In this presentation, Andreas Schlegel will give a brief overview of his work as a creative practitioner working with code and across disciplines.

When we think of coding, the visual arts are certainly not the first discipline that comes to mind where code is applied. However, artists have been enthusiastic, often innovative and influential practitioners at the intersection of code and art.

Looking back at my practice over the past years, my work is diverse in discipline, application and interest, but what most of my work has in common is writing code, expressing ideas through code. To what extend can code be a creative medium and to what extend is it a tool? Or is it both?

Over the years as practitioner and educator, code has been a constant and driving force in my work. You may notice in the following that code takes on different roles, applications and outcomes.

Although coding is a rather solitary activity, many of my works are collaborative and span across various disciplines and applications, from visual arts to music and performance, from research and education to workshops, performances or exhibitions.

I have written software to express ideas through visual, audible, interactive, or networked outcomes. Often this is driven by my fascination for contemporary technologies and advancements.

Tech now seems to advance and change so rapidly, I am not sure if it is me who is getting slower or if it is tech and the world that is just getting faster and faster?

Based on a series of prepared examples, workshop participants are invited to remix code and play with numbers to modify the visual output generated by code.

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19th Century

21st Century

20th Century

Ada Lovelace (1815 - 1852), although not an artist but considered the first computer programmer, asked in a letter to her mother, who was terrified that Ada might end up being a poet like her father: “if you can’t give me poetry, can’t you give me poetical science?” Can code be poetry? Can code make poetry?

The artist Harold Cohen, for example, dedicated most of his life to AARON, an AI machine that he meticulously developed and taught to paint independently and create his own painting style.

At times, AARON was quite autonomous of Cohen, responsible for the composition, coloring, and other aspects of a work; more recently, AARON served Cohen by making drawings that he would develop into paintings.

Harold Cohen and Aaron, 2016

In the early 2000s MIT students Casey Reas and Ben Fry at the Media Lab’s Aesthetics and Computation Group created a coding environment called Processing which should become a platform and community for many creatives to use code as an essential companion in their practice.

RandomNoiseFlow uses custom software to create black and white textures. The algorithm written for RandomNoiseFlow uses numbers generated by a computer's random number generator and the Perlin noise algorithm. The resulting algorithm is used to define the position of a single particle in a 2D space over time. The particle, a tiny white rectangle with a black border of one pixel, incrementally marks its next position. The images generated then resemble the visual quality of lava or rock layers expressed by algorithms and numbers.

In Movement of Things, a small motion sensor is attached to various physical objects to measure and record their movements. This project does not represent an end result, but a process. You could say the project just happened, one idea followed the next - through discussions, being in the flow, leading from one step to the next. Looking back at the work today, it doesn't make much sense functionally, but poetically it has value, stories and memories.  

Code is best written when in the flow, in a state of mind comparable to that of solitude and pure focus. Writing code is often associated with logic, rationality and efficiency – Machine Dreams eludes this approach. It is a generative system that creates a constantly changing sequence of images. Random numbers represent the sensory experience captured in this imaginary world, and computational processes translate into fleeting moments of abstract patterns.

Ray marching is a technique which traces a path of light step by step while testing for ray intersections. It is useful to find surfaces and render volumes in 3D space. The generated shapes in this work start from a sphere and continuously transition into heavily distorted and abstracted forms through parameter changes.

Ray marching computes 2D images from 3D volumetric data sets . It is often used in computer graphics to render (hyper-)realistic looking 3D scenarios and has its place in the demo scene, games, special effects or high-end graphics engines.

The first algorithm is based on reinforcement learning, an area of machine learning. In reinforcement learning, software agents perform actions within an environment.

Agents here learn over time based on the rewards they receive - learning by trial and error. This technique has proven to be successful when used in games, controlling robots, or performing autonomous tasks.

The second algorithm is based on a technique called ray marching. Here, the algorithm follows a virtual light path step by step, checking for intersections with objects in the environment.

Ray Marching is useful for finding surfaces and for rendering volumes in 3D space. It is commonly used in computer graphics to render (hyper)realistic looking 3D scenarios in real time and has its place in games, demoscene, virtual reality, special effects in movies or high-end graphics engines.

In Machine Dreams two algorithms run in parallel, one informing the other through its actions.

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Field Trip

DIY 3D scanning 

3D Printing 

Exhibition

in search of artifacts in a wide open terrain and far away.