Mechanistic Interpretability
mech-interpapproachPath: /knowledge-base/responses/mech-interp/
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"text": "DeepMind deprioritized SAE research",
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}Backlinks (21)
| id | title | type | relationship |
|---|---|---|---|
| representation-engineering | Representation Engineering | approach | — |
| sparse-autoencoders | Sparse Autoencoders (SAEs) | approach | — |
| language-models | Large Language Models | capability | — |
| situational-awareness | Situational Awareness | capability | — |
| why-alignment-hard | Why Alignment Might Be Hard | argument | — |
| deep-learning-era | Deep Learning Revolution (2012-2020) | historical | — |
| safety-spending-at-scale | Safety Spending at Scale | analysis | — |
| anthropic-investors | Anthropic (Funder) | analysis | — |
| anthropic | Anthropic | organization | — |
| arc | ARC (Alignment Research Center) | organization | — |
| deepmind | Google DeepMind | organization | — |
| chris-olah | Chris Olah | person | — |
| connor-leahy | Connor Leahy | person | — |
| dario-amodei | Dario Amodei | person | — |
| neel-nanda | Neel Nanda | person | — |
| alignment-interpretability-overview | Interpretability (Overview) | concept | — |
| debate | AI Safety via Debate | approach | — |
| process-supervision | Process Supervision | approach | — |
| reward-modeling | Reward Modeling | approach | — |
| weak-to-strong | Weak-to-Strong Generalization | approach | — |
| response-style-guide | Response Pages Style Guide | concept | — |