artificial

Daniel Ambrosi

​In 2011, I devised a unique form of computational photography that generates exceptionally immersive landscape images. My series "Dreamscapes" builds upon these previous experiments by adding a powerful new graphics tool to  my artistic workflow: an enhanced version of “DeepDream,” a computer vision program evolved from Google engineers’ desire to visualize the inner workings of Deep Learning artificial intelligence models. With proprietary access to a customized version of DeepDream expressly modified by two brilliant software engineers, Joseph Smarr (Google) and Chris Lamb (NVIDIA), to operate successfully on my giant images, I have been empowered to develop large scale artworks with highly intricate and surprising details.
 
My Grand Scale "Multi-Pass" Dreamscape Details investigate the possibilities of human-AI hybrid art by exploring multi-level "dreaming" effects. These works begin with a detail of one of my panoramic images to which multiple styles of neural network "hallucination" are applied at multiple scales. Unlike my previous "full scene" Dreamscapes, which appear completely photographic from a distance, these large works are clearly hallucinatory upon first impression, yet still contain intricate details that defy expectations.

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Double Arch Alcove - Grand Scale "Three-Pass" Detail. Image courtesy of the artist.

Double Arch Alcove - Grand Scale "Three-Pass" Detail (close up). Image courtesy of the artist.

"Ithaca Falls" Grand Scale "Two-Pass" detail (close up). Image courtesy of the artist.

"Ithaca Falls" Grand Scale "Two-Pass" detail. Image courtesy of the artist.

Daniel Ambrosi is recognized as one of the founding creators of the emerging AI art movement and is noted for the nuanced balance he achieves in human-AI hybrid art. Based near Silicon Valley in Half Moon Bay, California, Ambrosi has been exploring novel methods of visual presentation for almost 40 years since entering the Program of Computer Graphics at Cornell University where he earned a Bachelor of Architecture degree and a Masters in 3D Graphics. ​

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Mike Tyka

This series, titled "Portraits of Imaginary People," explores the latent space of human faces by training a neural network to imagine and then using it to depict portraits of people who don’t exist. To do so, many thousands of photographs of faces taken from Flickr are fed to a type of machine-learning program called a Generative Adversarial Network (GAN). GANs work by using two neural networks that play an adversarial game: one (the "Generator") tries to generate increasingly convincing output, while a second (the "Discriminator") tries to learn to distinguish real photos from the artificially generated ones. The two networks compete and through this process learn to imitate the learning data. Imaginary people are beginning to shape our thinking in the form of fake news spreading on social media and this work is a reflection on this development.
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"Jaclyn_Donahue" Neural net, digital. Image courtesy of the artist.

"khaledbakri7" Neural net, digital. Image courtesy of the artist.

"komarova6969" Neural net, digital. Image courtesy of the artist.

Mike Tyka's work has focused both on traditional sculpture and modern technology, such as 3D printing and artificial neural networks. In 2015 he created some of the first large-scale artworks using neural networks, such as Iterative DeepDream and co-founded the Artists and Machine Intelligence program at Google. In 2017 he collaborated with Refik Anadol to create a pioneering projection installation using Generative Adversarial Networks, "Archive Dreaming." His series "Portraits of Imaginary People" has been shown at ARS Electronica in Linz, Christie's in New York, and at the New Museum in Karuizawa, Japan. His kinetic, AI-driven sculpture "Us and Them" was featured at the 2018 Mediacity Biennale at the Seoul Museum of Art and in 2019 at the Mori Art Museum in Tokyo.

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Deirdre Barrett

My work is a collaboration between computer artificial intelligence (AI) and myself as a human artist. I begin with photographic elements collaged together. I give different pieces to different digital programs - including Deep Dream, MacFrac, and Puppet Morph - for them to alter with their distinctive algorithms. I then manually emphasize elements that are intriguing from a human perspective and revert ones that aren’t. I return it to the AI program for its reaction to my changes--repeating this 3-20 times for each element.

My own dreams inspired my current "Digital Dreams" series. Computer algorithms are perfect for evoking the dream world's fantastic entities and magical events - images that just can't be but which look so realistic that you don't question them at the time. The images in this series play with thin boundaries between the inanimate vs. sentient. Objects, animals, and humans in a dream can manifest the same traits, as they're all representations of our unconscious. My goal is for the viewer to experience a connection with the dream world as they catch a glimpse of one of my dream moments intertwined with the “dreaming” of the computer algorithm.
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"Charlie’s Kitchen" Image courtesy of the artist.

"Damp Disquiet" Image courtesy of the artist.

Deirdre Barrett, Ph.D. is a psychologist at Harvard where she teaches courses on dreams. She is the former president of IASD and The Society for Psychological Hypnosis. She has written five books including Pandemic Dreams and The Committee of Sleep, and she is the editor of four more including Trauma and Dreams. She is also Editor-in-Chief of IASD's journal, DREAMING. For the past four years, she has been making digital art based on her dreams, and is represented by Keep Contemporary Gallery in San Antonio. Her work has appeared in shows around the U.S. and won second place in The International Association for the Study of Dreams exhibition in 2017.

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Tristan Onek

My artwork is an extension of my research, which largely revolves around finding new ways to use artificial intelligence for creative problems. Although AI has often found itself being most popular in the mainstream media when applied to technology and business problems, it is my belief that there are also great opportunities in letting AI push the boundaries forward in the arts and humanities. I create programs that generate new artwork by taking in and reading materials such as poetry or literature, analyzing the provided material for its key concepts, and then creating artistic visualizations of those key concepts by merging images that correlate to those concepts. My only artistic tool that I use to create this art is my Python development environment where I design these programs. While I use a variety of books, poetry, and songs to create this art, I find that using materials from more radical figures leads to the most visually inspiring artwork. I therefore try to use a diverse pool of source materials ranging from Theodor Adorno to Vladimir Lenin to Maya Angelou and beyond. Each of these authors provide the necessary textual inspiration for my programs to generate new and unique artwork that often represents challenging and complex ideas. I seek to use my background in computer science to bring these authors and their ideas into an artistic context by using artificial intelligence so that I may ultimately spread awareness and inspiration alike.
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“Speculative” was created by Tristan Onek’s AI Aesthete program by analyzing Andrei Voznesensky’s poem entitled The Parabolic Ballad. This piece demonstrates what seems to be a statue beginning to form under a parabolic arch, although its features and purpose are not clear yet.

“Position” was created by Tristan Onek’s AI Aesthete program by analyzing the first chapter of Theodor Adorno’s book Aesthetic Theory, entitled Art, Society, Aesthetics. Just as Adorno explains how ‘nothing concerning art is self-evident anymore’, this piece demonstrates an image of a painting that is becoming distorted while other much fainter images begin to materialize on top of the existing artwork. The illusory imagery that is beginning to challenge the art has no theme or purpose, but neither part’s purpose is truly self-evident in any sense.

“Resolution” was created by Tristan Onek’s AI Aesthete program by analyzing the entirety of Søren Kierkegaard’s book entitled Either/Or: A Fragmented Life. Kierkegaard explains how people will regret any of the decisions before them, and not choosing to act on these decisions during a very finite lifetime leads to ‘double regret’ in which life is nothing but a series of painful choices. Overcoming this trap is necessary before the flower that is life wilts away into death.

​Tristan Onek is a computer science researcher, web developer, and digital artist. His work has recently focused on using AI and other computational methods to turn text-based media like poetry, musical lyrics, literature, and more into visual art. He created the AI Aesthete program during this research as a system that takes a wide range of media as input and analyzes its content to generate artwork by merging images scraped from the Internet which best represent that media. Aside from his personal scientific and artistic endeavors, he has also previously done separate work with East Tennessee State University and the University of Southern California. When not working or studying, Tristan spends considerable time traveling around the country discussing his activities at different academic events. Tristan recently finished his undergraduate studies at ETSU and is now working independently on different creative projects.

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