公开(公告)号：US20210069986A1

公开(公告)日：2021-03-11

申请号：US16605838

申请日：2019-09-10

Applicant: Google LLC

Inventor： Sharon Stovezky ,  Yariv Adan ,  Radu Voroneanu ,  Behshad Behzadi ,  Ragnar Groot Koerkamp ,  Marcin Nowak-Przygodzki

IPC: B29C64/393 ,  B29C64/295 ,  B33Y70/00 ,  B33Y10/00 ,  B33Y30/00

Abstract: In various embodiments, the invention relates to poly(propylene fumarate) (PPF)-based star-shaped copolymers synthesized using a core-first approach that uses a multi-functional alcohols as an initiator, and Mg(BHT)2(THF)2 as catalyst for controlled ring opening copolymerization (ROCOP) of maleic anhydride (MAn) with propylene oxide (PO). In some embodiments, these star-PPF copolymers have lower viscosities than their linear analogs, allowing a decrease in DEF fraction in resin formulation, as well as the use of higher molecular weights. These star-shape PPF can be used to prepare PPF:DEF resins containing as much as 70% by weight of the multi-arm PPF star copolymers, and have a low complex viscosity of high Mn star PPF resin that affords rapid printing with a Mn nearly eight times larger than the largest linear PPF oligomer printed previously.

公开(公告)号：US20200302924A1

公开(公告)日：2020-09-24

申请号：US16343285

申请日：2019-02-07

Applicant: Google LLC

Inventor： Mugurel Ionut Andreica ,  Vladimir Vuskovic ,  Joseph Lange ,  Sharon Stovezky ,  Marcin Nowak-Przygodzki

IPC: G10L15/22 ,  G10L15/02 ,  G06N3/08

Abstract: Implementations are set forth herein for creating an order of execution for actions that were requested by a user, via a spoken utterance to an automated assistant. The order of execution for the requested actions can be based on how each requested action can, or is predicted to, affect other requested actions. In some implementations, an order of execution for a series of actions can be determined based on an output of a machine learning model, such as a model that has been trained according to supervised learning. A particular order of execution can be selected to mitigate waste of processing, memory, and network resources—at least relative to other possible orders of execution. Using interaction data that characterizes past performances of automated assistants, certain orders of execution can be adapted over time, thereby allowing the automated assistant to learn from past interactions with one or more users.

公开(公告)号：US12175747B2

公开(公告)日：2024-12-24

申请号：US17888163

申请日：2022-08-15

Applicant: GOOGLE LLC

Inventor： Marcin Nowak-Przygodzki ,  Gökhan Bakir

IPC: G06V20/20 ,  G06F3/01 ,  G06F3/0482 ,  G06F3/04886 ,  G06F16/487 ,  G06F16/9032 ,  G06Q30/02 ,  G06V20/68 ,  H04N23/63 ,  H04N23/667

Abstract: Techniques described herein enable a user to interact with an automated assistant and obtain relevant output from the automated assistant without requiring arduous typed input to be provided by the user and/or without requiring the user to provide spoken input that could cause privacy concerns (e.g., if other individuals are nearby). The assistant application can operate in multiple different image conversation modes in which the assistant application is responsive to various objects in a field of view of the camera. The image conversation modes can be suggested to the user when a particular object is detected in the field of view of the camera. When the user selects an image conversation mode, the assistant application can thereafter provide output, for presentation, that is based on the selected image conversation mode and that is based on object(s) captured by image(s) of the camera.

公开(公告)号：US12118998B2

公开(公告)日：2024-10-15

申请号：US18231112

申请日：2023-08-07

Applicant: GOOGLE LLC

Inventor： Mugurel Ionut Andreica ,  Vladimir Vuskovic ,  Joseph Lange ,  Sharon Stovezky ,  Marcin Nowak-Przygodzki

IPC: G10L15/22 ,  G06N3/08 ,  G10L15/02

CPC classification number: G10L15/22 ,  G06N3/08 ,  G10L15/02 ,  G10L2015/223

Abstract: Implementations are set forth herein for creating an order of execution for actions that were requested by a user, via a spoken utterance to an automated assistant. The order of execution for the requested actions can be based on how each requested action can, or is predicted to, affect other requested actions. In some implementations, an order of execution for a series of actions can be determined based on an output of a machine learning model, such as a model that has been trained according to supervised learning. A particular order of execution can be selected to mitigate waste of processing, memory, and network resources—at least relative to other possible orders of execution. Using interaction data that characterizes past performances of automated assistants, certain orders of execution can be adapted over time, thereby allowing the automated assistant to learn from past interactions with one or more users.

公开(公告)号：US12106759B2

公开(公告)日：2024-10-01

申请号：US17588481

申请日：2022-01-31

Applicant: Google LLC

Inventor： Denis Burakov ,  Behshad Behzadi ,  Mario Bertschler ,  Bohdan Vlasyuk ,  Daniel Cotting ,  Michael Golikov ,  Lucas Mirelmann ,  Steve Cheng ,  Sergey Nazarov ,  Zaheed Sabur ,  Marcin Nowak-Przygodzki ,  Mugurel Ionut Andreica ,  Radu Voroneanu

IPC: G10L15/22 ,  G06F3/16 ,  G10L15/26

CPC classification number: G10L15/26 ,  G06F3/167 ,  G10L15/22 ,  G10L2015/223

Abstract: Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.

公开(公告)号：US20240232272A1

公开(公告)日：2024-07-11

申请号：US18612174

申请日：2024-03-21

Applicant: GOOGLE LLC

Inventor： Gökhan Bakir ,  Andre Elisseeff ,  Torsten Marek ,  João Paulo Pagaime da Silva ,  Mathias Carlen ,  Dana Ritter ,  Lukasz Suder ,  Ernest Galbrun ,  Matthew Stokes ,  Marcin Nowak-Przygodzki ,  Mugurel-Ionut Andreica ,  Marius Dumitran

IPC: G06F16/9535 ,  G06F16/9032

CPC classification number: G06F16/9535 ,  G06F16/90332

Abstract: Implementations are described herein for analyzing existing interactive web sites to facilitate automatic engagement with those web sites, e.g., by automated assistants or via other user interfaces, with minimal effort from the hosts of those websites. For example, in various implementations, techniques described herein may be used to abstract, validate, maintain, generalize, extend and/or distribute individual actions and “traces” of actions that are useable to navigate through various interactive websites. Additionally, techniques are described herein for leveraging these actions and/or traces to automate aspects of interaction with a third party website. For example, in some implementations, techniques described herein may enable users to engage with an automated assistant (via a spoken or typed dialog session) to interact with the third party website without requiring the user to visually interact with the third party web site directly and without requiring the third party to implement their own third party agent.

公开(公告)号：US11971936B2

公开(公告)日：2024-04-30

申请号：US17974086

申请日：2022-10-26

Applicant: GOOGLE LLC

Inventor： Gökhan Bakir ,  Andre Elisseeff ,  Torsten Marek ,  João Paulo Pagaime da Silva ,  Mathias Carlen ,  Dana Ritter ,  Lukasz Suder ,  Ernest Galbrun ,  Matthew Stokes ,  Marcin Nowak-Przygodzki ,  Mugurel-Ionut Andreica ,  Marius Dumitran

IPC: G06F16/00 ,  G06F16/9032 ,  G06F16/9535

CPC classification number: G06F16/9535 ,  G06F16/90332

Abstract: Implementations are described herein for analyzing existing interactive web sites to facilitate automatic engagement with those web sites, e.g., by automated assistants or via other user interfaces, with minimal effort from the hosts of those websites. For example, in various implementations, techniques described herein may be used to extract, validate, maintain, generalize, extend and/or distribute individual actions and “traces” of actions that are useable to navigate through various interactive websites. Additionally, techniques are described herein for leveraging these actions and/or traces to automate aspects of interaction with a third party website. For example, in some implementations, techniques described herein may enable users to engage with an automated assistant (via a spoken or typed dialog session) to interact with the third party website without requiring the user to visually interact with the third party web site directly and without requiring the third party to implement their own third party agent.

公开(公告)号：US11900944B2

公开(公告)日：2024-02-13

申请号：US17588481

申请日：2022-01-31

Applicant: Google LLC

Inventor： Denis Burakov ,  Behshad Behzadi ,  Mario Bertschler ,  Bohdan Vlasyuk ,  Daniel Cotting ,  Michael Golikov ,  Lucas Mirelmann ,  Steve Cheng ,  Sergey Nazarov ,  Zaheed Sabur ,  Marcin Nowak-Przygodzki ,  Mugurel Ionut Andreica ,  Radu Voroneanu

IPC: G10L15/22 ,  G10L15/26 ,  G06F3/16

CPC classification number: G10L15/26 ,  G06F3/167 ,  G10L15/22 ,  G10L2015/223

Abstract: Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.

公开(公告)号：US20240046929A1

公开(公告)日：2024-02-08

申请号：US18382353

申请日：2023-10-20

Applicant: GOOGLE LLC

Inventor： Joseph Lange ,  Marcin Nowak-Przygodzki

IPC: G10L15/22

CPC classification number: G10L15/22

Abstract: Implementations set forth herein relate to an automated assistant that can operate as an interface between a user and a separate application to search application content of the separate application. The automated assistant can interact with existing search filter features of another application and can also adapt in circumstances when certain filter parameters are not directly controllable at a search interface of the application. For instance, when a user requests that a search operation be performed using certain terms, those terms may refer to content filters that may not be available at a search interface of the application. However, the automated assistant can generate an assistant input based on those content filters in order to ensure that any resulting search results will be filtered accordingly. The assistant input can then be submitted into a search field of the application and a search operation can be executed.

公开(公告)号：US11568146B2

公开(公告)日：2023-01-31

申请号：US16605838

申请日：2019-09-10

Applicant: Google LLC

Inventor： Sharon Stovezky ,  Yariv Adan ,  Radu Voroneanu ,  Behshad Behzadi ,  Ragnar Groot Koerkamp ,  Marcin Nowak-Przygodzki

IPC: G06F40/295 ,  G06F16/9537

Abstract: Implementations set forth herein relate to an automated assistant that operates according to a variety of different location-based biasing modes for rendering responsive content for a user and/or proactively suggesting content for the user. The user can provide condensed spoken utterances to the automated assistant, when the automated assistant is operating according to one or more location-based biasing modes, but nonetheless receive accurate responsive outputs from the automated assistant. A responsive output generated by biasing toward a subset of location characteristic data that has been prioritized over other subsets of location characteristic data. The biasing allows the automated assistant to compensate for any details that may be missing from a spoken utterance, but allows the user to provide shorter spoken utterances, thereby reducing an amount of language processing when processing inputs from the user.