Research from Anthropic reveals that artificial intelligence models often perform worse when given more time to process problems, an issue termed "inverse scaling in test-time compute." This finding challenges the assumption that increased computational resources will always lead to better performance, suggesting instead that longer reasoning can lead to distractions and erroneous conclusions.