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.

I recently attended #alt-ai, a mini conference on Art and MI organized by Gene Kogan and folks at the School for Poetic Computation (sfpc) in New York City. The event took place in a building that was previously occupied by Bell Labs and was the location of 9 evenings almost 50 years ago. The building later became the Westbeth Artist community (home to many influential and successful artists over the years) and is now home to sfpc. The first day started with a gallery opening (about 14 pieces, many shown on Openframe.io) Gene Kogan gave an intro and a bird's eye view of the sudden explosion of interest in this field over the last year.

It's no secret that machine learning - more specifically, deep learning - has been playing an increasingly noticeable role in the world of art, as of late. From Deep Dream, to Deep Forger, to Beyond the Fence, and further, all varieties of art have been touched by the creativity of neural networks, and it seems that this has not gone unnoticed by those outside of the direct sphere of machine learning. Gene Kogan, of the Tisch School of the Arts at NYU, has recently started up his inaugural offering of Machine Learning for Artists, an elective course in the school's Interactive Telecommunications Program (ITP). The ITP has the mission of exploring "the imaginative use of communications technologies," and how they may be leveraged for bringing art and delight into the lives of individuals. They self-identify as "a Center for the Recently Possible," a term I think is fantastic.