Category: machine Learning research

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wilding AI in Montreal

To wild: to make wild. To see and hear the wild underneath the tame, to know it is there and embrace it fully, pull it out from under, with love.

I am honoured and grateful to be part of a cohort of artists and thinkers in the research cohort Wilding AI. Over the last few years, we have met in different locales – online and around the world – to think about what it means to work and create in this so-called algorithmic moment.

We all have (as collectives do) many differing ideas and interests (I’ve written about our residency at Fiber Festival in Amsterdam earlier this year in a blog post here). We recently finished a residency at Université de Montreal’s Laboratoire formes · ondes, and presented a collection of works at a sold-out show at SAT Montreal.

This project was a rubber-meets-the-road of our many discussions, Google Meets, emails, scholarly articles, residencies, dancing, meals, hugs over the last few years. It was the first time we all sat down to make something that we could share with others.

The process of discussion between us, and the many open labs we have hosted around the world has been an incredible watering of the soil. We’ve wrestled with software, with plugins, githubs, jet lag (so much jet lag), Google Colab and Jupyter notebooks, microphones, the world on fire, speakers, guitars and drumsticks, our own bodies and voices in the moment of making. We’ve all approached what it means to make with tools that are (supposedly) efficient, that prioritize efficiency and automation and want us to see and use them in that way.

Some of us did that, some of us didn’t (or maybe it would be more accurate to say we all did to varying degrees).

But what we also did was to invite ourselves and each other to be wild: to ask ourselves what is down deep, what is wild in our own minds, hands, bodies, ears, hearts, and to allow that wildness to sing in our making with the machine. Each song was different; each song was wild. And the discussions we had among ourselves and with others was wild too.

Every moment we talked with others about being wild in this machine space – about rejecting some part of the workflow, or listening to the composition and what it needed despite/beyond/outside the math, to hear the algorithm break down and embrace the possibility of that endpoint – I saw it land with people. I saw it dawn on them that there is room, that the machine imperative can be lived with instead of lived under. I saw it land that they can listen to their bodies and their ancestors, that they can be slow, they can be human and live in the gap between machine math and the mess and wildness of what it means to be on this earth, together.

And that is what we, WAI, did in Montreal – we were together, on this earth, listening, sharing and being wild.

(the image for this post comes from SpatGRIS, the spatialization software used at the Laboratoire. More info here).

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wilding AI @ fiber festival

the theatre @ contact
the lovely lobby area @ contact
the audience starting to arrive for the open day
some impressions from the festival, including some crowded days of sharing our work
screengrab from my talk at the open lab

A number of us from the ongoing Wilding AI project just returned from the Fiber Festival in Amsterdam, where we had an open lab day and residency as part of our research into using machine learning and AI in workflows that centre sound. Many of us are investigating the idea of “sonic agents” (e.g. Maurice Jones’ project “feral ai”) but we all have our own takes on the concept of “wilding” and how it might apply to the research-creation AI space.

And therein lies our strength, and the strength of the project: that we all bring our own perspectives, interests and opinions to the group, and that we listen to each other; that we get inspired and stay curious; and that we all move and grow together in our own ways. Like a tree maybe – each branch has its own pattern, size, shape, density, but every branch is a part of the tree, and they are ways the tree stays nourished, shoots its roots into the ground, reaches for the sun, drinks in the rain, provides shelter and shade when the days grow too hot.

Every one of us has different levels of bewilderment and surety in this very broad field of what we currently call “AI”. Each one of us has their own set of refusals and embraces in what they want to do and how they want to do it (here’s a link to a powerpoint of the talk I gave at the open lab day). And we by no means all agree all the time. But what each person brings to the group is welcomed, listened to, sifted, expanded and deepened through being together in all the different ways.

I know I keep coming back to listening and ways of being together, sometimes in ways that don’t make sense on the surface when discussing specifics about, say, rehearsal rooms in Canadian theatre, or machine learning, or sound designing. But I do that because I keep learning the same lesson, over and over, everywhere – the ways in which we show up in a room (virtual or IRL) has a profound effect, more than any tool, any software, any code.

It’s the thing that I know, and that I keep knowing, and what I always find down at the bottom of everything, lifting us up, softly and strongly.

Daniela Huerta (MX/DE; IG @babyvulture) leading us through a Pauline Oliveros score, during a working group online meeting in preparation for our 2025 MUTEK Montreal residency with some of the members of Wilding AI (Gadi Sassoon (IT), Maurice Jones (CA/DE), Alexandre Saunier (CH/FRA), and ds)