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Article Series: Securing the AI Stack: From Model to Production

Your AI deployment is one misconfiguration away from breach. Here's the layered defense framework enterprises are adopting now.

Reporting by InfoQ AI/ML 1 min brief
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Exploring the next frontier of AI research.AI illustration by KeyNews
The KeyNews take

Why it matters

As AI moves from research to production, security governance and MLOps resilience have become board-level concerns. This series addresses the infrastructure and policy gaps that separate prototype from production-ready systems.

The key facts

9 to know

  1. Focus on layered defense architecture for AI systems

  2. MLOps and governance integration as production requirements

  3. Shift from vulnerable prototypes to resilient deployments

  4. Security frameworks for end-to-end AI stack protection

  5. Focus on layered defense across AI stack

  6. MLOps and governance as core security pillars

  7. Addresses transition from prototype to production resilience

  8. Author: Claudio Masolo

  9. Published on InfoQ (enterprise architecture audience)

Go to the source

InfoQ AI/MLinfoq.com

Publisher excerpt: This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance. By Claudio Masolo
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