Chris Allen Premoe

Title: Chris Allen Premoe and AI Agent Control

Introduction

Chris Allen Premoe is an inventor based in Redmond, Washington. His patent work concerns methods for making artificial intelligence agents more reliable when they control mechanical systems.

Latest Patents

Premoe is associated with 1 patent, titled “Stochasticity Mitigation in Deployed AI Agents.” The disclosed techniques address variability in AI-agent outputs over both short and long timeframes. Long-term variability may be reduced by adjusting the reward function used to train a machine-learning model, while short-term variability may be managed by applying margins to an agent’s output. Examples include window averaging, clamps, and statistical process control bounds.

The patent also describes AI agents built as regression models from setpoints inferred from environmental states. Because regression fitting can produce predicted setpoints outside permitted ranges, the disclosed approaches can help keep control outputs within acceptable limits.

Career Highlights

Premoe is associated with Microsoft Technology Licensing, LLC. His patent reflects work at the intersection of machine learning and mechanical-system control, with a focus on managing variability in deployed AI systems.

Collaborations

Brendan Lee Bryant is identified as Premoe’s coworker. The provided information does not specify their roles or describe a particular joint project.

Conclusion

Chris Allen Premoe’s patent addresses practical ways to manage short- and long-term variability in AI agents controlling mechanical systems, highlighting reliability as a key concern in deployed artificial intelligence.