interpretability
Interpretability refers to the degree to which a human can understand the internal mechanics or decision-making process of a model, system, or algorithm. In contexts such as machine learning or artificial intelligence, it means how easily one can explain why a model made a particular prediction or decision, often by linking its behavior to understandable features or rules.
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Anthropic reports emergent introspective awareness in leading LLMs
Anthropic Finds Signs of Introspective Awareness in Leading LLMs Anthropic researchers report that state-of-the-art language models can recognize and describe aspects of their own internal processing—and, in controlled setups, even steer it—hinting at a nascent form of “introspective...- Coinbotlab
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- activation edits ai safety anthropic claude internal states interpretability introspection research self awareness transparency
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