A curious and creative character awakens. Developed inside a computer it yearns to learn. You meet it in our performance. It wants to learn about you and starts a conversation. It tries to express itself by playing with a musician. And it leaves that space to explore the world by itself. This is also a prototype for a theatrical staging in digital space. As an audience member, imagine yourself being one of the participants in this Zoom-like meeting. You enter the space with your webcam using the same custom built Augmented Reality filter which you see on all the faces in the video.
"Machine Learning for Musicians and Artists" is a course hosted on Kadenze.com and taught by Dr. Rebecca Fiebrink. It proved to be instructive and inspiring and helped effectively for the communication with specialists from the field. It's a good intro if you’re new to the area and interested to see how simpler ML algorithms can be related to music and performance art.
Already in 1990, musical experiments with analog neural networks have been made. David Tudor, a major figure in the New York experimental music scene, collaborated with Intel to build the very first analog neural synthesizer.
The Free Energy Principle - Neuroscientist Karl Friston on the Markov blanket, Bayesian model evidence, and different global brain theories. How is the brain a statistical model of the world it inhabits?
One of our research approach starts with the notion that language evolved as a subset of music. So first was music, then language. A notion that already Heiner Müller expressed when he said that it's not the singing that starts when words end, but exactly the opposite.