Since Friedrich Kittler we know that noise is not only disturbing our messages, rather it is the message itself — that wants to be decrypted. When looking at images of machine learning, one common pattern is noise. When looking at these machine generated images, what you commonly see, are very distinct artefacts. Moments of distortion, that so many engineers are probably trying to fighting right now. But instead of fighting it, we should take a closer look at the noise produced by these machine learning algorithms.

For example, when training Neural Networks on poster designs one thing become apparent: The machine has a different notion of typography. Overall it has a different understanding of what an image is. This was one of the starting points for the exploration.

As a result a web-tools was created to generate images and alter them using different algorithms to make the hidden noise inside those images visible.

This project was created as part of the Runway Flash Residency.

https://medium.com/runwayml/elements-of-disruption-the-noise-inside-learning-machines-cd0b42f655a8