公开(公告)号：US20250148412A1

公开(公告)日：2025-05-08

申请号：US18500930

申请日：2023-11-02

Applicant: Maplebear Inc.

Inventor： Charles Wesley ,  Brent Scheibelhut ,  Hua Xiao

IPC: G06Q10/083 ,  G08B21/18

Abstract: A trained computer model for automatic identification of a wrong delivery location for an order placed at an online system. The online system receives, via a user interface, a user input that includes a delivery location for the order. The online system compares the received delivery location with a stored delivery location for the user. Responsive to identifying that the received and stored delivery locations are different, the online system accesses and applies a computer model to predict, based on features of the order, a likelihood of the received delivery location being correct. The online system generates, based on the predicted likelihood, a confidence score of the received delivery location being correct. Responsive to the confidence score being below a threshold score, the online system causes a device of the user to display a user interface with a message prompting the user to verify accuracy of the received delivery location.

公开(公告)号：US20250139137A1

公开(公告)日：2025-05-01

申请号：US18495581

申请日：2023-10-26

Applicant: Maplebear Inc.

Inventor： Brent Scheibelhut ,  Charles Wesley ,  Siby Alappatt ,  Benjamin Chevoor ,  Viswa Mani Kiran Peddinti

IPC: G06F16/332 ,  G06F16/335 ,  G06T7/00

Abstract: Use of a language model to automatically perform visual assessment of quality of an item being fulfilled by a picker. The online system receives an image of the item and identifies a set of potential problems associated with the item. The online system generates a plurality of prompts for input into the language model including the image and one or more questions each corresponding to a respective potential problem of the set potential problems. The online system requests the language model to generate, based on the plurality of prompts, a feedback response for each potential problem. The online system generates an aggregated output by aggregating the feedback response for each potential problem, and based on the aggregated output, a second message that identifies one or more relevant problems associated with the item. The online system causes a device of the picker to display the second message.

公开(公告)号：US20230359901A1

公开(公告)日：2023-11-09

申请号：US18306556

申请日：2023-04-25

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Syed Wasi Hasan Rizvi ,  Charles Wesley

IPC: G06N3/09

CPC classification number: G06N3/09

Abstract: An online system validates item updates using a machine-learning model to identify item updates that need independent review. The online system maintains an item database that has item entries for items on the online system. The online system receives item updates from an item update system and applies an error prediction model to the item updates to generate an error likelihood score for each item update. The online system samples a subset of the item updates based on the error likelihood scores and passes these sampled item updates to a human reviewer system. The human reviewer system labels each of the sampled item updates with an error label indicating whether the corresponding item update is actually erroneous. The online system determines whether to update the item database with the full set of received item updates based on the error labels.