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.
Topics describe what an idea is about. Formats describe what kind of piece it became.
Featured / article
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.
Read the insight1 insight
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.
From insights to work
See the systems behind the ideas.
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.