with support from Music Hackspace, Sound and Music, Esmée Fairbairne Foundation, Arts Council England and British Council.
To find out more about Tim Murray-Browne you can visit his website or follow him on Substack, Instagram, Mastodon, or X.
A guide to seven powerful programs for music and visuals
Dom Aversano
What should I learn? A guide to seven powerful programs for music and visuals.
The British saxophonist Shabaka Hutchings described an approach to learning music that reduces it down to two tasks: the first is to know what to practise, and the second is to practise it. The same approach works for coding, and though it is a simple philosophy that does not necessarily make it easy. Knowing what to practise can feel daunting amid such a huge array of tools and approaches, making it all the more important to be clear about what you wish to learn so you can then devote yourself without doubt or distraction to the task of studying.
As ever the most important thing is not the tool but the skills, knowledge, and imagination of the person using it. However, nobody wants to attempt to hammer a nail into the wall with a screwdriver. Some programs are more suited to certain tasks than others, so it is important to have a sense of their strengths and weaknesses before taking serious steps into learning them.
What follows is a summary and description of some popular programs to help you navigate your way to what inspires you most, so you can learn with passion and energy.
Pure Data
Pure Data is an open-source programming language for audio and visual (GEM) coding that was developed by Miller Puckette in the mid-1990s. It is a dataflow language where objects are patched together using cords, in a manner appealing to those who like to conceptualise programs as a network of physical objects.
Getting started in Pure Data is not especially difficult even without any programming experience, since it has good documentation and plenty of tutorials. You can build interesting and simple programs within days or weeks, and with experience, it is possible to build complex and professional programs.
The tactile and playful process of patching things together also represents a weakness of Pure Data, since once your programs become more advanced you need increasing numbers of patch cables, and dragging hundreds – or even thousands – of them from one place to another becomes monotonous work.
Cost: free
Max/MSP/Jitter and Max for Live
Max/MSP is Pure Data’s sibling, which makes it quite easy to migrate from one program to the other, but there are significant and important differences too. The graphical user interface (GUI) for Max is more refined and allows for organising patching chords in elegant ways that help mental clarity. With Max for Live you have Max built into Ableton – bringing together two powerful programs.
Max has a big community surrounding it in which you can find plenty of tutorials, Discord channels, and a vast library of instruments to pull apart. Just as Pure Data has GEM for visualisation Max has Jitter, in which you can create highly sophisticated visuals. All in all, this represents an incredibly powerful setup for music and visuals.
The potential downsides are that Max is paid, so if you’re on a small budget Pure Data might be better suited. It also suffers from the same patch cord fatigue as Pure Data, where you can end up attaching cords from one place to another in a repetitive manner.
Cost: $9.99 per month / $399 permanent licence or $250 for students and teachers
SuperCollider
SuperCollider is an open-source language developed by James McCartney that was released in 1996, and a more traditional programming language than either Pure Data or Max. If you enjoy coding it is an immensely powerful tool where your imagination is the limit when it comes to sound design, since with as little as a single line of code you are capable of creating stunning musical outputs.
However, SuperCollider is difficult, so if you have no programming experience expect to put in many hours before you feel comfortable. Its documentation is inconsistent and written in a way that sometimes assumes a high level of technical understanding. Thankfully, there is a generous and helpful online forum that is very welcoming to newcomers, so if you are determined to learn, do not be put off by the challenge.
An area that SuperCollider is lacking in comparison to Max and Pure Data is a sophisticated built-in environment for visuals, and although you can use it to create GUIs, they do not have the same elegance as in Max.
Cost: free
TidalCycles
Though built from SuperCollider, TidalCycles is nevertheless much easier to learn. Designed for the creation of algorithmic music, it is popular in live coding or algorave music. The language is intuitive and uses music terminology in its syntax, giving people with an existing understanding of music an easy way into coding. There is a community built around it complete with Discord channels and an active community blog.
The downsides to TidalCycles are the installation is difficult, and it is a somewhat specialist tool that does not have as broad capabilities as the aforementioned programs.
Cost: free
P5JS
P5JS is an open-source Javascript library that is a tool of choice for generative visual artists. The combination of a gentle learning curve and the ease of being able to run it straight from your browser makes it something easy to incorporate into one’s life, either as a simple tool for sketching out visual ideas or as something much more powerful that is capable of generating world-class works of art.
It is hard to mention P5JS without also mentioning Daniel Shiffmen, one of the most charismatic, humorous, and engaging programming teachers, who has rightly earned himself a reputation as such. He is the authour of a fascinating book called The Nature of Code which takes inspiration from natural systems, and like P5JS is open-source and freely available.
Cost: free
Tone.js
Like P5JS, Tone.js is also a Javascript library, and one that opens the door to a whole world of musical possibilities in the web browser. In the words of its creators it ‘offers common DAW (digital audio workstation) features like a global transport for synchronizing and scheduling events as well as prebuilt synths and effects’ while allowing for ‘high-performance building blocks to create your own synthesizers, effects, and complex control signals.’
Since it is web based one can get a feel for it by delving into some of the examples on offer.
Cost: free
TouchDesigner
In TouchDesigner you can create magnificent live 3D visuals without the need for coding. Its visual modular environment allows you to patch together modules in intuitive and creative ways, and it is easy to input midi or OSC if you want to incorporate a new visual dimension to your music. To help learn there is an active forum, live meetups, and many tutorial videos on this site. While the initial stages of using TouchDesigner are not difficult, one can become virtuosic with the option of even writing your own code in the programming language Python.
There is a showcase of work made using TouchDesigner on their website which gives you a sense of what it is capable of.
Cost: All features $2200 / pro version $600 / free for personal and non-commercial use.
Bishi: a journey in music & technology
Bishi‘s talk explores her journey in music & technology, stemming from her cultural roots, charting the steps between being a musician, composer & performer to founder and technologist. The talk will feature some live Sitar midi-mapping performance.
Singer, electronic rock- sitarist, Composer, producer and performer BISHI was born in London of Bengali heritage. A multi-instrumentalist, BISHI received musical training in both Hindustani and Western Classical styles, including the study of the sitar under Gaurav Mazumdar a senior disciple of Ravi Shankar.
She has written & recorded two albums, produced by Matthew Hardern: Nights at The Circus and Albion Voice. Bishi co-produced her third album, ‘Let My Country Awake,’ with Jeff Cook.
Bishi is the founder of WITCiH: The Women in Technology Creative Industries Hub, a platform elevating Women & Non-Binary in tech, through commissions, performances & podcasts. She fronted a documentary for BBC Radio 4 exploring the future of technology in music.
Bishi’s collaborations & commissions for the stage have included The London Symphony Orchestra, The Kronos Quartet, Yoko Ono’s Meltdown, The Science Gallery, Nick Knight’s Showstudio & session work with Sean Ono Lennon, Luke Vibert, Richard Norris, Daphne Guinness & Tony Visconti. Bishi was recently a Tanpura soloist for the City of London Sinfonia, performing Jonny Greenwood’s ‘Water.’
Bishi was lead commissioned artist for Delia Derbyshire Day, who commissioned her to compose a piece of music, celebrating 50 years of White Noise ‘An Electric Storm.’ This resulted in ‘The Telescope Eye,’ an EP she co-produced with Richard Norris. Bishi fronted a documentary for Radio 4 centred around the groundbreaking tech company, ROLI. Her most recent EP ‘Of Rituals & Rites, with composer, Neil Kaczor is out on March 20th 2020, for Spring Equinox.
