INTERVIEW
by Jordan Kantor
•
13 Feb 2023
Laya Mathikshara was born and raised in Chennai, India. She is a fifteen-year-old digital artist, who currently attends high school. Mathikshara’s creative expression began in traditional art forms, however she began to explore creative coding during the Covid-19 pandemic. In addition to her work in generative art, she uses 3D and virtual reality programming to explore the interdisciplinary intersection of art, technology, and science.
Santiago was born in Barcelona, Spain in 1982, in the heyday of personal computing and the emergence of video games. This coincidence of biography and cultural evolution led to his fascination with technologically derived aesthetics. Santiago’s work utilizes code as a creative driver. He employs mathematical principles, physic simulations, genetic algorithms, and AI to manipulate machine-interpretable routines. Santiago regards coding as a form of transhumanistic poetry, a common ground between humans and machines, and his creative work centers around questions of technology’s synthetic nature, relation to society, and role in the evolution of the human species.
Laya Mathikshara: I was born, raised, and still live in Chennai, a city suffused with culture and tradition. It is considered to be the home of various art forms, ranging from Bharatanatyam dance to Tanjore paintings. Being very closely attached to the Tamil tradition, I have always had an interest in art. When the pandemic happened, what had been interests developed into concrete traits and habits. I found it incredibly life-changing in a lot of aspects—both positive and negative. When I was thirteen years old, I started pursuing my passion for art through digital forms. I absolutely enjoyed being an artist. As a school-going student, I gained a deeper exposure to technological tools through school activities and clubs. As my interest in tech grew bigger, I began mixing it with art. I really enjoy exploring the possibilities I see at the intersection of art and tech.
Santiago: Sure. At the beginning of my career, I considered myself more of an artisan. In a way, the passion and dedication for my craft were the main drivers of my artworks and their purpose of existence. As my work has developed, I have recognized that the concept of time has emerged as a central and recurring subject. Although this might not be present in Cerebellum per se, in my solo work I try treat time in the way the Romantic artists treated nature: as research into the sublime, exposing the juxtaposition of the subjective (emotion) and objective (an observable but often unsurmountable reality).
As for digital art, I’ve been exploring the generative medium since I started designing, fifteen years ago. I am fascinated by the expressive visual richness that coding affords. As my practice has evolved, I have transitioned from thinking of my work as a design service to an art product, always maintaining my procedural or generative approaches.
LM: As I mentioned before, during the pandemic, I began exploring digital art just as a hobby. I specifically choose 3D animation, as I found it highly interesting to simulate and make impossible things come true. I started with Blender, by watching courses and tutorials online. As my interest in 3D continued to grow, I slowly began exploring different tools. Simultaneously, my exposure to tech caught my interest, and when I began mixing them, the world of computational art opened up for me.
S: In fact, I discovered the blockchain as a medium for art through Art Blocks. I was interested in finding a way to reinforce the idea of code itself being art, which led me to learn about on-chain art specifically, and ultimately to Art Blocks!
LM: For me personally, the concept of ownership on the blockchain and the authenticity that it provides caught my attention, and made me feel it is a medium of art.
LM: I’ve always been a fan of Santi’s work. I’ve been following him on Instagram for a while. I had the idea of using reinforcement learning on-chain and some basic visuals. His style of work seemed like a perfect fit for this idea—beyond perfect. So I reached out, and the journey began almost a year ago …
S: Laya reached out with the idea of using Andrej Karpathy’s ConvNetJS library to create an artwork based on an artificial neural network. We experimented with several formal approaches, until we decided the final form of Cerebellum. Finally, we took the daunting task of porting that insanely large codebase into something “blockchain digestible.”
LM: I am quite proud to say that one of my works was featured this past winter in the Refraction Festival as part of Miami Art Week in 2022.
S: For my part, last year I gave myself the chance to dedicate fully to my art practice and dig deeper into the blockchain. I published the two collections you mentioned above with Art Blocks, and another with Gen.art (≈ 3000). In the physical world, I also had the opportunity to exhibit an installation entitled The Spectacle of Society at Gray Area in San Francisco.
S: Cerebellum is a multi-layered project. We believe it is one of the first on-chain pieces that is driven by a neural network. It is astonishing and mesmerizing in equal measure to observe how the network evolves, producing different movement flows through the visual components that comprise each piece. At a moment where AI based/derived art is increasingly gaining exposure, Cerebellum exposes the learning process, which, in a way, is similar to the building blocks with which this new “AI art” is being created.
LM: I would also like to highlight the fact that this is one of the very few works (and if I am not wrong, the only work on Art Blocks) made with reinforcement learning and 3D visualization along with aspects like intractability and dynamicity. I personally feel that the combination of all these aspects, with a touch of creativity, makes this work special. :)
S: Yes. Cerebellum works on several visual layers. The lowest layer is a constantly evolving neural network being trained via Q-learning. On top of that fundamental layer, several visualization systems act as “windows,” providing a view into this black-boxed learning process. The compositions of different Cerebellum outputs will be quite diverse and affected by how each piece’s network evolves over time, based on intrinsic parameters of the piece’s agent. Cerebellum is also highly interactive, allowing the viewer to re-compose the windows by dragging them or using key commands to visualize different aspects of the piece. There is even a 3D view! :)
LM: I would recommend the viewers to look for themselves in the art. That’s us, it’s you and me. We explore; we exploit. We learn from mistakes, but we also try to learn the pattern to avoid mistakes and just hit success most of the time. That’s precisely what our art is trying to do. It’s modeling us, on-chain; permanently, immutably. A seemingly random motion that has a meaning and story for every move it makes. Viewing our art through the various lenses makes the motion visually appealing in different ways.
LM: I’d say: enjoy the motion of an AI agent going from a “baby” (not knowing anything) to an “adult” with the best optimal strategy to navigate life.
S: It is very interesting to play around with the keyboard’s “t” toggle, which alternates between the network training and trained states. If left alone over time, the movement that drives Cerebellum will become more smooth, sophisticated, and effective at navigating space, deriving simultaneously into cleaner and more subtle flows into its set of visualization layers.
Santiago
Website: proper-code.com
Instagram: @____santi____
Twitter: @glitch_life
Laya Mathikshara
Website: layamathikshara.com
Instagram: @layamathikshara
Twitter: @layamathikshara
Linkedin: linkedin.com/in/layamathikshara