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:
Oct. 26, 2021

Filed:

Jan. 10, 2020
Applicant:

General Electric Company, Schenectady, NY (US);

Inventors:

Jason Nichols, Niskayuna, NY (US);

Johan Michael Reimann, Clifton Park, NY (US);

Nurali Virani, Niskayuna, NY (US);

Naresh Sundaram Iyer, Ballston Spa, NY (US);

Assignee:

GENERAL ELECTRIC COMPANY, Schenectady, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16C 20/20 (2019.01); G16C 20/70 (2019.01); G06N 7/00 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G16C 20/20 (2019.02); G06N 7/005 (2013.01); G06N 20/00 (2019.01); G16C 20/70 (2019.02);
Abstract

According to some embodiments, a system, method and non-transitory computer-readable medium are provided comprising a Hypothesis Generation Engine (HGE) to receive one or more property target values for a material; a memory for storing program instructions; an HGE processor, coupled to the memory, and in communication with the HGE, and operative to execute program instructions to: receive the one or more property target values for the material; analyze the one or more property target values as compared to one or more known values in a knowledge base; generate, based on the analysis, an initial set of hypothetical structures, wherein each hypothetical structure includes at least one property target value; execute a likelihood model for each candidate material to generate a likelihood probability for each hypothetical structure, wherein the likelihood probability is a measure of the likelihood that the hypothetical structure will have the target property value; convert each hypothetical structure into a natural language representation; execute an abduction kernel on the natural language representation with the at least one likelihood probability, to output at least one proposed structure that satisfies a likelihood threshold for having the property target value; and receive the output of the executed abduction kernel at a testing module to determine whether the output satisfies the property target values. Numerous other aspects are provided.


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