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Mario Klingemann

Mario Klingemann (a.k.a. Quasimondo) combines the analytic mind of a coder, the creative fervor of an artist, and a dash of mad scientist.


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Intro:

Klingemann is an award-winning artist and “skeptic with a curious mind,” whose preferred tools are neural networks, code and algorithms. He recently made headlines with the sale of his piece Memories of Passersby I, which was one of the first AI artworks bought in a traditional auction house (featured below). The art of that piece, he explains, is the code and system itself, rather than its continually evolving output on two screens - representing an important historical and conceptual landmark in the history of the art market.

Klingemann is driven by a deep desire to understand, question and subvert the inner workings of systems. He also has a deep interest in human perception and aesthetic theory. In order to surprise himself and his audience, Klingemann explores uncharted territories to discover unseen beauty and unthought ideas.

Klingemann’s interests are constantly evolving, encompassing artificial intelligence, deep learning, generative and evolutionary art, glitch art, data classification and visualization, and robotic installations.

His work is often inspired by overcoming limitations, and creatively repurposing and recombining objects and systems to reveal their hidden qualities. His creations have been exhibited in international art shows and won acclaim among critics as exemplary pieces of net art. Pieces like his Neural Network portraits, Lowpoly Bot, Mona Tweeta, ScribblerToo, Flickeur, or Dada Visualization have made their way into uncounted best-of lists and got featured in many articles.

In 2015 he won the Creative Award of the British Library, currently he is machine learning artist in residence at the Google Cultural Institute in Paris. Mario enjoys sharing his explorations and discoveries on design and technology conferences worldwide, has co-founded the Munich FabLab and is working as a freelance code artist building creative tools, mobile apps and media installations.

Selected AI projects:

1. Memories of Passersby I

Klingemann’s work Memories of Passersby I generates portraits in real-time using neural networks. It is a computer system hidden inside of an antique-looking piece of furniture, which looks like a cross between a midcentury modern cabinet and an old-fashioned radio.

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Klingemann says the art is not the images, which disappear, but the computer code that creates them. That makes it distinct from other pieces of AI art that have made it to auction–most of which consist of a single unchanging image generated by an algorithm.

The historic piece is a landmark in the history of AI Art because it is one of the first going up for auction in the traditional art market – and it is the algorithm itself that is the core of the piece. It’s expected to sell at Sotheby's for an estimated $50,000.

2. Neural Glitch

AI and computers have the ability to break us out of the confines of existing tradition. Klingemann explains:

"In the end, you are confined to what you have seen, heard or read, and it's very hard to glitch that. Some people take drugs to do that - to make even more absurd connections. But a machine enables you to forcefully provoke that. Because it's much easier to glitch, or bring off course, than a human brain. In the process of doing that often some interesting things happen which are unexpected."

To that end, Klingemann developed a technique he calls Neural Glitch.

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“Neural Glitch is a technique in which I manipulate fully trained GANs by randomly altering, deleting or exchanging their trained weights. Due to the complex structure of the neural architectures the glitches introduced this way occur on texture as well as on semantic levels which causes the models to misinterpret the input data in interesting ways, some of which could be interpreted as glimpses of autonomous creativity.”

3. pix2pix Experiments With Electron Microscopy

Klingemann applies deep learning techniques in an attempt to discover new forms of aesthetics - and blur the lines between human and machine creativity. He has used image-focused neural network architectures since the release of Deep Dream.

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Style transfer, ppgn, pix2pix and CycleGAN are architectures he has investigated and experimented with in an artistic context. Klingemann showed several of his “Neurographer” works at Ars Electronica 2017.

Klingemann is currently an Artist in Residence at Google Arts & Culture. He also helps institutions like the British Library, the Cardiff University or the New York Public Library with the processing and classification of their vast digital archives. He believes that his future creative agents will require a solid foundation of human knowledge to build upon.

Klingemann received the Artistic Award 2016 by the British Library Labs and won the Lumen Prize Gold 2018.

Klingemann on using artificial intelligence:

How has AI impacted your creative practice?

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What excites you most about AI as an artist?

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What specific AI / machine learning technologies does you use?

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