The discussion centers on the implications of having 'N' identical chess computers with the same rating play against each other infinitely. Participants question whether the computers are reset before each game or if they learn from experience, affecting their ratings. It is suggested that if the computers are identical and do not update their settings, their ratings would converge to a uniform distribution. However, if they learn and adjust their strategies, the ratings might trend towards a normal distribution due to the central limit theorem. The conversation highlights the complexities of rating systems like ELO and how they might behave under these conditions.