Part 7/9:
A notable segment of their conversation focused on AI interpretability—the challenge of understanding how AI models arrive at their decisions. Nathan shared promising advancements in interpretability research, indicating that researchers are beginning to uncover how AI systems process information internally. This includes identifying the activation of specific neurons corresponding to particular concepts, which could ultimately provide insights into ensuring that AI operates within safe and ethical parameters.