I trained a neural net from scratch on lists of colors I could find online, and with no prior training on English or any language (and therefore no idea what paint colors were) it managed to reproduce some of the letter combinations in the originals. And these neural networks have not only seen English before, they have also read all the popular paint color sites. As the January 2022 Futurist in Residence at the Smithsonian AIB, I've spent the month thinking about how much difference our starting points make, how we have to take care what foundations we build on when working with AI. So as my starting point I used that original neural net's garbled paint colors. A computer screen generates its colors by illuminating tiny red, green, and blue dots that blend together when you view them from a distance. But it had seen enough Red, Green, Blue color listings that it was able to follow the format from just a couple of examples.

One of my first experiments with neural network text generation was to generate and name paint colors. I trained a neural net from scratch on lists of colors I could find online, and with no prior training on English or any language (and therefore no idea what paint colors were) it managed to reproduce some of the letter combinations in the originals. In the nearly five years since, a lot has changed in AI. Now we have giant internet-trained neural networks. And these neural networks have not only seen English before, they have also read all the popular paint color sites.