Amazon Technologies, Inc.

Karthik Ram Srinivasan

Shao-Wen Yang

Amber Roy Chowdhury

Zheng Wang

Tarun Bhatia

Valerie Galluzzi Liptak

Brian Michael Rock

Badrinath Gurappa Srinivas

Bettina Cornelia Sehorsch

Techniques for triggering a mitigation action based on an artificial intelligence (AI) model-based delivery defect prediction are described. In an example, a computer system determines contextual information associated with a stage of a delivery flow of an item to a delivery location. The computer system generates an input based at least in part on the contextual information and provides the input to an AI model trained to predict delivery defect information at delivery flow stages. The computer system determines, based at least in part on an output of the artificial intelligence model, a predicted delivery defect associated with the stage of the delivery flow. The computer system determining a mitigation action based at least in part on the predicted delivery defect and causing the mitigation action to be performed.

Triggering a mitigation action based on an artificial intelligence model-based delivery defect prediction

Artificial intelligence (AI) models for verifying packing removed deliveries are described herein. In an example, a computer system receives image data corresponding to a portion of a delivery location. The computer system determines an indication of at least one delivery object in the portion. The computer system inputs the indication into a first AI model trained for detecting entity-associated packaging associated with the at least one delivery object. The computer system receives, from the first AI model, an output of whether the at least one delivery object includes the entity-associated packaging. The computer system causes a first presentation about the output to be provided at a device.

Artificial intelligence models for verification of packaging removed deliveries

A system can be configured to receive and analyze an image captured by a user device at a delivery location. The system can utilize local algorithms tailored to the delivery location to confirm that the delivery location is the intended delivery location for a package. The system can utilize global algorithms to generate three-dimensional models of the delivery environment and an augmented reality interface providing delivery instructions to the deliverer. The delivery instructions include indications of approved delivery locations and rejected delivery locations associated with the general delivery location of the customer. The delivery instructions and the user device can be utilized to ensure package placement for secure delivery to a customer.

Location-based package drop-off instructions

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Bellevue, WA, United States of America

Karthik Ram Srinivasan