Zoom In: An Introduction to Circuits
by Distill / OpenAI · free · Last verified 2026-03-17
This essay by Chris Olah and colleagues at Distill introduces the circuits framework for mechanistic interpretability, arguing that neural network weights encode interpretable algorithms composed of features and circuits. It presents case studies of curve detectors and multimodal neurons as evidence that individual units and motifs in neural networks are meaningfully interpretable.
https://distill.pub/2020/circuits/zoom-in/ ↗B
B—Above Average
Adoption: B+Quality: A+Freshness: BCitations: AEngagement: F
Specifications
- License
- Open Access
- Pricing
- free
- Capabilities
- feature-analysis, circuit-analysis, mechanistic-understanding, weight-interpretation
- Integrations
- Use Cases
- ai-safety, model-interpretability, neural-network-analysis
- API Available
- No
- Tags
- interpretability, mechanistic-interpretability, circuits, neural-networks, features
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
66.6Adoption
70
Quality
93
Freshness
60
Citations
80
Engagement
0