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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.

Patent No.:

US 11599752 B1

PDFFull Text
Date of Patent:
Mar. 07, 2023

Filed:

Jun. 03, 2020

Distributed and redundant machine learning quality management

Applicant:

Cerebri Ai Inc., Austin, TX (US);

Inventors:

Alain Charles Briancon, Germantown, MD (US);

Jean Joseph Belanger, Austin, TX (US);

Chris Michael Coovrey, Austin, TX (US);

Travis Stanton Penn, Austin, TX (US);

Divya Karumuri, Austin, TX (US);

Valisis Sotiris, College Park, MD (US);

Assignee:

Cerebri AI Inc., Austin, TX (US);

Attorney:

Pillsbury Winthrop Shaw Pittman LLP

Primary Examiner:

Anna C Deng

Int. Cl.
CPC ...
G06F 9/44 (2018.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01); G06F 8/20 (2018.01); G06N 20/20 (2019.01); G06F 30/20 (2020.01); G06F 8/10 (2018.01); G06F 8/30 (2018.01); G06Q 40/08 (2012.01); G06F 8/36 (2018.01); G06F 16/25 (2019.01); G06F 9/445 (2018.01); G06N 5/04 (2023.01); G06Q 10/0631 (2023.01); G06Q 10/0637 (2023.01); G06Q 10/0639 (2023.01); G06Q 10/067 (2023.01); G06Q 30/012 (2023.01); G06Q 30/016 (2023.01); G06Q 30/0204 (2023.01); G06Q 40/02 (2023.01); G06Q 30/0202 (2023.01);
U.S. Cl.
CPC ...
G06K 9/6257 (2013.01); G06F 8/10 (2013.01); G06F 8/24 (2013.01); G06F 8/315 (2013.01); G06F 8/36 (2013.01); G06F 9/44521 (2013.01); G06F 16/254 (2019.01); G06F 30/20 (2020.01); G06K 9/6256 (2013.01); G06K 9/6264 (2013.01); G06K 9/6282 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06Q 10/067 (2013.01); G06Q 10/06316 (2013.01); G06Q 10/06375 (2013.01); G06Q 10/06393 (2013.01); G06Q 30/012 (2013.01); G06Q 30/016 (2013.01); G06Q 30/0202 (2013.01); G06Q 30/0204 (2013.01); G06Q 40/025 (2013.01); G06Q 40/08 (2013.01);
Abstract

Provided is a process including: writing modelling-object classes using object-oriented modelling of the modelling methods, the modelling-object classes being members of a set of class libraries; writing quality-management classes using object-oriented modelling of quality management, the quality-management classes being members of the set of class libraries; scanning modelling-object classes in the set of class libraries to determine modelling-object class definition information; scanning quality-management classes in the set of class libraries to determine quality-management class definition information; using the modelling-object class definition information and the quality-management class definition information to produce object manipulation functions that allow a quality management system to access methods and attributes of modelling-object classes to manipulate objects of the modelling-object classes; and using the modelling-object class definition information and the quality-management class definition information to produce access to the object manipulation functions.

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