Clyde Simmons Manuel

Title: Clyde Simmons Manuel and Machine-Learning-Based Order Management

Introduction

Clyde Simmons Manuel is an inventor associated with Northfield, Ohio, and Maplebear Inc. His patent work concerns using machine learning to predict when a variable-state item will change state while an order is being serviced.

Latest Patents

Manuel is credited with 1 patent: “Using Trained Machine-Learning Model of an Online System to Predict Timing of State Change of Variable State Item.” The invention describes an online system that analyzes information about an item and ambient conditions to estimate when the item’s state will change at a source location. Based on that prediction, the system generates a control signal to initiate and carry out an action related to the order, the item, or both.

Career Highlights

Manuel’s listed patent reflects an application of machine learning to operational decision-making. By predicting a state change and using that estimate to guide actions, the system is designed to coordinate order servicing with the changing condition of an item.

Collaborations

Manuel’s listed coworkers include Brent Scheibelhut and Sara Starck. His patent is associated with Maplebear Inc.

Conclusion

Clyde Simmons Manuel’s patent focuses on using machine-learning predictions to support timely actions in online order servicing.