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DeepMind gives up on mechanistic interpretability research

cubefox Monday, December 01, 2025
Summary
The article proposes a pragmatic vision for interpretability in machine learning, focusing on understanding the system's reasoning and decision-making processes rather than achieving full transparency. It emphasizes the importance of interpretability for building trust and reliability in AI systems.
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