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:
Apr. 18, 2023

Filed:

Dec. 31, 2019
Applicant:

X Development Llc, Mountain View, CA (US);

Inventors:

Sarah Ann Laszlo, Mountain View, CA (US);

Philip Edwin Watson, Santa Cruz, CA (US);

Assignee:

X Development LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/04 (2012.01); G06F 16/22 (2019.01); G06N 3/02 (2006.01); G06N 3/08 (2023.01); G06N 3/006 (2023.01); G06N 3/04 (2023.01); G06N 3/12 (2023.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06N 3/006 (2013.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/12 (2013.01); G06N 3/0472 (2013.01); G06N 3/084 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a student neural network. In one aspect, there is provided a method comprising: processing a training input using the student neural network to generate a student neural network output comprising a respective score for each of a plurality of classes; processing the training input using a brain emulation neural network to generate a brain emulation neural network output comprising a respective score for each of the plurality of classes; and adjusting current values of the student neural network parameters using gradients of an objective function that characterizes a similarity between: (i) the student neural network output for the training input, and (ii) the brain emulation neural network output for the training input.


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