公开(公告)号：US20190236740A1

公开(公告)日：2019-08-01

申请号：US15885492

申请日：2018-01-31

Applicant: Maplebear, Inc. (dba Instacart)

Inventor： Sharath Rao ,  Shishir Prasad ,  Jeremy Stanley

IPC: G06Q50/28 ,  G06N99/00 ,  G06N7/00 ,  G06Q10/06

CPC classification number: G06Q50/28 ,  G06N7/005 ,  G06N20/00 ,  G06Q10/06315 ,  G06Q10/067

Abstract: A method for predicting inventory availability, involving receiving a delivery order including a plurality of items and a delivery location, and identifying a warehouse for picking the plurality of items. The method retrieves a machine-learned model that predicts a probability that an item is available at the warehouse. The machine-learned model is trained, using machine learning, based in part on a plurality of datasets. The plurality of datasets include data describing items included in previous delivery orders, whether each item in each previous delivery order was picked, a warehouse associated with each previous delivery order, and a plurality of characteristics associated with each of the items. The method predicts the probability that one of the plurality of items in the delivery order is available at the warehouse, and generates an instruction to a picker based on the probability. An instruction is transmitted to a mobile device of the picker.

公开(公告)号：US11544810B2

公开(公告)日：2023-01-03

申请号：US15885492

申请日：2018-01-31

Applicant: Maplebear, Inc.

Inventor： Sharath Rao ,  Shishir Prasad ,  Jeremy Stanley

IPC: G06Q50/28 ,  G06Q10/06 ,  G06Q10/08

Abstract: A method for predicting inventory availability, involving receiving a delivery order including a plurality of items and a delivery location, and identifying a warehouse for picking the plurality of items. The method retrieves a machine-learned model that predicts a probability that an item is available at the warehouse. The machine-learned model is trained, using machine learning, based in part on a plurality of datasets. The plurality of datasets include data describing items included in previous delivery orders, whether each item in each previous delivery order was picked, a warehouse associated with each previous delivery order, and a plurality of characteristics associated with each of the items. The method predicts the probability that one of the plurality of items in the delivery order is available at the warehouse, and generates an instruction to a picker based on the probability. An instruction is transmitted to a mobile device of the picker.

公开(公告)号：US20230113122A1

公开(公告)日：2023-04-13

申请号：US18080118

申请日：2022-12-13

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Sharath Rao ,  Shishir Prasad ,  Jeremy Stanley

IPC: G06Q10/087 ,  G06Q10/0631 ,  G06Q10/067

Abstract: A method for predicting inventory availability, involving receiving a delivery order including a plurality of items and a delivery location, and identifying a warehouse for picking the plurality of items. The method retrieves a machine-learned model that predicts a probability that an item is available at the warehouse. The machine-learned model is trained, using machine learning, based in part on a plurality of datasets. The plurality of datasets include data describing items included in previous delivery orders, whether each item in each previous delivery order was picked, a warehouse associated with each previous delivery order, and a plurality of characteristics associated with each of the items. The method predicts the probability that one of the plurality of items in the delivery order is available at the warehouse, and generates an instruction to a picker based on the probability. An instruction is transmitted to a mobile device of the picker.