{"id":1209,"date":"2022-02-23T11:26:18","date_gmt":"2022-02-23T16:26:18","guid":{"rendered":"https:\/\/courses.ideate.cmu.edu\/60-212\/s2022\/?p=1209"},"modified":"2022-03-22T16:27:10","modified_gmt":"2022-03-22T20:27:10","slug":"hunan-creature","status":"publish","type":"post","link":"https:\/\/courses.ideate.cmu.edu\/60-212\/s2022\/hunan\/02\/23\/hunan-creature\/","title":{"rendered":"hunan-creature"},"content":{"rendered":"

http:\/\/142.93.58.191\/automata\/<\/a><\/p>\n

INTERACTION<\/strong>\u00a0 You can click or click-drag across the canvas to destroy the cells, they will regenerate (to a certain extent.) Y0u can also double click to spawn a new cell which will grow into a new colony.<\/p>\n

INTRODUCTION<\/strong>\u00a0 This is a living self-portrait in a cellular automata (game of life) where each pixel in the 48*48 grid is an individual “creature” that has a 256 bit memory, the first 32 bit of which is its displayed color (RGBA.) A fixed neural network (can be thought of as a set of very complex rules, these rules are learned instead of manually selected like in Conway’s game of life) is then used to operate on the state of the creature based on a 3*3 perception field and its memory.<\/p>\n

IDEATION<\/strong>\u00a0 This piece, especially the idea of a self-portrait, is inspired by Leibniz’s Monadology. In Leibniz’s metaphysics, he proposes that everything in the world is made of “monads” (conscious, thinking atoms) and that all objects, including us humans, are just many monads working in perfect, predetermined, harmony (established by God) without communicating with each other. The concept of cellular automata is exactly that — independent cells, each with limited perception, without any communication, reacting to the changes in their environment according to pre-established, unchanging laws (the neural network.)<\/p>\n

TECHNOLOGY<\/strong>\u00a0 The model takes the perception field of each cell and performs a depth-wise convolution with Sobel and identity kernels before feeding it into a standard Densenet-121, where it then goes through another dense block before outputting the 32 channel new state (top 4 will be the new appearance.) There is also an alive mask where all cells with alpha below 0.1 are reset. A better explanation of the technology behind this project can be found here: https:\/\/distill.pub\/2020\/growing-ca\/<\/a>. This is the paper that inspired part of this work and provided almost all the implementation for the model and the tensorflow.js code that powers the real-time inference on the frontend. The model currently in use was trained on the drawing (of myself) below for 30k epochs (~1.5h.)<\/p>\n

SKETCH\u00a0 <\/strong>This is a sketch that represents what I want to achieve visually if I had the time and skill. I decided to use different angles to highlight the fact that it is not about the image but rather the true three-dimensional self. The Warhol-like gradients add some visual interests and variety while subtlety hinting at the fading dichotomy of digital mass-production and individualism.<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

SCREENSHOT<\/strong><\/p>\n

\"\"<\/p>\n

DEMO<\/strong><\/p>\n