NORAA [machinic doodles]
Jessica In, George Profenza, Sam Price · 2020
How does machine learning contribute to our understanding of how ideas are communicated through drawing? Specifically, how can networks capable of exhibiting dynamic temporal behaviour for time sequences be used for the generation of line (vector) drawings? Can machine-learning algorithms reveal something about the way we draw? Can we better understand the way we encode ideas into drawings from these algorithms?