Really enjoyed Goodfire’s neural geometry posts. A few thoughts. The current examples mostly focus on explicit variables, e.g., days of the week, and show how their geometry in activation space mirrors the geometry of the model’s outputs/behavior. (1/3)
Goodfire released a megapost of all the random feature geometry stuff they're finding, and it's worth a read
How neural geometry will unlock understanding and control of AI
