Decomposing Language Models Into Understandable Components. Anthropic appear to have made a major breakthrough with respect to the interpretability of Large Language Models:
“[...] we outline evidence that there are better units of analysis than individual neurons, and we have built machinery that lets us find these units in small transformer models. These units, called features, correspond to patterns (linear combinations) of neuron activations. This provides a path to breaking down complex neural networks into parts we can understand”
Recent articles
- First impressions of Claude Cowork, Anthropic's general agent - 12th January 2026
- My answers to the questions I posed about porting open source code with LLMs - 11th January 2026
- Fly's new Sprites.dev addresses both developer sandboxes and API sandboxes at the same time - 9th January 2026