On April 24th I have the great honor to share the stage with Casey Reas and Christiane Paul for a conversation about generative systems at the Great Hall at The Cooper Union in New York City.
www.eventbrite.com/e/conversati...

Oops, I should have checked that a bit earlier: turns out my dawing board bends down 5 mm in the center. Not great if a millimeter more or less already makes the stroke width vary considerably.

Starting to get some more trust in my robot not running into a wall or trying to pierce my canvas, so I dare to allow it some "broad strokes".

All my early AI work was using models I had trained on my own datasets that I had collected/curated myself.

These for example are from my 2017 "Imposture" series that was trained on images and poses extracted from pornographic images.

Of course the loss explodes if I measure similarity instead of distance, duh. I still don't know what it tries to optimize for here, but I kind of like the Moomin-graffiti vibes.

Maybe I should turn down the learning rate somewhat. But it does explode in a quite interesting way.

It's easier for the algorithm to work with shorter segments.

Different starting conditions and target.

I have started to experiment again with diffvg and gradient descent on expressive vector strokes.

You are here.