公开(公告)号：US20250078025A1

公开(公告)日：2025-03-06

申请号：US18952836

申请日：2024-11-19

Applicant: Maplebear Inc.

Inventor： Jeremy Stanley ,  Montana Low ,  Nima Zahedi

IPC: G06Q10/087 ,  G06N3/04 ,  G06N3/08 ,  G06N5/01 ,  G06N20/20

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.

公开(公告)号：US20190236525A1

公开(公告)日：2019-08-01

申请号：US15882934

申请日：2018-01-29

Applicant: Maplebear, Inc. (dba Instacart)

Inventor： Jeremy Stanley ,  Montana Low ,  Nima Zahedi

IPC: G06Q10/08 ,  G06N3/08

CPC classification number: G06Q10/087 ,  G06N3/08

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.

公开(公告)号：US12182760B2

公开(公告)日：2024-12-31

申请号：US18236575

申请日：2023-08-22

Applicant: Maplebear Inc.

Inventor： Jeremy Stanley ,  Montana Low ,  Nima Zahedi

IPC: G06Q10/087 ,  G06N3/04 ,  G06N3/08 ,  G06N5/01 ,  G06N20/20

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.

公开(公告)号：US20230394432A1

公开(公告)日：2023-12-07

申请号：US18236575

申请日：2023-08-22

Applicant: Maplebear Inc.

Inventor： Jeremy Stanley ,  Montana Low ,  Nima Zahedi

IPC: G06Q10/087 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06N5/01

CPC classification number: G06Q10/087 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06N5/01

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.

公开(公告)号：US11775926B2

公开(公告)日：2023-10-03

申请号：US15882934

申请日：2018-01-29

Applicant: Maplebear, Inc.

Inventor： Jeremy Stanley ,  Montana Low ,  Nima Zahedi

IPC: G06Q10/087 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06N5/01

CPC classification number: G06Q10/087 ,  G06N3/04 ,  G06N3/08 ,  G06N5/01 ,  G06N20/20

Abstract: An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.