We're entering the age of machine-generated art. Many of the new systems are shockingly impressive but impossible to replicate by individuals because they rely on complex machine learning techniques with huge datasets that aren't feasible to do in a home environment. Fortunately, there's an entire group of clever approaches to generate graphics that look cohesive, unique, and deliberate... and that you can easily do on your own computer. In this short talk we'll go through a few of those algorithms like Clifford attractors, slime mold simulation, and reduction of source imagery to geometric primitives. We'll generate images and animations, we'll dabble in 2D and 3D. You'll leave the talk with your own ideas how to create attractive visualizations out of thin air. The talk assumes familiarity with Python and high-school math.