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Created by Benedict Hubener, Stephanie Lee and Kelvyn Marte at the CIID with the help from Andreas Refsgaard and Gene Kogan, ‘The Classyfier’ is a table that detects the beverages people consume around it and chooses music that fits the situation accordingly.
Earlier this year SFPC in NYC was the host to alt-AI, a conference organised by Lauren Gardner and Gene Kogan to highlight and question artificial intelligence through the lens of artistic practice.
The following is a documentation of a new course ran by Gene Kogan on Machine Learning for Artists at ITP-NYU in spring 2016.
At the upcoming (14th!) edition of Geneva’s Mapping Festival (May 9 – 12), CAN is proud to co-host Mapping LAB – a one-day educational program of 13 workshops run by leading artists, designers, and researchers in our field. Join us!
Created by Bjørn Karmann at CIID, Objectifier empowers people to train objects in their daily environment to respond to their unique behaviours. Interacting with Objectifier is much like training a dog – you teach it only what you want it to care about. Just like a dog, it sees and understands its environment.
At its best, creative inquiry offers intellectual nourishment, empowerment and solace. At the end of 2016, we need all of those, which is why remembering – and celebrating – the outstanding work done this year is all the more important. Over the past twelve months we’ve added more than 100 projects to our archive – and with your help we’ve selected the favourite ones!
In December 2015, SFPC were invited to participate at Day for Night festival in Houston, TX. SFPC co-founder Zach Lieberman, students from the fall 2015 session, and the larger SFPC community worked together to create ‘SFPC re-coded’, a project that presented over 50 animations from more than 30 different contributors.
Algorithmically generating 3d printed forms created for the sole purpose of listening to the “ocean”. In this process, the project attempts to address the role of experience in the mediation of the virtual world to the real world and visa versa.