Creative hacks of Machine Learning

This talk will examine the resurgence of popular interest in machine learning and artificial intelligence through the lens of creative subversion. Recent breakthroughs in scientific research, combined with the rise of big data and the proliferation of cheap GPU computing power, have dramatically increased the capacities of machine intelligence in a variety of domains. Boosted by powerful new open source libraries and various initiatives to demystify AI and make its research more accessible, the subject is rapidly crossing over into mainstream culture, inspiring numerous subversions of machine intelligence in nontraditional contexts.

This talk will examine a wave of artistic projects applying these methods in various domains, producing troves of machine-hallucinated text, images, sounds, and video, demonstrating an affinity to imitating human style and sensibility. These experimental works attempt to show the capacity of these machines for producing aesthetically and culturally meaningful art, while also challenging them to illuminate their most obscure and counter-intuitive properties.

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About the speaker

Gene Kogan is an artist and programmer who is interested in generative systems and applications of emerging technology in artistic and expressive contexts. He writes code for live music, performance, and visual art. He contributes to numerous open-source software projects and frequently gives workshops and demonstrations on topics related to code and art.

He is a contributor to openFrameworks, Processing, and p5.js, an adjunct professor at Bennington College and NYU, a former resident at Eyebeam Art & Technology Center, and a former Fulbright scholar in Bangalore, India, 2012-2013.

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