公开(公告)号：US20250124498A1

公开(公告)日：2025-04-17

申请号：US18917136

申请日：2024-10-16

Applicant: Maplebear Inc.

Inventor： Prithvishankar Srinivasan ,  Shishir Kumar Prasad ,  Min Xie ,  Shrikar Archak ,  Shih-Ting Lin ,  Haixun Wang

IPC: G06Q30/08 ,  G06Q30/0601

Abstract: An online system presents a sponsored content page to a user in conjunction with a model serving system. The online system accesses a content page for a food item and identifies one or more sponsorship opportunities at the content page. The online system identifies one or more candidate sponsors for each sponsorship opportunity. The online system selects a bidding sponsor for the sponsorship opportunity from the one or more candidate sponsors and a candidate item associated with the bidding sponsor as a sponsored item. The online system provides a content page, a description of the sponsored item, and a request to generate a sponsored content page for the sponsorship opportunity to a model serving system. The online system receives a sponsored content page generated by a machine-learning language model at the model serving system and presents the sponsored content page to a user.

公开(公告)号：US20250078101A1

公开(公告)日：2025-03-06

申请号：US18954374

申请日：2024-11-20

Applicant: Maplebear Inc.

Inventor： Tejaswi Tenneti ,  Tyler Russell Tate ,  Jonathan Lennart Bender ,  Shishir Kumar Prasad ,  Qingyuan Chen

IPC: G06Q30/0201 ,  G06F16/901 ,  G06F16/9535 ,  G06Q30/0601

Abstract: An online concierge system suggests subsequent search queries based on previous search queries and whether the previous search queries resulted in conversions. The online concierge system trains a machine learning model using previous delivery orders and whether initial and subsequent search queries in the previous delivery orders resulted in conversions. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies items related to the search query. In response to the search query resulting in a conversion, the online concierge system retrieves a conversion graph and presents a suggested subsequent search query based on the conversion graph. In response to the search query not resulting in a conversion, the online concierge system retrieves a non-conversion graph and presents a suggested subsequent search query based on the non-conversion graph.

公开(公告)号：US20250078056A1

公开(公告)日：2025-03-06

申请号：US18240719

申请日：2023-08-31

Applicant: Maplebear Inc.

Inventor： Aoshi Li ,  Prithvishankar Srinivasan ,  Shang Li ,  Mengyu Zhang ,  Daniel Haugh ,  Cheryl D’Souza ,  Syed Wasi Hasan Rizvi ,  William Halbach ,  Ziwei Shi ,  Annie Zhang ,  Giovanny Castro ,  Sonali Parthasarathy ,  Shishir Kumar Prasad

IPC: G06Q20/14 ,  G06Q10/087 ,  G06Q30/0601

Abstract: An online concierge system compensates pickers who fulfill orders including one or more items based in part on weights of the items included in an order. Because the online concierge system does not physically possess the items that are obtained, the online concierge system cannot directly weigh the items and weights specified for items in a catalog from a retailer may be inaccurate. To more accurately determine weights of items, the online concierge system trains a weight prediction model to estimate an item's weight from attributes of the item and uses the output of the weight prediction model to determine compensation to a picker. The weight prediction model may output a predicted weight of an item or a classification of the item as heavy or light. Where discrepancies are found between a predicted weight and the catalog weight of an item, additional information about the item is obtained.

公开(公告)号：US20240403938A1

公开(公告)日：2024-12-05

申请号：US18326900

申请日：2023-05-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Tilman Drerup ,  Shishir Kumar Prasad ,  Zoheb Hajiyani ,  Luis Manrique

IPC: G06Q30/0601 ,  G06N20/00

Abstract: An online system predicts replacement items for presentation to a user using a machine-learning model. The online system receives interaction data describing a user's interaction with the online system. In particular, the interaction data describes an initial item that the user added to their item list. The online system identifies a set of candidate items that could be presented to the user as potential replacements for the initially-added item. The online system applies a replacement prediction model to each of these candidate items to generate a replacement score for the candidate items. The online system selects a proposed replacement item and transmits that item to the user's client device for display to the user. If the user selects the proposed replacement item, the online concierge system replaces the initial item with the proposed replacement item in the user's item list.

公开(公告)号：US12002084B2

公开(公告)日：2024-06-04

申请号：US18218967

申请日：2023-07-06

Applicant: Maplebear Inc.

Inventor： Shishir Kumar Prasad ,  Sharath Rao Karikurve ,  Diego Goyret

IPC: G06Q30/0601 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0204

CPC classification number: G06Q30/0639 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0205 ,  G06Q30/0619 ,  G06Q30/0629 ,  G06Q30/0633

Abstract: An online concierge system allows users to order items from a warehouse having multiple physical locations, allowing a user to order items at any given warehouse location. To select a warehouse location for a warehouse selected by a user, the online concierge system identifies a set of items that the user has a threshold likelihood of purchasing from prior orders by the user. For each of a set of warehouse locations, the online concierge system applies a machine-learned item availability model to each item of the identified set. From the availabilities of items of the set at each warehouse location of the set, the online concierge system selects a warehouse location. The online concierge system identifies an inventory of items from the selected warehouse location to the user for inclusion in an order.

公开(公告)号：US20230351480A1

公开(公告)日：2023-11-02

申请号：US18218967

申请日：2023-07-06

Applicant: Maplebear Inc.

Inventor： Shishir Kumar Prasad ,  Sharath Rao Karikurve ,  Diego Goyret

IPC: G06Q30/0601 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0204 ,  G06N5/04 ,  G06N20/00

CPC classification number: G06Q30/0639 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/087 ,  G06Q30/0201 ,  G06Q30/0205 ,  G06Q30/0619 ,  G06Q30/0629 ,  G06Q30/0633

Abstract: An online concierge system allows users to order items from a warehouse having multiple physical locations, allowing a user to order items at any given warehouse location. To select a warehouse location for a warehouse selected by a user, the online concierge system identifies a set of items that the user has a threshold likelihood of purchasing from prior orders by the user. For each of a set of warehouse locations, the online concierge system applies a machine-learned item availability model to each item of the identified set. From the availabilities of items of the set at each warehouse location of the set, the online concierge system selects a warehouse location. The online concierge system identifies an inventory of items from the selected warehouse location to the user for inclusion in an order.

公开(公告)号：US11568464B2

公开(公告)日：2023-01-31

申请号：US16815846

申请日：2020-03-11

Applicant: Maplebear, Inc.

Inventor： Shishir Kumar Prasad ,  Sharath Rao

IPC: G06Q30/06 ,  G06F16/953

Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.

公开(公告)号：US20220108333A1

公开(公告)日：2022-04-07

申请号：US17486395

申请日：2021-09-27

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Tejaswi Tenneti ,  Tyler Russell Tate ,  Jonathan Lennart Bender ,  Shishir Kumar Prasad ,  Qingyuan Chen

IPC: G06Q30/02 ,  G06F16/9535 ,  G06F16/901 ,  G06Q30/06

Abstract: An online concierge system suggests subsequent search queries based on previous search queries and whether the previous search queries resulted in conversions. The online concierge system trains a machine learning model using previous delivery orders and whether initial and subsequent search queries in the previous delivery orders resulted in conversions. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies items related to the search query. In response to the search query resulting in a conversion, the online concierge system retrieves a conversion graph and presents a suggested subsequent search query based on the conversion graph. In response to the search query not resulting in a conversion, the online concierge system retrieves a non-conversion graph and presents a suggested subsequent search query based on the non-conversion graph.

公开(公告)号：US20250037323A1

公开(公告)日：2025-01-30

申请号：US18785665

申请日：2024-07-26

Applicant: Maplebear Inc.

Inventor： Prithvishankar Srinivasan ,  Shih-Ting Lin ,  Yuanzheng Zhu ,  Min Xie ,  Shishir Kumar Prasad ,  Shrikar Archak ,  Karuna Ahuja

IPC: G06T11/00 ,  G06T5/70 ,  G06V10/764

Abstract: An online system performs a task in conjunction with the model serving system or the interface system. The system generates a first prompt for input to a machine-learned language model, which specifies contextual information and a first request to generate a theme. The system provides the first prompt to a model serving system for execution by the machine-learned language model, receives a first response, and generates a second prompt. The second prompt specifies the theme and a second request to generate a third prompt for input to an image generation model that includes a third request to generate one or more images of one or more items associated with the theme. The system receives the third prompt by executing the model on the second prompt, provides the third prompt to the image generation model, and receives one or more images for presentation.

公开(公告)号：US12169858B2

公开(公告)日：2024-12-17

申请号：US18090506

申请日：2022-12-29

Applicant: Maplebear Inc.

Inventor： Shishir Kumar Prasad ,  Sharath Rao Karikurve

IPC: G06Q30/0601 ,  G06F16/953

Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.