公开(公告)号：US12020706B2

公开(公告)日：2024-06-25

申请号：US17899162

申请日：2022-08-30

Applicant: GOOGLE LLC

Inventor： Arvind Neelakantan ,  Daniel Duckworth ,  Ben Goodrich ,  Vishaal Prasad ,  Chinnadhurai Sankar ,  Semih Yavuz

IPC: G10L15/22 ,  G06N5/04

CPC classification number: G10L15/22 ,  G06N5/04 ,  G10L2015/225

Abstract: Training and/or utilizing a single neural network model to generate, at each of a plurality of assistant turns of a dialog session between a user and an automated assistant, a corresponding automated assistant natural language response and/or a corresponding automated assistant action. For example, at a given assistant turn of a dialog session, both a corresponding natural language response and a corresponding action can be generated jointly and based directly on output generated using the single neural network model. The corresponding response and/or corresponding action can be generated based on processing, using the neural network model, dialog history and a plurality of discrete resources. For example, the neural network model can be used to generate a response and/or action on a token-by-token basis.

公开(公告)号：US10963779B2

公开(公告)日：2021-03-30

申请号：US15349955

申请日：2016-11-11

Applicant: Google LLC

Inventor： Quoc V. Le ,  Ilya Sutskever ,  Arvind Neelakantan

IPC: G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing operations using data from a data source. In one aspect, a method includes a neural network system including a controller neural network configured to: receive a controller input for a time step and process the controller input and a representation of a system input to generate: an operation score distribution that assigns a respective operation score to an operation and a data score distribution that assigns a respective data score in the data source. The neural network system can also include an operation subsystem configured to: perform operations to generate operation outputs, wherein at least one of the operations is performed on data in the data source, and combine the operation outputs in accordance with the operation score distribution and the data score distribution to generate a time step output for the time step.

公开(公告)号：US20240347061A1

公开(公告)日：2024-10-17

申请号：US18751911

申请日：2024-06-24

Applicant: GOOGLE LLC

Inventor： Arvind Neelakantan ,  Daniel Duckworth ,  Ben Goodrich ,  Vishaal Prasad ,  Chinnadhurai Sankar ,  Semih Yavuz

IPC: G10L15/22 ,  G06N5/04

CPC classification number: G10L15/22 ,  G06N5/04 ,  G10L2015/225

Abstract: Training and/or utilizing a single neural network model to generate, at each of a plurality of assistant turns of a dialog session between a user and an automated assistant, a corresponding automated assistant natural language response and/or a corresponding automated assistant action. For example, at a given assistant turn of a dialog session, both a corresponding natural language response and a corresponding action can be generated jointly and based directly on output generated using the single neural network model. The corresponding response and/or corresponding action can be generated based on processing, using the neural network model, dialog history and a plurality of discrete resources. For example, the neural network model can be used to generate a response and/or action on a token-by-token basis.

公开(公告)号：US20220415324A1

公开(公告)日：2022-12-29

申请号：US17899162

申请日：2022-08-30

Applicant: GOOGLE LLC

Inventor： Arvind Neelakantan ,  Daniel Duckworth ,  Ben Goodrich ,  Vishaal Prasad ,  Chinnadhurai Sankar ,  Semih Yavuz

IPC: G10L15/22 ,  G06N5/04

Abstract: Training and/or utilizing a single neural network model to generate, at each of a plurality of assistant turns of a dialog session between a user and an automated assistant, a corresponding automated assistant natural language response and/or a corresponding automated assistant action. For example, at a given assistant turn of a dialog session, both a corresponding natural language response and a corresponding action can be generated jointly and based directly on output generated using the single neural network model. The corresponding response and/or corresponding action can be generated based on processing, using the neural network model, dialog history and a plurality of discrete resources. For example, the neural network model can be used to generate a response and/or action on a token-by-token basis.

公开(公告)号：US11475890B2

公开(公告)日：2022-10-18

申请号：US16910435

申请日：2020-06-24

Applicant: Google LLC

Inventor： Arvind Neelakantan ,  Daniel Duckworth ,  Ben Goodrich ,  Vishaal Prasad ,  Chinnadhurai Sankar ,  Semih Yavuz

IPC: G10L15/22 ,  G06N5/04

Abstract: Training and/or utilizing a single neural network model to generate, at each of a plurality of assistant turns of a dialog session between a user and an automated assistant, a corresponding automated assistant natural language response and/or a corresponding automated assistant action. For example, at a given assistant turn of a dialog session, both a corresponding natural language response and a corresponding action can be generated jointly and based directly on output generated using the single neural network model. The corresponding response and/or corresponding action can be generated based on processing, using the neural network model, dialog history and a plurality of discrete resources. For example, the neural network model can be used to generate a response and/or action on a token-by-token basis.