The article discusses a new approach to improve large language models by using weak critics to provide guidance rather than direct labels, enhancing their performance through a method called on-policy critique distillation (OPCD). This technique shows promise for scalable oversight in AI, suggesting that even weak supervision can lead to significant improvements in model capabilities over time.