公开(公告)号：US20240311749A1

公开(公告)日：2024-09-19

申请号：US18122057

申请日：2023-03-15

Applicant: X Development LLC

Inventor： Grace Taixi Brentano ,  Salil Vijaykumar Pradhan ,  Rebecca Radkoff ,  David Andre ,  Lam Thanh Nguyen ,  Sze Man Lee ,  Gearoid Murphy

IPC: G06Q10/0835 ,  G06N3/0475 ,  G06N3/092 ,  G06N3/094

CPC classification number: G06Q10/08355 ,  G06N3/0475 ,  G06N3/092 ,  G06N3/094

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating alternative networks. One of the methods includes receiving supply chain data representing a first supply chain network having nodes and links, receiving map data, providing the map data and the supply chain data as input to a generative process that is configured to generate one or more second supply chain networks, receiving, as output from the generative process, a second supply chain network, performing a supply chain simulation on the second supply chain network generated by the generative model, and computing a performance metric for the second supply chain network based on performing the simulation.

公开(公告)号：US20230117297A1

公开(公告)日：2023-04-20

申请号：US18047510

申请日：2022-10-18

Applicant: X Development LLC

Inventor： Ryan Butterfoss ,  David Andre ,  Salil Vijaykumar Pradhan ,  Rebecca Radkoff

IPC: G06F30/27 ,  G06Q10/06 ,  G06Q50/28

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatic generation of a supply chain simulation. The methods, systems, and apparatus include actions of obtaining supply chain data of a supply chain, generating a supply chain network graph that represents relationships between locations indicated by the supply chain data, determining classifications of the locations indicated by the supply chain data, determining agent rule models based on the supply chain data, and generating a supply chain simulation based on the supply chain network graph, the classifications of the locations, and the agent rule models.

公开(公告)号：US11861263B1

公开(公告)日：2024-01-02

申请号：US17846351

申请日：2022-06-22

Applicant: X Development LLC

Inventor： Thomas Hunt ,  David Andre ,  Nisarg Vyas ,  Rebecca Radkoff ,  Rishabh Singh

IPC: G06F3/0481 ,  G06F3/16 ,  G06F3/0484 ,  G10L15/22

CPC classification number: G06F3/167 ,  G06F3/0481 ,  G06F3/0484 ,  G10L15/22

Abstract: This specification is generally directed to techniques for robust natural language (NL) based control of computer applications. In many implementations, the NL control is at least selectively interactive in that the user feedback input is solicited, and received, in resolving action(s), resolving action set(s), generating domain specific knowledge, and/or in providing feedback on implemented action set(s). The user feedback input can be utilized in further training of machine learning model(s) utilized in the NL based control of the computer applications.

公开(公告)号：US20230144113A1

公开(公告)日：2023-05-11

申请号：US17984185

申请日：2022-11-09

Applicant: X Development LLC

Inventor： Salil Vijaykumar Pradhan ,  Grigory Bronevetsky ,  Ryan Butterfoss ,  Rebecca Radkoff ,  David Andre ,  Randolph Preston McAfee ,  John Michael Stivoric ,  Grace Taixi Brentano ,  Sze Man Lee

IPC: G06Q10/08 ,  G06Q10/06 ,  G06Q30/06

CPC classification number: G06Q10/08345 ,  G06Q10/067 ,  G06Q30/0611

Abstract: Methods and systems including receiving a plurality of shipping bids from a plurality of shipping entities, each entity having goods to ship from locations to destinations, wherein each bid represents an option to ship goods at a shipping price, and wherein each bid comprises a plurality of shipping parameters; receiving a plurality of carrier bids from a plurality of carrier entities, each entity transporting the goods, wherein each bid represents an option to transport the goods at a price, and wherein each bid comprises a plurality of carrier parameters; performing a matching process to generate a plurality of pair-wise partial matches, wherein each match associates a shipping and carrier bid at a modified price, wherein the modified price is based on a deviation between the parameters; providing information representing the matches to the shipping and carrier entities; and generating training data representing which matches were exercised.

公开(公告)号：US20220405489A1

公开(公告)日：2022-12-22

申请号：US17706844

申请日：2022-03-29

Applicant: X Development LLC

Inventor： Rebecca Radkoff ,  David Andre

IPC: G06F40/56 ,  G06F40/35 ,  G06V20/40

Abstract: Implementations are described herein for formulating natural language descriptions based on temporal sequences of digital images. In various implementations, a natural language input may be analyzed. Based on the analysis, a semantic scope to be imposed on a natural language description that is to be formulated based on a temporal sequence of digital images may be determined. The temporal sequence of digital images may be processed based on one or more machine learning models to identify one or more candidate features that fall within the semantic scope. One or more other features that fall outside of the semantic scope may be disregarded. The natural language description may be formulated to describe one or more of the candidate features.

公开(公告)号：US12217029B1

公开(公告)日：2025-02-04

申请号：US17889567

申请日：2022-08-17

Applicant: X Development LLC

Inventor： David Andre ,  Nisarg Vyas ,  Salil Pradhan ,  Rebecca Radkoff ,  Ryan Butterfoss ,  Falak Shah ,  Jayendra Parmar

IPC: G06F8/35 ,  G06F9/54

Abstract: This specification is generally directed to techniques for generating interfacing source code between computing components based on natural language input. In various implementations, a natural language input that requests generation of interfacing source code to logically couple a first computing component with a second computing component may be processed to generate an interface request semantic embedding. The interface request semantic embedding may be processed based on one or more domain models associated with the first and second computing components to generate a pool(s) of candidate code snippets for logically coupling with first and second computing components. A plurality of candidate instances of interfacing source code may be generated between the first and second computing components. Each candidate software interface may include a different permutation of candidate code snippets from the pool(s) of candidate code snippets.

公开(公告)号：US20240256314A1

公开(公告)日：2024-08-01

申请号：US18633322

申请日：2024-04-11

Applicant: X Development LLC

Inventor： Rebecca Radkoff ,  David Andre

IPC: G06F9/455 ,  G06F3/0482 ,  G06F3/16 ,  G06F16/33 ,  G06F16/332 ,  G06F16/9032 ,  G06F16/9535 ,  G06F40/30 ,  G06F40/35 ,  G06F40/40 ,  G06F40/58

CPC classification number: G06F9/45529 ,  G06F3/0482 ,  G06F40/30 ,  G06F3/167 ,  G06F16/3329 ,  G06F16/3344 ,  G06F16/90332 ,  G06F16/9535 ,  G06F40/35 ,  G06F40/40 ,  G06F40/58

Abstract: Disclosed implementations relate to automating semantically-similar computing tasks across multiple contexts. In various implementations, an initial natural language input and a first plurality of actions performed using a first computer application may be used to generate a first task embedding and a first action embedding in action embedding space. An association between the first task embedding and first action embedding may be stored. Later, subsequent natural language input may be used to generate a second task embedding that is then matched to the first task embedding. Based on the stored association, the first action embedding may be identified and processed using a selected domain model to select actions to be performed using a second computer application. The selected domain model may be trained to translate between an action space of the second computer application and the action embedding space.

公开(公告)号：US20220101277A1

公开(公告)日：2022-03-31

申请号：US17033512

申请日：2020-09-25

Applicant: X Development LLC

Inventor： Diosdado Rey Banatao ,  Karen R. Davis ,  Neil Treat ,  Artem Goncharuk ,  Charles Spirakis ,  Sujit Sanjeev ,  Gearoid Murphy ,  Lance Co Ting Keh ,  Rebecca Radkoff ,  Taoran Dai

IPC: G06Q10/00 ,  G06T7/00 ,  G06F16/21 ,  G06N20/00 ,  G01J3/28

Abstract: Systems and methods for managing chemical recycling processes include accessing characterization data of a feedstock, the characterization data comprising one or more spectra collected according to one or more spectroscopic methods. The methods include predicting, using the characterization data, a set of constituent materials included in the feedstock. The methods include predicting a material composition of the feedstock using the predicted set of constituent materials. The methods include identifying, at least in part using the predicted material composition of the feedstock, one or more target products. The methods include generating a set of chemical reaction schemas enabling a conversion of at least part of the feedstock into the one or more target products. The methods also include storing identifications of the material composition of the feedstock, the one or more target products, and the set of chemical reaction schemas in a data store.

公开(公告)号：US11983554B2

公开(公告)日：2024-05-14

申请号：US17726258

申请日：2022-04-21

Applicant: X Development LLC

Inventor： Rebecca Radkoff ,  David Andre

IPC: G06F16/242 ,  G06F3/0482 ,  G06F3/0488 ,  G06F9/455 ,  G06F40/30 ,  G06F3/16 ,  G06F16/33 ,  G06F16/332 ,  G06F16/9032 ,  G06F16/9535 ,  G06F40/35 ,  G06F40/40 ,  G06F40/58

CPC classification number: G06F9/45529 ,  G06F3/0482 ,  G06F40/30 ,  G06F3/167 ,  G06F16/3329 ,  G06F16/3344 ,  G06F16/90332 ,  G06F16/9535 ,  G06F40/35 ,  G06F40/40 ,  G06F40/58

Abstract: Disclosed implementations relate to automating semantically-similar computing tasks across multiple contexts. In various implementations, an initial natural language input and a first plurality of actions performed using a first computer application may be used to generate a first task embedding and a first action embedding in action embedding space. An association between the first task embedding and first action embedding may be stored. Later, subsequent natural language input may be used to generate a second task embedding that is then matched to the first task embedding. Based on the stored association, the first action embedding may be identified and processed using a selected domain model to select actions to be performed using a second computer application. The selected domain model may be trained to translate between an action space of the second computer application and the action embedding space.

公开(公告)号：US20230359789A1

公开(公告)日：2023-11-09

申请号：US18142472

申请日：2023-05-02

Applicant: X Development LLC

Inventor： David Andre ,  Rishabh Singh ,  Rebecca Radkoff ,  Yu-Ann Madan ,  Nisarg Vyas ,  Jayendra Parmar ,  Falak Shah ,  Shaili Trivedi

IPC: G06F30/27 ,  G10L15/183

CPC classification number: G06F30/27 ,  G10L15/183

Abstract: As opposed to a rigid approach, implementations disclosed herein utilize a flexible approach in automatically determining an action set to utilize in attempting performance of a task that is requested by natural language input of a user. The approach is flexible at least in that embedding technique(s) and/or action model(s), that are utilized in generating action set(s) from which the action set to utilize is determined, are at least selectively varied. Put another way, implementations leverage a framework via which different embedding technique(s) and/or different action model(s) can at least selectively be utilized in generating different candidate action sets for given NL input of a user. Further, one of those action sets can be selected for actual use in attempting real-world performance of a given task reflected by the given NL input. The selection can be based on a suitability metric for the selected action set and/or other considerations.