Generative Art

Generative Art is a process of algorithmically generating new ideas, forms, shapes, colors or patterns. First, you create rules that provide boundaries for the creation process. Then a computer (or less commonly a human) follows those rules to produce new works. Generative art is performed by mathematical algorithms that were written by the artist. And the role of the artist is to create an autonomous system and define algorithms according to which, the Art is being created.

In contrast to traditional artists who may spend days or even months exploring one idea, generative code artists use computers to generate thousands of ideas in milliseconds. Generative artists leverage modern processing power to invent new aesthetics – instructing programs to run within a set of artistic constraints, and guiding the process to a desired result. This method vastly reduces the exploratory phase in art and design, and often leads to surprising and sophisticated new ideas.

This Generative 101 example is Kaleidoscope. The person is controlling the visual, but the algorithm has been created beforehand and adhere mathematical theory of chaos.

The difference between traditional art also known as “manual” art, is the artist is working on the piece itself and artist is the sole creator of the work. Each piece is controlled by artist. Only the artist is responsible for the work.

In generative art — the beauty lies in building a system, a third force that dominates the Artist and the work itself. The artist is “painting” the formula according to which a detail extends to numerous details and transforms into a completed piece of work. Unique characteristics of a piece are written in an algorithm.

Generative Art by Frederik Vanhoutte: Creative coder, generative geometrist, medical radiation physicist refers to his generative art as  #Processing #CreativeCoding #GenerativeGeometry #NFT #CryptoArt | Follow Fredrik on Twitter

“Generative art is the ceding of control by the artist to an autonomous system. With the inclusion of such systems as symmetry, pattern, and tiling one can view generative art as being old as art itself. This view of generative art also includes 20th century chance procedures as used by Cage, Burroughs, Ellsworth, Duchamp, and others.” – Cecilia Di Chio from the book Applications of Evolutionary Computation.

Anders Hoff (a.k.a. inconvergent on Twitter) is a generative artist who is fascinated by patterns. He often finds it useful to start with a highly organized structure and to then look for ways to gradually disrupt it. Hoff says interesting results can often be found between the initial organized structure and the chaotic end result. He searches for enough order to be recognizable and enough chaos to break out of ordinary forms.

The Nature of Generative Art

I’ve always wondered what inspires intention and invention.  For many generative artists like me, we love to get back to the basics of visualizing spaceship earth, it’s natural forms, living organisms, trillions of interactions of molecules. Spaceship earth’s system is in constant movement and interaction between each other, strictly following the rules of the nature.

All natural phenomena — rain, snow, fire. They are all meant to be seen as random and chaotic, but they are all working altogether in constant change and interaction. Generative art is meant to be in constant change, to be an everlasting novelty. And one could interact with the visual using whatever sources — light, sound, spatial position of the physical objects. It’s information, for our art.

Tremendous number of living organisms use sound to communicate or exchange information. We can also connect it to our visuals and encounter the immediate changes. For example, depending whether the sound frequency is low or high, the visual lines might go up or down. That’s the most basic example, and you could only imagine how complicated the work could be if it takes each detail to account.

It is evident that the founding mothers of generative art tech have replicated the magic in the nature, evident in the force of our planet. The current generative art movement might be the closest thing to nature. I believe each of us is bringing back this unbroken interaction from the nature world.

The Practical Application of Generative Art

Today generative art has met commercial success in four areas:(1) Video games and gaming engines. Generative art is used to simultaneously generate and optimize images in real time in scenario based games. This is achieved by using rules based algorithmic art (code) that predicts the behavior of the images like landscapes. (2) Virtual Reality and 3 Dimensional environments. In film, Disney’s The Mandalorian, used a generative art gaming engine that produced stunning locations for it’s virtual production. (3) Augmented reality and visual projections in light design are being used and applied in theaters, museums and concerts. (4) Architecture-based mapping. Computation-based approaches in design have emerged in the last decades and rapidly became popular among architects e.g. Zaha Hadid Architects. The new expressions continue to grow at a race and pace that is disrupting the business models in commercial art.

Generative Art & Algorithmic Art

Many have asked what is the difference between Generative art and Algorithmic art?  Algorithmic art is a subset of generative art and is related by systems theory. The final output of algorithmic art is typically displayed on a computer monitor, printed with a raster-type printer, or drawn using a plotter.  Algorithmic art is also sometimes called code art or procedural art, because it is created by computer following a set of procedures laid out in code.

Algorithmic art dates back to the early 1940s by researchers at ENIAC, Bell Labs and GRAV who were pioneering the use of computers for creativity. Researchers like Michael Noll and Vera Molnár envisioned a new breed of artist-computer scientist. Today that vision has been realized.

Algorithmic Artist Vera Molnar: www.veramolnar.com

Artists Shaping Generative Art Scene.

From the pioneers to the present day practitioners here are a number of generative artists you should follow.

Vera Molnár

In the 1960s, Molnar co-founded several artist research groups: GRAV, who investigate collaborative approaches to mechanical and kinetic art, and Art et Informatique, with a focus on art and computing.
Visit Vera’s Site >>

Katharina Brunner

Katharina Brunner is a generative artist and data journalist whose GitHub repository on Generative Art is a great resource for anyone looking to get started using the programming language R. “The R package generative art let’s you create images based on many thousand points. 
Visit Katharina’s Site >>

Jon McCormack

Since the late 1980s McCormack has worked with computer code as a medium for creative expression. Inspired by the complexity and wonder of a diminishing natural world, his work is concerned with electronic “after natures” – alternate forms of artificial life that may one day replace the biological nature lost through human progress and development. 
Visit John’s Site >> 

 

Margaret A. Boden

Margaret A. Boden is Research Professor of Cognitive Science at the University of Sussex. She is the author of Artificial Intelligence and Natural Man, expanded second edition (MIT Press), AI: Its Nature and Future, The Creative Mind, and other books. She was the 2018 recipient of the ACM-AAAI Allen Newell Award for contributions to the philosophy of cognitive science. 
Wikipedia >>

 

Mike Brondbjerg

Designer / developer / artist working in data viz, information & generative design. Currently at London City Hall Intelligence Unit working on Data Viz. 
View Mike’s Works >>

 

Roelof Pieters & Samim Winiger

Roelof Pieters and Samim Winiger, co-founders of Creative.ai, provide an exceptional timeline of computation creativity in their treatise On the Democratization & Escalation of Creativity. 
Visit Creative.ai >>

 

Frederik Vanhoutte

During the daytime, a physics Ph.D. working as a medical radiation expert in a university hospital in Belgium. Together with a team of radiation oncologists, physicists, and nurses, I turn medical data into effective treatments for cancer patients. 
Visit wblut.com >>

Dr. Rebecca Anne Fiebrink

Rebecca Anne Fiebrink, HCI/ML researcher. Dr. Rebecca Fiebrink is a reader at the Creative Computing Institute University of the Arts London
and Department of Computing Goldsmiths, University of London. 
Visit Rebecca’s site >>

Generative Art Action Learning

Getting started with Generative Art has many avenues. There are many tools, programs, frameworks and languages that make it easy to start creating your own algorithmic art. Here are tools, and programs to help get you started.

• Processing: Our staff pick. This is a powerful programming language and development environment for code-based art.
• openFrameworks: A popular open source C++ toolkit for generative and algorithmic art.
• Cinder: An open source C++ library for creative coding.
• C4: An open source iOS framework for generative art.
• Unity: A powerful game engine that can help with generative art and large-scale installations.
• PlayCanvas: A collaborative WebGL engine that works in real-time.
• hg_sdf: A GLSL library for signed distance functions.
• HYPE:  A collection of classes that does a lot of heavy lifting with minimal code required.
• nannou:  An open source framework for creative coding in Rust.
• thi.ng: An open source collection of Clojure and ClojureScript design tools.
• PixelKit: An open source Swift framework for live graphics.
• OPENRNDR: An open source Kotlin library for generative art.
• Phaser: An HTML5 framework for games that uses Canvas and WebGL.
• Canvas-sketch: An HTML5 framework for generative artwork in JavaScript and your browser.
• TouchDesigner:  Point cloud data and recent GPUs’ power to handle it in real-time all pointed to the need for a better point cloud workflow in TouchDesigner
• vvvv: vvvv is a hybrid visual/textual live-programming environment for easy prototyping and development. It is designed to facilitate the handling of large media environments with physical interfaces, real-time motion graphics, audio and video that can interact with many users simultaneously.
• Pure Data: Pure Data (or just Pd) is an open source visual programming language for multimedia. Its main distribution (aka Pd Vanilla) is developed by Miller Puckette.
• Notch: A node-based interface that’s familiar and intuitive to explore, allowing limitless possibilities simply by connecting logical building blocks. Timeline and animation editing, compositing and grading, all in one environment, designed with narrative in mind.

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The following tools are all based on the theory of ornamental group—a specific classification that allocates patterns into categories according to their symmetry and describes its special aspects.

• Adobe Illustrator and Photoshop: Within Adobe Illustrator and Photoshop, you can choose from pre-designed elements (or create them yourself) to generate a pattern instantly. Simple select your object then hit Object> Pattern> Make. The final product can be saved in any format.
• Geo Pattern: Enter any combination of letters, and this fun tool will generate a random geometric pattern made up of polygons, interlocking circles, harmonic waves, and so on. Save options are available only in PNG format.
• KORPUS: A similar free of charge program that transforms any word into a unique pattern. Based on Conway’s Law, it allows you to generate an unlimited number of ornaments. The outcome can be saved in PNG, JPG, or SVG.
• Plain Pattern & Patternico: These are free analogs to Adobe Illustrator and Photoshop. Plain Pattern and Patternico can save you time during the setup mode. You can even upload your own SVG files and use them to create a pattern. Results available in PNG format.
• EveryPixel: Everypixel is an algorithm that forms a layout independently using pre-installed elements: lines, objects, images. In just one cycle, it can automatically create a ton of different patterns. By using the same ornament, you can generate hundreds of options that will consist of the same elements but in different sizes, colors, and orientations against each other. Right now, you can download pre-made patterns, but soon, developers will upload the software to the public and will also teach neural networks this operation.

100 Years of Generative Art

Our abilities to represent complex creative problems is increasing. A fundamental shift in perspective is allowing us to revisit many creative problems. The following section presents generative creation and explores how it democratizes and escalates creativity.

Generative art has come a long way since the 1940s, as we rush toward 2040 we can see it in a full bloom. Generative art and automated algorithms still need human artists to help machine learning algorithms to grasp creative tasks.