Interpretability and mechanistic approaches

As generative AI moves into production, traditional guardrails and input/output filters can prove too slow, too expensive, and/or too limited. In this episode, Alizishaan Khatri of Wrynx joins Daniel and Chris to explore a fundamentally different approach to AI safety and interpretability. They unpack the limits of today’s black-box defenses, the role of interpretability, and how model-native, runtime signals can enable safer AI systems. 

Featuring:

• Alizishaan Khatri – LinkedIn
• Chris Benson – Website, LinkedIn, Bluesky, GitHub, X
• Daniel Whitenack – Website, GitHub, X

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