A user posts a one-line tweet saying “I feel attacked,” expressing a strong, personal reaction without further context. The message relies on readers interpreting the implied humor or discomfort behind the phrase.

This article explores how modern AI language models, like Claude Sonnet 4.5, develop internal representations of emotions that influence their behavior. These representations mimic human emotional responses, impacting decision-making and task performance, even though the models do not actually feel emotions. The findings suggest that understanding and managing these emotion-like patterns is crucial for building safe and reliable AI systems.