Deep Meditations (2018)

Deep Meditations is a series of abstract films and video and sound installations that celebrate life, nature, the universe and our subjective experience of them. The works invite us on a spiritual journey through slow, meditative, continuously evolving images and sounds, told through the imagination of a deep artificial neural network.

“It feels like the machine is trying to tell me something…” – audience member

What does love look like?

What does grief look like?

What does faith look like?

You know what love is, not because someone taught you what it is. But because you felt it first, in your body. And someone told you its name, and said: “that, which you are feeling right now, that is called Love.” And you learnt to associate that word, with the feeling that you were having in your body, your inner state, so to speak. Similarly with grief, and joy and anger.

Could a machine understand these feelings? Could we teach a machine to learn these concepts?

These are very abstract, subjective concepts that don’t have clearly defined, objective representations. They are not something that can just be programmed into a computer.

So instead, I trained an AI model on what our subjective experience of them is. Or more specifically, what our collective consciousness thinks they look like, as archived in the cloud — as we like to call it — by the keepers of our collective consciousness.

I downloaded hundreds of thousands of images from the photo sharing website flickr, tagged with the words life, love, art, faith, ritual, worship, god, nature, universe, cosmos (and many more). And I trained a custom AI model on those images.

The result is a series of works that exist in various forms, ranging from short video works to large-scale multi-channel installations.

Given such a diverse dataset, I didn’t give the artificial neural network any image labels, i.e. semantic context required to be able to distinguish between different categories of images, between small or large; microscopic or galactic; organic or human-made. Without any of this semantic context, the network analyses and learns purely on surface aesthetics. Swarms of bacteria blend with clouds of nebula; oceanic waves become mountains; flowers become sunsets; blood cells become technical illustrations.

The images seen in the final work are not the images downloaded, but are generated from scratch from the fragments of memories in the depths of the neural network.

The model isn’t learning what these concepts are, it’s learning what we think they should look like.

Sound is generated by another artificial neural network using a custom architecture GranNMA which I trained on hours of religious and spiritual chants, prayers and rituals from around the world.

“We are all connected. To each other, biologically. To the earth, chemically. To the rest of the universe atomically.”
– Neil deGrasse Tyson

“The cosmos is within us. We are made of star-stuff. We are a way for the universe to know itself.”
– Carl Sagan

“How can we think in times of urgencies without the self-indulgent and self-fulfilling myths of apocalypse, when every fiber of our being is interlaced, even complicit, in the webs of processes that must somehow be engaged and repatterned? Recursively, whether we asked for it or not, the pattern is in our hands.
…
It matters what ideas we use to think other ideas with. It matters what matters we use to think other matters with. It matters what knots knot knots.
It matters what thoughts think thoughts. It matters what worlds world worlds”
– Donna Haraway

Research: Latent Storytelling & Narrative

The work is also an exploration into the use of Deep Generative Neural Networks as a medium for creative expression and story telling with meaningful human control over narrative. While the explorations of these so-called ‘latent spaces’ in generative neural networks are typically random, here, precise journeys are carefully constructed in these high dimensional spaces to create a narrative.

Some writing on the technical aspects:

Credits & Acknowledgments

Created during my PhD, funded by the EPSRC.

Visual network is a ProGAN.
Audio network is a custom architecture GranNMA.

Amongst many people, I’d like to especially thank Nina Miolane and Sylvain Calinon for their contributions and help with Riemannian Geometry, and Miolane et al for geomstats.

Series

More works in the Deep Meditations series.

Selected Exhibitions, Performances & Presentations(10 / 10)

Only selected shows with project pages are listed below. For more complete exhibition and performance history please see Show History.

Words(4 / 4)

Press(28 / 28)

Interviews(4 / 4)

Features(4 / 4)

Books(1 / 1)

Catalogs(3 / 3)

  • 2026  EMERGENCE, Kate Vass, Ágnes Ferenczi (eds.), Kate Vass Galerie, pp. 95–114 · Catalog
  • 2023  Contemporary Istanbul, 18th Edition — Catalogue, Contemporary Istanbul, pp. 129 · Catalog
  • 2020  Immaterial/Re-material: A Brief History of Computing Art, Jérôme Neutres (eds.), UCCA Center for Contemporary Art / Culture and Art Publishing House · Catalog ★

Other Coverage(6 / 6)

News(3 / 3)

Academic Papers(7 / 7)

Collections(1 / 1)

Show History(15 / 15)

Solo Exhibitions and Presentations(2 / 2)

  • 2024  Gallery QI, La Jolla, CA, USA, 25 Jan 2024 ★
  • 2020  Deep Meditations: A brief history of almost everything in 60 minutes, How We Make Meaning, QUAD Gallery, Derby, UK ★

Performances(1 / 1)

Group Exhibitions(12 / 12)