SeeFar

Project Description

An interactive art installation named SeeFar, which focuses on the competition between humans and AI for the lead in intelligence.

SeeFar is an homage to the CIFAR-10 computer vision challenge. CIFAR-10 (www.cs.toronto.edu/~kriz/cifar.html) is an iconic image dataset used for evaluation of image recognition algorithms. It consists of 60,000 32×32 color images in 10 categories, with 6,000 images per class. In 2015, deep learning neural network algorithms have surpassed human performance levels for the first time on image recognition tasks.

In collaboration with Dr. Eyal Gruss and Batt-Girl.

Project Details
Date November 19, 2017