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. 08, 2022

Filed:

Aug. 04, 2020
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Noam M. Shazeer, Palo Alto, CA (US);

Aidan Nicholas Gomez, Toronto, CA;

Lukasz Mieczyslaw Kaiser, Mountain View, CA (US);

Jakob D. Uszkoreit, Portola Valley, CA (US);

Llion Owen Jones, San Francisco, CA (US);

Niki J. Parmar, Sunnyvale, CA (US);

Ashish Teku Vaswani, San Francisco, CA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/284 (2020.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06F 40/284 (2020.01); G06K 9/6227 (2013.01); G06K 9/6298 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media for training a machine learning model to perform multiple machine learning tasks from multiple machine learning domains. One system includes a machine learning model that includes multiple input modality neural networks corresponding to respective different modalities and being configured to map received data inputs of the corresponding modality to mapped data inputs from a unified representation space; an encoder neural network configured to process mapped data inputs from the unified representation space to generate respective encoder data outputs; a decoder neural network configured to process encoder data outputs to generate respective decoder data outputs from the unified representation space; and multiple output modality neural networks corresponding to respective different modalities and being configured to map decoder data outputs to data outputs of the corresponding modality.


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