The article explores the concept of "brain rot" in large language models (LLMs), hypothesizing that exposure to low-quality content, such as junk social media posts, leads to a decline in cognitive abilities. Through controlled experiments using Twitter/X data, the authors demonstrate that continual training on junk data results in significant drops in reasoning and understanding, suggesting that data quality is crucial for maintaining LLM performance. The findings advocate for better data curation practices to ensure LLMs remain effective and reliable over time.