Saturday 13:30–14:30 in Auditorium

KEYNOTE: Picasso's terminal; data science and AI in the visual arts

Gene Kogan

Audience level:


A talk about the flourishing intersection between machine learning and art, a survey of recent works emerging from it, and a primer on how to get started with it for seasoned developers and newcomers alike.


Over the past several years, two trends in machine learning have converged to pique the curiosity of artists working with code: the proliferation of powerful open source deep learning frameworks like TensorFlow and Torch, and the emergence of data-intensive generative models for hallucinating images, sounds, and text as though they came from the oeuvre of Shakespeare, Picasso, or just a gigantic database of digitized cats. This talk will review these developments and offer a set of interdisciplinary tools and learning resources for artists and data scientists alike, if ever there was a difference to begin with.

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