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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 11288444 B1

PDFFull Text
Date of Patent:
Mar. 29, 2022

Filed:

Dec. 11, 2020

Optimization techniques for artificial intelligence

Applicant:

100.co, Llc, Miami Beach, FL (US);

Inventors:

Robert J. Munro, San Francisco, CA (US);

Schuyler D. Erle, San Francisco, CA (US);

Jason Brenier, Oakland, CA (US);

Paul A. Tepper, San Francisco, CA (US);

Tripti Saxena, Cupertino, CA (US);

Gary C. King, Los Altos, CA (US);

Jessica D. Long, San Francisco, CA (US);

Brendan D. Callahan, Philadelphia, PA (US);

Tyler J. Schnoebelen, San Francisco, CA (US);

Stefan Krawczyk, Menlo Park, CA (US);

Veena Basavaraj, San Francisco, CA (US);

Assignee:

100.co, LLC, Miami Beach, FL (US);

Attorney:

Stetina Brunda Garred and Brucker

Primary Examiner:

Keith D Bloomquist

Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 40/169 (2020.01); G06F 16/35 (2019.01); G06F 16/93 (2019.01); G06F 16/242 (2019.01); G06F 16/28 (2019.01); G06F 16/36 (2019.01); G06F 16/951 (2019.01); G06F 16/332 (2019.01); G06F 16/2453 (2019.01); G06Q 50/00 (2012.01); G06F 40/30 (2020.01); G06F 40/40 (2020.01); G06F 40/42 (2020.01); G06F 40/137 (2020.01); G06F 40/221 (2020.01); G06F 3/0482 (2013.01);
U.S. Cl.
CPC ...
G06F 40/169 (2020.01); G06F 3/0482 (2013.01); G06F 16/243 (2019.01); G06F 16/24532 (2019.01); G06F 16/285 (2019.01); G06F 16/288 (2019.01); G06F 16/3329 (2019.01); G06F 16/35 (2019.01); G06F 16/367 (2019.01); G06F 16/93 (2019.01); G06F 16/951 (2019.01); G06F 40/137 (2020.01); G06F 40/221 (2020.01); G06F 40/30 (2020.01); G06F 40/40 (2020.01); G06F 40/42 (2020.01); G06N 20/00 (2019.01); G06Q 50/01 (2013.01);
Abstract

Methods, apparatuses and computer readable medium are presented for generating a natural language model. A method for generating a natural language model comprises: selecting from a pool of documents, a first set of documents to be annotated; receiving annotations of the first set of documents elicited by first human readable prompts; training a natural language model using the annotated first set of documents; determining documents in the pool having uncertain natural language processing results according to the trained natural language model and/or the received annotations; selecting from the pool of documents, a second set of documents to be annotated comprising documents having uncertain natural language processing results; receiving annotations of the second set of documents elicited by second human readable prompts; and retraining a natural language model using the annotated second set of documents.

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