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Robot Art 2017 - Top Technical Contributor

CloudPainter used deep learning, various open source AI, and some of our own custom algorithms to create 12 paintings for the 2017 Robot Art Contest. The robot and its software was awarded the Top Technical Contribution Award while the artwork it produced recieved 3rd place in the aesthetic competition.  You can see the other winners and competitors at www.robotart.org.

Below are some of the portraits we submitted.  

Portrait of Hank

Portrait of Hank

Portrait of Corinne

Portrait of Corinne

Portrait of Hunter

Portrait of Hunter

We chose to go an abstract route in this year's competition by concentrating on computational abstraction.  But not random abstraction. Each image began with a photoshoot, where CloudPainter's algorithms would then pick a favorite photo, create a balanced composition from it, and use Deep Learning to apply purposeful abstraction. The abstraction was not random but based on an attempt to learn from the abstraction of existing pieces of art whether it was from a famous piece, or from a painting by one of my children.

Full description of all the individual steps can be seen in the following video.

 

 

NVIDIA GTC 2017 Features CloudPainter's Deep Learning Portrait Algorithms

CloudPainter was recently featured in NVIDIA's GTC 2017 Keynote. As deep learning finds it way into more and more applications, this video highlight some of the more interesting applications. Our ten seconds comes around 100 seconds in, but I suggest watching the whole thing to see where the current state of the art in artificial intelligence stands.