ƈօʍքʊȶǟȶɨօռǟʟ Aʀȶɨֆȶ; AI wrangler; curious philomath;
speculative simulation & data dramatization;
PhD in artificial intelligence × expressive human-machine interaction;
Assistant Professor @ UCSD Visual Arts;
Works | Bio | Statement | PhD Research | Awards | Juries | Collections | Publications | Shows | Talks | Press | Education
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… about my current (circa 2018/2019) motivations (spanning #ritual #algorithm #consciousness #life #empathy #meaning #artificialintelligence #waves #gods #weareallconnected) [project page]
b. Istanbul, TR, 1975
Memo Akten is a multi-disciplinary artist, experimental filmmaker, musician and computer scientist from Istanbul, Turkey. He works with emerging technologies and computation as a medium, to create images, sounds, films, large-scale responsive installations and performances. Fascinated by trying to understand the nature of nature and the human condition, he draws from fields such as biological and artificial intelligence, computational creativity, consciousness, neuroscience, physics, biology, ecology, philosophy, ritual and religion. He has a PhD in Artificial Intelligence and expressive human-machine interaction from Goldsmiths University of London, and is Assistant Professor of Computational / New Media Art at University of California, San Diego (UCSD). Akten is a frequent keynote speaker on topics involving art, science, technology and culture. As part of his PhD, he specializes in expressive human-machine interaction and creative explorations of Artificial Intelligence, and in this field he is considered one of the world’s leading pioneers.
Akten received the Prix Ars Electronica Golden Nica – one of the most prestigious awards in Media Art – for his work ‘Forms’ in 2013. His work has been shown internationally at exhibitions such as The Grand Palais’s “Artistes & Robots” in 2018 (Paris FR), The Barbican’s “More than human” in 2017 (London UK), the Victoria & Albert Museum’s landmark “Decode” exhibition in 2009 (London UK), and venues such as the Moscow Museum of Modern Art (Moscow RU), Shanghai Ming Contemporary Art Museum (Shanghai CN), Mori Art Museum (Tokyo JP), Royal Opera House (London UK) and many others. He has collaborated with celebrities such as Lenny Kravitz, U2, Depeche Mode and Professor Richard Dawkins; and brands including Google, Apple, Twitter, Deutsche Bank and Sony PlayStation. Akten’s work is in numerous public and private collections around the world. He has served as mentor and jury on numerous international awards, residencies and conferences such as Ars Electronica, Google Arts and Culture, and SIGGRAPH.
In 2007 Akten founded The Mega Super Awesome Visuals Company (MSA Visuals), a creative studio spanning art and technology. In 2011, with two new partners this evolved into Marshmallow Laser Feast (MLF). In 2014, after a string of hugely successful, influential and large scale projects, Memo left MLF to pursue his PhD and focus on personal work, collaborations and research. In 2020 he joined the UC San Diego Visual Arts Faculty.
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Akten received the Prix Ars Electronica Golden Nica for his work ‘Forms’ in 2013. He has exhibited and performed internationally at venues such as The Grand Palais (Paris FR), The Barbican (London UK), Victoria & Albert Museum, Moscow Museum of Modern Art (Moscow RU), Shanghai Ming Contemporary Art Museum (Shanghai CN) and many others. He has also collaborated with celebrities such as Lenny Kravitz, U2, Depeche Mode and Professor Richard Dawkins.
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Akten received the Prix Ars Electronica Golden Nica for his work ‘Forms’ in 2013 and has exhibited and performed internationally. He has also collaborated with celebrities such as Lenny Kravitz, U2, Depeche Mode and Professor Richard Dawkins.
(actually more of a work-in-progress brain dump than a statement, but you get the idea)
I’m an artist, musician and researcher working with emerging technologies – particularly software, algorithms and computation – as a medium.
These days I’m mostly thinking about the tensions and intersections between science and spirituality. Or to be more precise, the collisions between nature, science, technology, ethics, ritual, tradition and religion; especially in the context of the current ecological collapse, social and political polarizations, moral crises and technological submission.
My biggest inspiration is nature, and the nature of nature. I don’t just mean forests and flowers etc. – though that too of course – but the underlying processes that give rise to everything that happens around – and inside – us. On one level, the fundamental questions that drive me are the same questions that have been asked for thousands of years. What is the nature of the universe? What is the nature of life? What is the nature of the mind? Drawing from fields such as physics, biology, abiogenesis, evolution, neuroscience, psychology, philosophy, sociology, anthropology, history, and theology, I study the hidden processes that shape our world, and I develop systems that abstract behavior, hoping to create unfamiliar familiarities and encourage new perceptions.
Analogous to painting a sunset on a stormy sea, I’m fueled by the idea of studying the nuclear fusion inside the sun powering our planet, the photons scattering in the atmosphere to create a crimson sky, the fluid dynamics driving the wind and the waves crashing onto the shore. As opposed to taking inspiration directly from the observable aesthetics of what I see around me, I’m inspired by the processes and behaviour that create and shape them. And I’m inspired by our capacity to dig deeper and learn more about the poetry of nature.
My craft, so to speak, is that I write software – I design systems that abstract behavior. One crucial aspect of these systems that I’ve always been very interested in, is exploring interactive, realtime, computational systems to enhance artistic, creative expression. Here the emphasis is on realtime and interactive. In other words, systems that enable you to expressively create, manipulate and perform images and sound. Analogous to playing a musical instrument, like a piano, where there’s an immediate creative feedback loop between the user and the system. In fact, from a cybernetics or control systems theory point of view we can liken this to continuous control, but with emphasis on expressivity. Photoshop, or Maya, as powerful as they are, do not fall into this category. Playing a piano does. Furthermore, a lot of my work also falls into the field known as expanded animation. Breaking away from a 2D screen, exploring ways of augmenting and hacking physical space.
Alongside my practice, I have completed a PhD in Artificial Intelligence (AI) – or to be more precise: Deep Learning (ML) – and expressive human-machine interaction. As well as technical (Computer Science) perspectives, I’m equally (if not more) interested in the cultural, social, ethical, legal, philosophical and religious implications of the recent and ongoing developments in AI. (More on this in the following section)
I’m delighted to learn that Leonardo, the prestigious peer-reviewed journal focusing on the intersections of art, science and technology, has selected my thesis abstract to be amongst their highest-rated, and to be published in their October 2022 issue (Vol 55, No 5). https://leonardo.info/labs-2021
Thesis can be downloaded from https://research.gold.ac.uk/id/eprint/30191/
Completed in the Department of Computing, Goldsmiths University of London; under the supervision of Dr. Mick Grierson and Dr. Rebecca Fiebrink; funded by the EPSRC.
Deep Visual Instruments: Realtime Continuous, Meaningful Human Control over Deep Neural Networks for creative expression
In this thesis, we investigate Deep Learning models as an artistic medium for new modes of performative, creative expression. We call these Deep Visual Instruments: realtime interactive generative systems that exploit and leverage the capabilities of state-of-the-art Deep Neural Networks (DNN), while allowing Meaningful Human Control, in a Realtime Continuous manner.
We characterise Meaningful Human Control in terms of intent, predictability, and accountability; and Realtime Continuous Control with regards to its capacity for performative interaction with immediate feedback, enhancing goal-less exploration. The capabilities of DNNs that we are looking to exploit and leverage in this manner, are their ability to learn hierarchical representations modelling highly complex, real-world data such as images. Thinking of DNNs as tools that extract useful information from massive amounts of Big Data, we investigate ways in which we can navigate and explore what useful information a DNN has learnt, and how we can meaningfully use such a model in the production of artistic and creative works, in a performative, expressive manner.
We present five studies that approach this from different but complementary angles. These include: a collaborative, generative sketching application using MCTS and discriminative CNNs;
a system to gesturally conduct the realtime generation of text in different styles using an ensemble of LSTM RNNs; a performative tool that allows for the manipulation of hyperparameters in realtime while a Convolutional VAE trains on a live camera feed; a live video feed processing software that allows for digital puppetry and augmented drawing; and a method that allows for long-form story telling within a generative model’s latent space with meaningful control over the narrative.
We frame our research with the realtime, performative expression provided by musical instruments as a metaphor, in which we think of these systems as not used by a user, but played by a performer.
This research investigates how the latest developments in Machine Learning – with an emphasis on Deep Learning – can be used to create intelligent systems that enhance artistic expression. These are systems that people can interact with and gesturally ‘conduct’ to expressively produce and manipulate text, images and sounds – in effect, collaborating with a ‘creative’, ‘talented’ agent. These systems learn – both offline and online – and have a level of autonomy that could be perceived as creative behaviour.
The desired relationship between human and machine (software) here is analogous to that between an Art Director and graphic designer, film director and video editor, concept / story teller and ghost writer – i.e. a visionary communicates their vision to a ‘doer’ who produces the actual output under the direction of the visionary (though often the doer also shapes the output with their own vision and skills). Crucially, the desired human-machine relationship here also draws inspirations from that between a pianist and piano, a conductor and orchestra, an abstract expressionist painter and the system comprising of brush+paint+canvas+gravity+fluid dynamics. I.e. again a visionary (human) communicates their vision to a system which produces the actual output, but this communication is real-time, continuous and expressive; it’s an immediate response to everything that has been produced so far, creating a closed feedback loop.
Within this very broad topic, the key problem area that the research tackles is as follows: Given a very large corpus of example data (e.g. thousands or millions of examples), we can train a generative deep model. That model will hopefully learn something, and contain some kind of ‘knowledge’ about the data (and its underlying structure). The questions are: i) What exactly has the model learned? how can we investigate what knowledge the model contains? ii) how can we do this interactively and in real-time, and expressively explore the knowledge that the model contains iii) how can we use this to steer the model to produce not just anything that resembles the training data, but what *we* want it to produce, *when* we want it to produce it, again in real-time and through expressive, continuous interaction and control.
I try to keep a copy of all papers also on arxiv.org and non peer-reviewed (more speculative) articles at memo.tv/texts/