Can you understand an artist by rebuilding their process?
Over the last few years I’ve been experimenting with Processing and Java to create generative artwork. Most projects have explored modern computing power, real-time animation and increasingly complex systems.
This project is different.
Rather than asking “What can today’s computers do?” I wanted to ask:
“What could have been achieved with the mathematical thinking available in the 1960s?”
That naturally led me to the pioneering work of Vera Molnár.
Looking backwards instead of forwards
Vera Molnár is recognised as one of the earliest artists to embrace computers as a creative partner. Long before generative art became fashionable, she was exploring systems, rules and controlled randomness.
What’s remarkable is that many of her ideas existed before she even had regular access to a computer.
She imagined what she called an “imaginary machine”—a conceptual computer capable of carrying out simple instructions repeatedly. When computers eventually became available, they simply became another tool for testing those ideas.
Looking through her work, it’s easy to become distracted by the finished images.
What interests me more is the thinking behind them.
This isn’t about copying
The intention isn’t to reproduce Vera Molnár’s artwork.
Instead, it’s an attempt to understand the constraints she worked within.
Today’s software makes almost everything effortless:
- millions of calculations every second
- unlimited colours
- complex animation
- advanced rendering
- countless libraries
Removing those luxuries forces different decisions.
For this series I’ll deliberately restrict myself to:
- Basic geometric shapes
- Straight lines
- Simple transformations
- Repetition
- Small amounts of controlled randomness
- Elementary mathematics
- Black and white compositions
- A3 portrait layouts
Every project will be written in Processing using Java.
Not because it’s historically accurate, but because it allows me to think algorithmically without unnecessary complexity.
Designing with limitations
One thing that becomes obvious very quickly is that limitations are surprisingly creative.
Instead of asking:
“What should I draw?”
the question becomes
“What simple rule should I write?”
A square becomes interesting once it’s repeated.
A line becomes interesting once it’s rotated.
A grid becomes interesting once every element breaks the rules slightly.
Tiny mathematical changes produce surprisingly rich compositions.
Thinking like an early computer
Modern generative artists often build systems with noise functions, particle engines, physics simulations and GPU shaders.
For this project I’m intentionally avoiding most of that.
Instead I’ll explore ideas that feel closer to the computational mindset of the 1960s:
- Regular grids
- Rotation
- Translation
- Scaling
- Sequential plotting
- Iteration
- Random number generation
- Permutation
- Probability
- Simple geometric relationships
Almost every image should be explainable in a few lines of mathematics.
A study rather than a tribute
I’m treating this as a research project.
Each artwork will begin with a question.
What happens if every square rotates by one degree more than its neighbour?
What if a perfect grid slowly loses its precision?
How much randomness is enough before order disappears?
Those questions feel far more interesting than chasing a particular visual style.
Hopefully, by rebuilding these ideas from first principles, I’ll gain a deeper appreciation of why Vera Molnár’s work remains so influential today.
The series
Over the coming weeks I’ll be creating a collection of A3 portrait artworks, each exploring a single mathematical idea.
Every piece will be generated entirely in Processing using Java and deliberately limited to the simplest possible visual language.
No textures.
No gradients.
No effects.
Just mathematics, repetition and controlled variation.
Sometimes the simplest rules produce the richest results.
That’s a lesson Vera Molnár understood more than sixty years ago—and one that’s still worth exploring today.