Exploring How To Fail Interpretability Research
Exploring How To Fail Interpretability Research reveals several interesting facts.
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In-Depth Information on How To Fail Interpretability Research
Been Kim (Google Brain) https://simons.berkeley.edu/talks/tba-90 Emerging Challenges in Deep Learning. Stanford AI Lab Faculty Lunch, November 7, 2025. Updated version of https://web.stanford.edu/~cgpotts/blog/interp/ 0:59 ... A surprising fact about modern large language models is that nobody really knows how they work internally. At Anthropic, the ... Been Kim (Google Brain) https://simons.berkeley.edu/talks/tbd-72 Frontiers of Deep Learning.
When Anthropic tested Claude Sonnet 4.5 for alignment, the model appeared perfectly behaved — but it turned out the model had ...
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