A weekend program exploring the interconnection between art and machine learning.

November 16, 2019, 10:00 am   » 

**November 15, 2019 (night-time only) - Navel - Downtown LA
November 16-17, 2019 - EDA (Broad Art Center 1250), UCLA

Feature Extraction is a series of talks and workshops centered around machine learning, abstraction, and algorithmic subjectivity organized by Blaine O'Neill and Ulysses Pascal, grad students in the Design Media Arts and Information Studies departments. Participants in the first Feature Extraction weekend will learn how certain machine learning models work, play with them in creative/critical ways, and contextualize them in social, cultural, and political frameworks. We will kick off the weekend Friday night at NAVEL in downtown LA with an evening panel discussion and social, followed by 1.5 days of workshops at the EDA led by Gene Kogan and Lou Cantor.

Day 2
Saturday, Nov. 16, 2019, 10am-6pm
The Neural Aesthetic
Gene Kogan

A coding/art workshop equipping participants with the skills to better understand and work creatively with machine learning models.

10am - 1pm - Session 1
1pm - 2pm - Lunch
2pm - 5pm - Session 2
Gene Kogan is an artist and a programmer who is interested in autonomous systems, collective intelligence, generative art, and computer science. Gene initiated ml4a, a free book about machine learning for creative practice.
(EDA) Broad Art Center, 1250

Day 3
Sunday, Nov. 17, 2019, 12-3pm
Myths of the Near Future
Lou Cantor

An art/writing workshop speculating on the social repercussions of AI.

12pm - 1:30pm - Session 1
1:30pm - 2:00pm - Break
2:00pm - 3:30pm - Session 2
3:30pm - 4pm - Closing Remarks

Lou Cantor is a Berlin-based artist collective founded in 2011, whose main scope of interest is grounded in intersubjectivity and interpersonal communication.
(EDA)Broad Art Center, 1250

More info

EDA  (Map)
Broad Art Center
240 Charles E. Young Drive, Room 1250
Los Angeles, CA 90095
+Parking is $12 all day, and is available in structure 3, adjacent to the building. For more information, call 310.825.9007.