We tested the model using self-play frequently before we ever put it in front of humans (outside of our team). One interesting learning was that mistakes that the model makes in self-play games aren't reflective of the mistakes it makes when playing against humans. From a language perspective, in self-play, the model is more prone to "spirals" of degenerate text (as one bad message begets the next, and the model continues to mimic its past language). Moreover, humans reacted differently to mistakes the model made — in human play, a human might question/interrogate the agent after receiving a bad message, while another model is unlikely to do so. This really underscored the importance of playing against humans during development for research progress. -ED