Researchers at Anthropic have made significant progress in understanding the internal workings of large language models (LLMs), particularly Claude 3. Their new interpretability paper reveals detailed insights into the 'features' of Claude 3, identifying millions of these features that activate when specific concepts such as San Francisco, lithium, or deception are discussed. This breakthrough offers a glimpse into the previously mysterious operations of artificial neural networks, potentially addressing the long-standing issue of AI being perceived as a 'black box'. The research highlights concept-like feature representations for a range of ideas, from concrete entities like the Golden Gate Bridge to abstract notions such as secrecy and conflict. Additionally, a new 'brain scan' developed by the researchers could be a solution to understanding AI operations.