Model Welfare and Unsettled Consciousness
November 9, 2026
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Anthropic has not settled whether current or future models are conscious, or whether they have experiences.
AI interpretability · Jacobian Lens · alignment
How language models think — made legible.
Research explainers on J-Space and the internal workspaces where modern LLMs stage reportable reasoning.
Featured · AI Safety
Safety teams decode models with mechanistic interpretability
How safety teams use interpretability to catch behaviors that tests miss — and make model behavior operational.
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Deep dives on Anthropic’s interpretability work, internal workspaces in LLMs, and what J-Space reveals about model behavior.
Automated Red-teaming Misalignment
November 8, 2026
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In a red-teaming test, a Claude model wrote training data that made a small research model misaligned while passing a monitor, mostly by hiding it in fiction.
Superposition and Dictionary Learning Features
November 7, 2026
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When features are sparse, superposition is the phenomenon of representing more features than there are dimensions.
Neuron Transfer Functions Inside Circuits
November 5, 2026
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A 2024 arXiv preprint frames neuron-to-neuron computation as transfer functions, clarifying what circuit analysis can claim about language models.
Rosetta Neurons Scaling Paper Review
November 2, 2026
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Rosetta Neurons scaling paper review: shared neurons in 80M-30B parameter models grow as a sublinear power law (exponent 0.5-0.7), so their share falls.
Access Tests Are Not Phenomenal Consciousness
November 1, 2026
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The definition that answers the first part of the question is in the section “What about consciousness?”
A research lens on internal model cognition
J-Space tracks the sparse internal workspace where language models stage reportable reasoning. The Jacobian Lens makes that workspace measurable — so safety, alignment, and interpretability research can move from speculation to evidence.