In 2017, a group of researchers at OpenAI (Alec Radford, Rafal Jozefowicz, and Ilya Sutskever) made an interesting discovery when they observed the values produced by one particular neuron of a language model they had trained. The numeric value that this single neuron took, given an input sequence of words, determined with surprisingly high accuracy the sentiment of the full sequence. Manually editing the value of the sentiment neuron gave them what they called a “direct dial to control the sentiment” of the text generated by the model. Within what seemed to be a chaotic bundle of self organized weights some structure had been identified. Equipped with a partial understanding of this model users were simultaneously granted an opportunity for interpretation, control, and compression of the system as a whole.