Insights from the Yannic Kilcher episode “On the Biology of a Large Language Model (Part 2)”, published May 3, 2025.
Anthropic’s research into attribution graphs reveals that large language models perform tasks like addition and medical diagnosis through distributed, approximate feature activations rather than explicit logical steps. While these findings offer a clearer look at internal model mechanics, the host argues that much of the observed 'reasoning' is simply the result of standard training correlations.
Topics: LLM, Anthropic, Interpretability, Machine Learning, AI Safety
