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Notes from research and engineering practice, with a focus on trustworthy AI and real-world systems.
[ 4/14/2026 ]
Self-Adaptive AI for Healthcare: Balancing Personalization, Privacy, and Safety
Healthcare AI must adapt to individual patient contexts while preserving privacy and clinical safety. This post outlines a trustworthy path.
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Design Principles for Self-Adaptive AI: Monitor, Decide, Adapt, Verify
A practical blueprint for adaptive AI loops: continuous monitoring, policy-based decisions, safe adaptation, and post-change verification.
Read post[ 4/14/2026 ]
Self-Adaptive AI in Real-World Systems: Why Static Models Fail
Static AI models degrade after deployment. Self-adaptive AI continuously senses drift, updates behavior, and preserves reliability in changing environments.
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