Summary:
- The article outlines Anthropic’s research into "interpretability," a field of study focused on reverse-engineering the internal neural activations of Large Language Models (LLMs) to understand how they process information.
- It details the discovery of millions of "features" within the model's neural network, which correspond to human-understandable concepts, providing a significant step forward in making "black box" AI systems more transparent and controllable.