In 2018 I began exploring new ways to utilize generative neural networks to multiply a person's creative output. I worked closely with a fellow designer/data scientist to setup a test bed generative adversarial neural network. With this test bed we generated a number of visual outputs all based on TV shows such. This was simply a proof of concept though, my real interest was to create a tool that would allow a designer to have a generative feedback loop with the machine. To that end I curated a data set of ~2500 images of chairs to use to train the network. With that model we were able to create a simple interface that allowed a designer to generate random chairs then remix and iterate based on styles they liked. These chairs were always novel and the outputs had immense variety.