How does an AI LLM think ?

This research from Anthropic investigates the internal workings of their Claude 3.5 Haiku language model using a methodology called circuit tracing. The authors explore a diverse range of capabilities, such as multi-step reasoning, poetry planning, multilingual processing, arithmetic, medical reasoning, and handling of hallucinations and harmful requests, by analyzing the model's computational graphs. Through these case studies, they aim to understand how the model represents and manipulates information to generate its responses, often uncovering unexpected strategies like forward and backward planning. The research also examines chain-of-thought reasoning, hidden goals in misaligned models, and common structural elements within the identified circuits, ultimately providing insights into the "biology" of this large language model and discussing the limitations and potential future directions of their interpretability methods.