公开(公告)号：US20240070393A1

公开(公告)日：2024-02-29

申请号：US17821889

申请日：2022-08-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shishir Kumar Prasad ,  Cameron Nicholas Taylor ,  John Salaveria ,  Joey Loi ,  Kevin McCullough

IPC: G06F40/284 ,  G06Q30/06

CPC classification number: G06F40/284 ,  G06Q30/0621

Abstract: An online concierge system generates suggested instructions for presentation to a user. The online concierge system access instruction examples corresponding to a target item category and generates candidate instruction representations based on instruction messages within each instruction example. The online concierge system generates preliminary scores for the candidate instruction representations that are directly related to an intra-category frequency of use of the instruction tokens of the candidate instruction representation within the target item category. The online system normalizes these preliminary scores for the candidate instruction representations based on the inter-category frequency of use of the instruction tokens in all item categories to generate final scores for the candidate instruction representations. The online concierge system selects a set of instruction representations based on these final scores and generates suggested instructions based on the set of instruction representations.

公开(公告)号：US11734749B2

公开(公告)日：2023-08-22

申请号：US17230816

申请日：2021-04-14

Applicant: Maplebear, Inc.

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

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

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：US20250139106A1

公开(公告)日：2025-05-01

申请号：US18933807

申请日：2024-10-31

Applicant: Maplebear Inc.

Inventor： Sharath Rao Karikurve ,  Shrikar Archak ,  Shishir Kumar Prasad

IPC: G06F16/2457 ,  G06F16/248

Abstract: An online system performs an atypical replacement recommendation task in conjunction with a model serving system or the interface system to make recommendations to a user for replacing a target item with an atypical replacement item. The online system receives a search query from a user and identifies a target item based on the search query. The online system identifies a set of candidate items for replacing the target item. The online system may select one or more atypical replacement items in the set of candidate items, and generate an explanation for each atypical replacement item. The explanation provides a reason for using the atypical replacement item to replace the target item. The online system provides the atypical replacement items and the corresponding explanations as a response to the search query.

公开(公告)号：US20250095046A1

公开(公告)日：2025-03-20

申请号：US18888607

申请日：2024-09-18

Applicant: Maplebear Inc.

Inventor： Shih-Ting Lin ,  Saurav Manchanda ,  Prithvishankar Srinivasan ,  Shishir Kumar Prasad ,  Min Xie ,  Benwen Sun ,  Axel Mange ,  Wenjie Tang ,  Sanchit Gupta

IPC: G06Q30/0601 ,  G06Q10/0833 ,  G06Q30/0201

Abstract: An online system obtains a target food from an order for a user and alcohol preferences from an order purchase history. The online system generates a prompt for a machine learning model to request alcohol candidates based on the target food category. The prompt includes the alcohol preferences, and requests for each alcohol candidate, a pairing score indicating how well the target food category pairs with the alcohol candidate and a user preference score indicating how well the alcohol candidate aligns with the alcohol preferences. The online system receives as output the candidate alcohol items. Each alcohol candidate has the pairing score, the user preference score, and a textual reason for scores. The online system matches at least one alcohol item from a catalog with each alcohol candidate. A subset of alcohol items is presented to the user as a carousel.

公开(公告)号：US20250095044A1

公开(公告)日：2025-03-20

申请号：US18965973

申请日：2024-12-02

Applicant: Maplebear Inc. (dba Instacart)

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.

公开(公告)号：US20250069298A1

公开(公告)日：2025-02-27

申请号：US18236346

申请日：2023-08-21

Applicant: Maplebear Inc.

Inventor： Prithvishankar Srinivasan ,  Shih-Ting Lin ,  Min Xie ,  Shishir Kumar Prasad ,  Yuanzheng Zhu ,  Katie Ann Forbes

IPC: G06T11/60 ,  G06F16/55 ,  G06F16/583 ,  G06Q30/0601 ,  G06T11/20

Abstract: An online concierge system trains a fine-tuned generative image model for distinct categories of items based on a generative image model that takes a textual query as input and outputs and an associated image. Training of the fine-tuned generative image model is additionally based on a small set of representative images associated with the various categories, as well as textual tokens associated with the categories. Once trained, the fine-tuned generative image model can be used to generate realistic representative images for items in a database of the online concierge system that are lacking associated images. The fine-tuned model permits the generation of different variants of an item, such as different quantities or amounts, different packaging or packing density, and the like.

公开(公告)号：US12175482B2

公开(公告)日：2024-12-24

申请号：US17486395

申请日：2021-09-27

Applicant: Maplebear Inc.

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

IPC: G06Q10/00 ,  G06F16/901 ,  G06F16/9535 ,  G06Q30/0201 ,  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：US20240303711A1

公开(公告)日：2024-09-12

申请号：US18596592

申请日：2024-03-05

Applicant: Maplebear Inc.

Inventor： Li Tan ,  Tejaswi Tenneti ,  Shishir Kumar Prasad ,  Huapu Pan ,  Allan Stewart ,  Taesik Na ,  Tyler Russell Tate ,  Joshua Roberts ,  Haixun Wang

IPC: G06Q30/0601 ,  G06F16/9532

CPC classification number: G06Q30/0627 ,  G06F16/9532 ,  G06Q30/0635

Abstract: A system, for example, an online system uses a machine learning based language model, for example, a large language model (LLM) to process high-level natural language queries received from users. The system receives a natural language query from a user of a client device. The system determines contextual information associated with the query. Based on this information, the system generates a prompt for the machine learning based language model. The system receives a response from the machine learning based language model. The system uses the response to generate a search query for a database. The system obtains results returned by the database in response to the search query and provides them to the user. The system allows users to specify high level natural language queries to obtain relevant search results, thereby improving the overall user experience.

公开(公告)号：US20240289862A1

公开(公告)日：2024-08-29

申请号：US18587668

申请日：2024-02-26

Applicant: Maplebear Inc.

Inventor： Haixun Wang ,  Shishir Kumar Prasad ,  Tejaswi Tenneti ,  Li Tan

IPC: G06Q30/0601 ,  G06N5/04

CPC classification number: G06Q30/0631 ,  G06N5/04

Abstract: An online system performs an inference task in conjunction with the model serving system to infer one or more purposes of the order of a user that includes a list of ordered items. The model serving system may host a machine-learned language model, and in one instance, the machine-learned language model is a large language model. The online system generates recommendations to the user based on the inferred purpose of the order. The online system may generate one or more recommendations that are equivalent orders having the same or similar purpose as the existing order.

公开(公告)号：US20220335505A1

公开(公告)日：2022-10-20

申请号：US17230816

申请日：2021-04-14

Applicant: Maplebear, Inc.(dba Instacart)

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

IPC: G06Q30/06 ,  G06Q10/08 ,  G06Q30/02 ,  G06N20/00 ,  G06N5/04

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.