Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet (via) Big advances in the field of LLM interpretability from Anthropic, who managed to extract millions of understandable features from their production Claude 3 Sonnet model (the mid-point between the inexpensive Haiku and the GPT-4-class Opus).
Some delightful snippets in here such as this one:
We also find a variety of features related to sycophancy, such as an empathy / “yeah, me too” feature 34M/19922975, a sycophantic praise feature 1M/847723, and a sarcastic praise feature 34M/19415708.
Recent articles
- Highlights from my appearance on the Data Renegades podcast with CL Kao and Dori Wilson - 26th November 2025
- Claude Opus 4.5, and why evaluating new LLMs is increasingly difficult - 24th November 2025
- sqlite-utils 4.0a1 has several (minor) backwards incompatible changes - 24th November 2025