Digital prints on dibond
As a visual artist and software engineer, Sarin finds inspiration in unifying patterns of nature and computation. Her discovery of Generative Adversarial Networks (GANs) that reveal some of these patterns and reassemble them in intriguing ways changed her artistic process in dramatic way. The shift to working with Neural Networks from being an analog artist has been both challenging and exhilarating; what hasn’t changed though it the subject matter. She continued exploring still lifes and variations on masters. Jason Bailey had this to say about her AI art: “Much of Sarin’s work is modeled on food, flowers, vases, bottles, and other “bricolage,” as she calls it. Working from still lifes is a time-honored approach for artists exploring the potential of new tools and ideas.” Jer Thorp echoed:” Where a lot of AI-based art can feel like exploration into alien lands Sarin’s fondness for the quotidian gives her work a personality that feels very much part of the real world.”
In Sarin’s explorations of AI as a medium she decided to use her own datasets, of her drawings and photographs, suggesting that the AI artist’s intent is indeed in the training data for neural networks. Vis-àvis abstract nature of generated images, she then works carefully on image captioning, to give them additional (verbal) dimension,
Recently sensing how a lot of AI Art looks the same she coined the term postGANnism – the style in which Sarin added post processing using Python scripts and even analog assemblage to her AI art making pipeline. Ultimately she strives for her generative artwork to be not only interesting and aesthetically pleasing but to reflect the characteristics of her analog art – improvised, bold and deeply personal. Helena’s work does not stop at the visual, since it has tactile, olfactory qualities, it is purely sensory. Her sense of color, her variety of shapes and strokes, it all allows us to see everyday life with new eyes. This series of prints offers us a glimpse of the artist’s perceptions of the everyday live, always filtered by the gaze of the machine.
Visual artist and software engineer, Helena Sarin has always been working with cutting edge technologies, first at Bell Labs, designing commercial communication systems, and for the last few years as an independent consultant, developing computer vision software using deep learning. While she has always worked in tech, Helena has been doing commission work in watercolor and pastel as well as in the applied arts like fashion, food and drink styling and photography. But art and software ran as parallel tracks in her life, all her art being analog… until she discovered GANs (Generative Adversarial Networks). Since then generative models became her primary medium.
She is a frequent speaker at ML/AI conferences, for the past year delivering invited talks at MIT, Library of Congress, Adobe Research. Her artwork was exhibited at AI Art exhibitions in Zurich, Dubai, Oxford, Shanghai and Miami, and was featured in number of publications including the recent issue of “Art In America” magazine. She published an artist book “The Book of GANesis” that was immediately sold out and now working on “The Book of veGAN”
Generative deep learning involves training artificial neural networks (models) to be able to make new artefacts such as images, sounds and sentences. The training usually involves the model examining huge amounts of data, such as a large collection of images, which we call the data set. Artistic practice for many artists involves collecting this data in the hope that the trained model will generate new things which are beautiful, intriguing and surprising.