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Controlling AI Models from the Inside
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Daniel Whitenack and Chris Benson

· 44 Minutes

PodcastPractical AI

Controlling AI Models from the Inside

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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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Original source

This story was published by Practical AI and written by Daniel Whitenack and Chris Benson. SyncAI.news shows a preview; the complete article is on the publisher's site.

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