IRA GREENBERG: CRACKING THE CODE

Ira Greenberg: I need to go back to around 1979/1980, when a neighborhood friend’s dad, a professor at the local university, brought home a computer. My friend and I spent hours playing early text based games (e.g. Zork). This friend was a true genius, so it was fun exploring that magic box together. Though it would be about a decade before I began using a computer explicitly for creative work, that sense of awe about the machine never left.

In 1992, upon graduating with my MFA in painting and having a pretty major first teaching job failure, an uncle suggested I look into computer graphics. I rented a Mac, got some free early Adobe pirated software and aftermarket books, and spent about two months teaching myself to do desktop publishing. This rather quickly led to paying work and an unexpected level of expertise. It helped that no one else really knew what they were doing, and I realized I was good at teaching myself this stuff. The truth is, I loved reading the early computer graphics manuals so much that I found it a little disturbing. I was supposed to be a painter.

IG: The more I learned, the deeper I wanted to go. I think my painting background, which is exclusively observational, drove this impulse. It felt like I was trying to get to the fundamental materiality of the machine, to the computation itself. After moving through all aspects of applied computer graphics and some basic scripting, I knew I had to learn to code and refresh my math knowledge. So I went back to the manuals and began a very deep dive, teaching myself languages like Lingo, ActionScript, and Java. I also quickly realized that the programming manuals weren’t good and were not written for people like me, who lacked the ability to follow rules.

Once I got to the code, I found something akin to paint and charcoal, and I was able to map my creative practice to computation, less as an applied tool but more as a generative medium.

IG: I guess I have always been too egocentric and impulsive to ever question whether what I wanted to do was realistic or even remotely possible. Even when I studied painting, it quickly became, "How can I make paintings to hang next to Titian, Rembrandt, Cezanne, etc.”

I tend to be attracted to finding and hitting limits. As a middle-aged ice hockey player, that included tearing ligaments, tendons, and muscles. With my creative practice, it was finding a way to support my family while doing the work I wanted to do without compromising.

Even back when I was an undergraduate, I realized that I couldn’t work for someone and that I wanted to be able to study the things that interested me on my schedule. I looked at my art professors as a 20-year-old, and they seemed to have a great life, so I decided that’s how I’d pay the bills. No one told me at the time how hard it was to land a tenure-track art position.

IG: For the most part, this model of academic patronage has worked for me. I was pretty good at prioritizing my creative research, and as I got more involved in computation, art departments were actively seeking this skill and experience. It helped me outcompete nearly all of my peers; in many ways, it was just dumb luck that I picked something of utility to learn. Of course, there was very little utility I was actually using computation for.

This state has pretty much been my career for a couple decades now. There were some well-received Processing books, national grants, and forays across disciplines (CS, Data Science), and I built a center around creative computation, but what I never really explored was the art world and art market. I had an early experience, right out of grad school, with Bowery Gallery in NYC, but I found the experience mostly negative at the time.

IG: Beginning about five years ago, I began to wonder about something beyond academia. For the first time in my career, I imagined a life fully devoted to my practice. Nothing really changed though for a while, until the NFT space took off, really the generative art NFT space. One day, an ex-student showed me Art Blocks and said, "Hey, this is what you taught us”. It was startling to see the interest in the work and money that people were spending for digital files, work that some of us were doing 20 years earlier as pure art research exploration with no prospect of earning any money from it.

The generative NFT space has reinvigorated my passion for creative coding. I’ve found a similar excitement in what’s happening in the generative AI space. It’s been fun engaging with a new generation of artists and students passionate about learning to code as a creative medium. And it’s honestly been very rewarding to sell a fair amount of art, something that I never really saw a path toward when I began the art journey.

IG: Though I’ve been able to develop a creative practice working across drawing and painting and creative computation, it hasn’t been a smooth journey. For many years, I felt torn between painting and coding. Aside from the practices being so different, the communities were also completely distinct. I will always have a deep, almost religious, reverence for painting; it really is what set me free as a young person. The most spiritual moments in my life have probably been standing in front of paintings in major museums.

Coding is something I’m good at and is also very natural for me. I find the practice somewhat meditative, but I don’t have the same deep reverence for code that I do for painting. It may be because there’s not much history or heroes or icons there that I aspired to be like or learn from; it was pretty much a blank slate when I started.

I spent many years wrestling with this bifurcation in my practice. It would usually amount to intense periods of painting and coding, but almost never concurrent practices. While I was in these intense periods, I found myself engaging with the different communities, almost like two separate families. Eventually, I found a limit here as well, where I almost lost all interest in my practice, with no sense of clear direction or connection. It took a trip overseas and some wandering around a new city to begin the process again through some simple drawing.

I began to wonder how my years of computation had changed me and how that experience could inform my drawing and painting. For most of my career, I was searching for materiality in computation. I used to say I was trying to figure out how to ‘make code drip'. I hadn’t asked myself how algorithms could influence my drawing or painting. I began to think of drawing as an embodiment of algorithms and shifted my material practice from observation to automatic. This led to an explosion of new work and investigations.

Most of this automatic work occurs at an unconscious level, where I create random fields of marks and then begin excavating structures and (sometimes) narratives of what begins to reveal itself to me. I try not to judge or direct the work too early. If I do, it often feels too contrived and less surprising. In many ways, I’m still doing observational work, but the motif reveals itself in real-time directly in the work. There is also a fascinating correlation with this automatic process and diffusion in AI, my most recent obsession.

So I began to think there was no longer a difference between my bodies of work; both were generative and emergent, and so I needed a new way of describing this integration. Post-computationa’ is what I came up with.

IG: ‘Generative’ for me signifies parameterized randomization. Emergence is a by-product of a generative process. The parameterization – the really stratified parameterization – is where the creative expression resides. Back in 2003, when I first created Protobytes, I realized I could use code, math, and randomization to create distinct creatures. It was one of my first experiences, in a sense, drawing with code like I was drawing with charcoal. Rather than creating random geometry, marks, and other visual artifacts defined by computational drawing methods, I was leveraging the computation more as a collaborator than a supplicant to create something more integrated.

I spent most of my career exploring this human-machine collaborative and creative space. Though I have taught and coded many popular algorithmic phenomena, e.g., cellular automata, L-systems, fractals, grids, etc., I’ve always been compelled to find something less computational through the computation. The NFT space has created an explosion of practice and interest in geometric and algorithmic explorations of form, pattern, fields, etc. Art Blocks, with their on-chain limitations, has perhaps become the pantheon for this type of work.

So for me, there is something historical about much of this generative NFT work. Some of it is extraordinary, so I don’t mean to criticize it at all; it’s just territory that some of us explored a while back. Though there are certainly many people now doing it better than we ever did.

IG: My practice has changed most dramatically with the introduction of Stable Diffusion. My generative art drops on fxhash were less new territory for me. Though the dynamics of putting work into a marketplace were very new to me, I did quickly realize that the collector base and even many of the other artists were different from back in the early Flash and Processing days. My initial projects on fxhash were fairly complex computationally. I tend to code most things from scratch, so all the physics is generally hand-coded without the use of a physics library, and I like to push each project a little further to challenge myself.

What I saw over time was less engagement in the marketplace with some of the more complex work. Back in the early days, the only people who really hacked around with this stuff had pretty developed coding chops, so there was an appreciation for complexity in the code and execution. We certainly cared about formal design aesthetics, but it was more at the service of creative coding aesthetics and pushing the technical envelope.

IG: When I first began playing with Stable Diffusion, it blew my mind. Less so because it could produce very realistic things, but much more so because of how generative it was. I fed some of my drawings into it, and what it produced were incredible variations. The drawings, though automatic and not based on any specific motif or model, were figurative and informed by my interest in early Renaissance painting. The variations the AI produced taught me things about the work, such as new or alternative forms, figures, and spaces that could exist in the drawings. Because I included some of my heroes, Piero della Francesca, Andrea Mantegna, and Giovanni Bellini, in the text prompt, the output also felt like it transported me back in time to the early fifteenth century.

Stable Diffusion has felt like a technology I was waiting to be invented for 20 years. It perfectly combines my fascination with drawing and painting with generativity. I’ve been greatly enjoying doing both short and long-form drops with the work, and honestly, if not for market dynamics, I would probably be releasing multiple pieces every day. I feel like I have years of pent-up work inside me to release.

IG: GLOMULARUS extends my Protobyte work using three.js. I wanted my first fxhash piece to be noticed. One of the challenges of being a little older than the typical web artist and being away from Twitter since the Trump administration came to power was having my work be found on a very active platform. I wasn’t sure if my history would mean much within the community. Even my experience with Processing was pretty dated; nearly everyone, especially in Web3, now uses P5. I put a fair amount of engineering into GLOMULARUS to enable both the visual impact and also the performance. I was really happy when it came out pretty quickly.

IG: Yes, it’s actually pretty ironic that I kicked off the platform with a PFP project, which it definitely is. I was, early on, a passionate detractor of the whole PFP, pseudonymous meme culture. I realize now that I didn't really get it. I didn’t set out to make the Oracles a PFP, but it just went there, and I embraced it. I’ve come to realize that PFP culture is more about community and support than fraud and rugpulling, though there are both, of course.

IG: It’s just where my heart is in painting, especially over the last decade. I was really lucky to see the Mantegna and Bellini show at the National Gallery in 2018. There is something about the work produced during transitional periods that speaks to me. You see it in the period between the middle ages and the early Renaissance in Giotto, Masaccio, Mantegna, etc. The work has a charged tension that you don’t quite see in high Renaissance work, where the artists are perhaps in more control and showing off. There is a will and determination driving the work during transitional periods that is extremely moving. You see it in Cezanne and early Cubism, as well as later in Abstract Expressionism, in painters like De Kooning, Hofmann, and Mitchell. This somehow feels akin to the period we’re living in now, where technology is slowly getting more deeply integrated, but we’re still distinct from it, with an interesting tension between the fear of the unknown and a compulsion to embrace or absorb it.

IG: NFTs have shown me the potential of a more integrated path. I never thought I’d be able to put together my passion and practice with ‘any’ real compensation. I always assumed it would require too much compromise or sacrifice.

The NFT space has also taught me to be more expansive and inclusive in my thinking about art. My painting education was very narrow and, I imagine, not all that different from going to seminary to become a priest. It was a highly specialized education and subculture, requiring an unspoken commitment to asceticism or being thought of as a sell-out. And anyone making work outside of these strict bounds was dismissed.

IG: It’s all about coding literacy. Until I learned to properly code, I was hacking at things and not able to directly touch the material of computation. It’s like living in a foreign country and never developing fluency in the native tongue. Historically, in digital art programs, students never developed coding literacy, mostly because there was no one to teach them. Part of the reason I wrote the first Processing book was to try to improve this situation. I tried to write a book that spoke to artists and showed them both a path to coding literacy and why it’s worth taking the time to develop it.

IG: For me personally, the best version of AI may have already been developed. Already there are new versions of Stable Diffusion that I like less than the earlier ones. The problems engineers and developers are trying to solve in AI will likely bring greater uniformity and predictability. From an engineering and product perspective, this makes sense. However, as a chaotic, generative medium for creative practice, it’s highly problematic. Twenty years ago, some of us began coding to subvert the software application interface and error correction algorithms (undo/redo). These software innovations eliminated generative and expressive potential (human creative innovations).

In my experience, humans are most creative when they are improvising and solving problems with some risk or loss involved. When you can undo or redo ad nauseam or be assured that every AI hand will have five perfectly formed fingers, that risk goes away, as does the chance to synthesize new, original solutions.

In regard to "normal and common," I wouldn’t be surprised if more people are already making art with AI than with paint.