In this episode we discuss Large Language Models Cannot Self-Correct Reasoning Yet by Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou. The paper explores the effectiveness of self-correction in Large Language Models (LLMs) for improving the accuracy and appropriateness of generated content. It specifically focuses on the role of self-correction in reasoning tasks. The study reveals that LLMs struggle to self-correct without external feedback and, in some cases, their performance declines after self-correction. Possible areas for further research and practical applications in this domain are also discussed.