The details behind my most recent painting are complex, but the impact is simple.
My robots had a photoshoot with my youngest child, then painted a portrait with her in the style of one of her paintings. Straightforward A.I. by today’s standards, but who really cares how simple the process behind something is as long as the final results are emotionally relevant.
With this painting there were giggles as she painted alongside my robot and an amazed result when she saw the final piece develop over time, so it was a success.
The following image shows the inputs, my robot’s favorite photo from the shoot (top left) and a painting made by her (top middle). The A.I. then created a CNN style transfer to reimagine her face in the style of her painting (top right). As the robot worked on painting this image with feedback loops, she painted along on a touchscreen, giving the robot direction on how to create the strokes (bottom left). The robot then used her collaborative input, a variety of generative A.I., Deep Learning, and Feedback Loops to finish the painting one brushstroke at a time (bottom right).
In essence, the robot was using a brush to remove the difference between an image that was dynamically changing in its memory with what it saw emerging on the canvas. A timelapse of the painting as it was being created is below…
Pindar