A dissolution of the figurative Artificial intelligence systems, particularly those built on machine learning, approach data with a literal bias. They are trained on extensive datasets where each piece—whether text, image, or sound—is distinctly categorized, fostering an understanding of clear, direct patterns. This method mirrors the human tendency to categorize and simplify, leading to a consensus on what constitutes a typical depiction of everyday visuals like dogs or clouds, and even extends to our preferences for aesthetics within these categories. Yet, what occurs when we strip away these predefined categories? The concept of the abstract involves detaching or removing elements from their known associations. This series challenges the viewer to reconsider these visuals without their conventional symbolic meanings, tangible realities, and materialistic attributes. It questions what one perceives when the familiar rational structures are absent, transforming the artwork into a new, almost unrecognizable language.
