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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 10671938 B1

PDFFull Text
Date of Patent:
Jun. 02, 2020

Filed:

Jan. 26, 2017

Artificial intelligence engine configured to work with a pedagogical programming language to train one or more trained artificial intelligence models

Applicant:

Bonsai Ai, Inc., Berkeley, CA (US);

Inventors:

Mark Isaac Hammond, Berkeley, CA (US);

Keen McEwan Browne, Berkeley, CA (US);

Megan Adams, San Francisco, CA (US);

Assignee:

Bonsai AI, Inc., Berkeley, CA (US);

Attorney:

Alleman Hall Creasman & Tuttle LLP

Primary Examiner:

Austin Hicks

Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 16/951 (2019.01); G06F 16/22 (2019.01); G06F 8/38 (2018.01); G06Q 10/00 (2012.01); G06N 3/10 (2006.01); G06F 30/20 (2020.01); G06F 8/30 (2018.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); H04L 29/06 (2006.01); G06F 9/451 (2018.01); G06F 3/0482 (2013.01); G06N 3/00 (2006.01); G06N 5/04 (2006.01); G06F 9/48 (2006.01); G06F 15/80 (2006.01); G06K 9/62 (2006.01); G06F 30/333 (2020.01); G06F 40/166 (2020.01); G06F 3/0354 (2013.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 3/0482 (2013.01); G06F 8/31 (2013.01); G06F 8/38 (2013.01); G06F 9/451 (2018.02); G06F 9/4881 (2013.01); G06F 15/80 (2013.01); G06F 16/2228 (2019.01); G06F 16/951 (2019.01); G06F 30/20 (2020.01); G06K 9/6257 (2013.01); G06N 3/008 (2013.01); G06N 3/04 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 3/105 (2013.01); G06N 5/04 (2013.01); G06Q 10/00 (2013.01); H04L 67/42 (2013.01); G06F 3/03543 (2013.01); G06F 30/333 (2020.01); G06F 40/166 (2020.01);
Abstract

Provided in some embodiments is an artificial intelligence ('AI') engine configured to work with a pedagogical programming language configured to enable an author to 1) define a mental model to be learned by an AI model, the mental model including an input, one or more concept nodes, one or more stream nodes, and an output, as well as 2) define one or more curriculums for training the AI model respectively on the one or more concept nodes. A compiler can be configured to generate an assembly code from a source code authored in the pedagogical programming language. An architect module can be configured to propose a neural-network layout from the assembly code. A learner module can be configured to build the AI model the neural-network layout. An instructor module can be configured to train the AI model on the one or more concept nodes respectively with the one or more curriculums.

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