Edge intelligence, central reasoning
A research note on giving efficient local models and larger central systems different jobs inside one security architecture.
Insights
One publication. Many difficult questions.
Technical articles, research, engineering notes, and professional analysis about intelligent systems and the real engineering required to make them useful.
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Ergodic Theory: What the Long Run Can Teach Us
Ergodic theory explains when one long trajectory can reveal a system’s statistical truth—and why data volume alone cannot guarantee learning.
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articleFrom the law of large numbers to Mamba-based telemetry analysis and human trial-and-error, the value of repetition depends on what the process lets us observe.Ergodic theory explains when one long trajectory can reveal a system’s statistical truth—and why data volume alone cannot guarantee learning.
articleRyan Powers reflects on his path from Marine cyber operations to cybersecurity graduate study and applied research at USF.How military service, resilience, and an applied research mindset shape my work in cybersecurity and AI at the University of South Florida.
articleLearn the foundations of reinforcement learning and Markov decision processes, then compare PPO and SAC through their mechanics, use cases, strengths, weaknesses, and practical tradeoffs.A practical guide to two leading reinforcement-learning algorithms: how Markov decision processes frame the problem, why PPO favors stable updates, and why SAC emphasizes sample efficiency and exploration.
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Ergodic Theory: What the Long Run Can Teach Us
From the law of large numbers to Mamba-based telemetry analysis and human trial-and-error, the value of repetition depends on what the process lets us observe.