AI Internals Are Weird — Tom McGrath
Tom McGrath, Chief Scientist at Goodfire, delves into neural network interpretability, intentional design, and the geometry of learned concepts. The discussion covers how models learn modularity and algorithmic structures like arithmetic, the limitations of current interpretability tools like sparse autoencoders, and the implications for alignment, reward hacking, and multi-agent systems.
