The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 05, 2024

Filed:

Jun. 09, 2023
Applicant:

Google Llc, Mountain View, CA (US);

Inventor:

Yuzhao Ni, Sunnyvale, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/9032 (2019.01); G06F 16/33 (2019.01); G06F 40/216 (2020.01); G06F 40/35 (2020.01); G06N 3/006 (2023.01); G06N 3/02 (2006.01); G06N 3/084 (2023.01); G06N 5/022 (2023.01); G10L 15/18 (2013.01); G10L 15/22 (2006.01); G10L 15/26 (2006.01);
U.S. Cl.
CPC ...
G06F 16/90332 (2019.01); G06F 16/3334 (2019.01); G06F 40/216 (2020.01); G06F 40/35 (2020.01); G06N 3/006 (2013.01); G06N 3/02 (2013.01); G06N 3/084 (2013.01); G10L 15/18 (2013.01); G10L 15/22 (2013.01); G10L 15/26 (2013.01); G06N 5/022 (2013.01); G10L 2015/223 (2013.01); G10L 2015/227 (2013.01); G10L 2015/228 (2013.01);
Abstract

Generating and/or recommending command bundles for a user of an automated assistant. A command bundle comprises a plurality of discrete actions that can be performed by an automated assistant. One or more of the actions of a command bundle can cause transmission of a corresponding command and/or other data to one or more devices and/or agents that are distinct from devices and/or agents to which data is transmitted based on other action(s) of the bundle. Implementations determine command bundles that are likely relevant to a user, and present those command bundles as suggestions to the user. In some of those implementations, a machine learning model is utilized to generate a user action embedding for the user, and a command bundle embedding for each of a plurality of command bundles. Command bundle(s) can be selected for suggestion based on comparison of the user action embedding and the command bundle embeddings.


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