LOG-IN

Gene Kogan OpenTalk

Gene Kogan OpenTalk

23/11/2016 - 19:00

Gene Kogan OpenTalk
Machine Learning for Artists: a beautiful and interesting game

Within the Machine Learning for Artists workshop program in Opendot from 21st to 25th of November, we are proud to invite you to the Gene Kogan OpenTalk, on Wednesday 23rd at 7 pm in Opendot lab.

A Beautiful and Interesting Game: a lecture by Gene Kogan on creative applications for Machine Learning algorithms

This talk examines the rise of machine learning and artificial intelligence through the lens of artistic practice and creative subversion. Recent breakthroughs in scientific research, combined with the proliferation of big data and cheap GPU computing power, have dramatically increased the capacities of machine intelligence in a variety of domains. The tech titans have swiftly integrated them into most of their core services, whilst numerous startups have appeared to capitalize on emerging markets. At the same time, artists, boosted by independent open source implementations, have attempted to subvert and illuminate those same technologies, shedding light on the sometimes beautiful and sometimes dangerous new faculties of these powerful algorithms.

/ About Gene
Gene Kogan is an artist and a programmer who is interested in generative systems, artificial intelligence, and software enabling self-expression and creativity. He writes code for live music, performance, and visual art. He is a collaborator within numerous open-source software projects, and leads workshops and demonstrations on topics related to code and art. Gene is a contributor to ml4a, a free book about machine learning for artists, activists, and citizen scientists. He regularly publishes video lectures, writings, and tutorials to facilitate a greater public understanding of the topic. He has previously taught classes at ITP-NYU, Bennington College, and SchoolOfMa, and has been artist-in-residence at SFPC and Eyebeam.

@genekogan / genekogan.com / ml4a.github.io
eyebeam.org / schoolofma.org / sfpc.io / tisch.nyu.edu/itp

 

Docenti: 
Gene Kogan