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AMOR: Entropy-Gated SSM-Attention Hybrid

AMOR: Entropy-Gated SSM-Attention Hybrid

AMOR is a hybrid model inspired by dual-process cognition theories, dynamically activating sparse attention only when SSM predictions show high entropy uncertainty. It projects Ghost KV from SSM states for O(n) efficiency, outperforming SSM-only and Transformer baselines on retrieval tasks with perfect accuracy using just 22% attention positions. Prediction entropy reliably detects retrieval needs with a 1.09 nats gap.

ArXiv AIResearchFeb 17#research#amor#architecture
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Cybersecurity Must Protect Physical Reality

As industrial systems, infrastructure, robots, and AI agents gain the ability to change physical conditions, cybersecurity must protect actions and outcomes—not only data and access. The article argues that future defenses need to evaluate whether an authorized action is appropriate for the current environment, state, and safety boundaries.