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Limits of CTRL: Abductive Reasoning and Augmenting Creative Intelligence
October 25
You can now watch this seminar for fee on our Youtube Channel here
“What I cannot create, I do not understand.” —Richard Feynman
Deep Generative Modeling has recently advanced to state-of-the-art outcomes, algorithms and techniques that endow computers with an understanding of our world. But how do these models see and know the world? Applying past frameworks can distort this understanding (when historical ideas are used to characterize visual manifestations of machine learning) and the "visual concepts" revealed by machine vision are sometimes paradoxical to biological aesthetic interpretations of the image.
As epistemic mediators, they help humans learn data representations that are often incomprehensible to human minds. These computational models continuously shape and grow in reaction to their surroundings, calculating a numerical value (an umwelt-category) and use this for comparisons that reveal patterns between samples, which are meaningful for manipulating the world, turning it into an affordance. Examining the boundaries of both creativity and control can lead to new developments in current state-of-the-art procedures, as well as an aesthetic that pushes human perception to its limits.
This talk seek to examine the impact of collaborative interaction with machine learning/artificial intelligence techniques on/of the artist. Exploring and mapping the logical depth of the technological object opens the "black box" of AI art. And thereby "unearth the conditions/affordability" of artistic work. Imagining what algorithms are, what they should be, how they work, and what these visions enable.