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Pikazo: Deep Neural Network Art on Intel Architecture

In this video from the Intel HPC Developer Conference, Noah Rosenberg and Karl Stiefvater from Pikazo describe the company’s innovative Pikazo App for smartphones.

Noah Rosenberg, CEO, Pikazo

Noah Rosenberg, CEO, Pikazo

“Pikazo was developed in 2015 using neural style transfer algorithms. It is a collaboration between human, machine, and our concept of art. It is a universal art machine that paints any image in the style of any other, producing sometimes-beautiful, sometimes-disturbing, always-surprising artworks. Pikazo allows novice artists to create impressive imagery via a technique known as neural style transfer. Neural style is a very uncommon problem set for computation, using a detection network to actually generate images. Common methods involve large pre-trained networks, with functional results delivered via feed-forward processes running on GPU systems with relatively low RAM. Our implementation for performing neural style transfer of artistic images requires a novel sampling of the network data as it is being calculated, which requires exceptional amount of compute and RAM availability. We’ll cover our implementation, the difference between CPU and GPU, how to implement training live at scale, and what future applications may be in store.”

See more Machine Learning videos from the Intel HPC Developer Conference

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