What Is AI Interpretability — and Why Look Inside Models?
AI interpretability is the effort to understand what happens inside a model between input and output. Here's what it means, how researchers do it, and why it matters.
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AI interpretability is the effort to understand what happens inside a model between its input and output — the concepts and computations behind its answers. This hub follows interpretability research and why it matters for safety and trust.
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Anthropic's J-Lens Reveals a Hidden Workspace Inside Claude
A new Anthropic interpretability tool called the Jacobian lens surfaces concepts Claude is silently processing but never writes down, including signs it recognizes when it's being tested.
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