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Controlling AI Models from the Inside

Practical AI · 2026-01-20 · 44 min

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Topics in this episode

Neural networksComputer visionArtificial intelligenceMachine LearningDeep Learningchangelog

Episode notes

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 Upcoming Events: Register for upcoming webinars here !

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