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:
Dec. 16, 2025

Filed:

Feb. 26, 2025
Applicant:

Openai Opco, Llc, San Francisco, CA (US);

Inventors:

Jerry Tworek, San Francisco, CA (US);

Nicholas Turley, San Francisco, CA (US);

Assignee:

OpenAl OpCo, LLC., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/36 (2025.01); G06F 8/10 (2018.01); G06F 8/35 (2018.01); G06F 8/70 (2018.01); G06F 9/445 (2018.01); G06F 9/455 (2018.01); G06F 11/3604 (2025.01); G06F 21/53 (2013.01); G06F 40/174 (2020.01); G06F 40/40 (2020.01); G06V 30/10 (2022.01); G06V 40/16 (2022.01); G06F 3/01 (2006.01); G06F 3/06 (2006.01); G06F 8/33 (2018.01); G06F 9/50 (2006.01); G06F 11/07 (2006.01); G06F 40/20 (2020.01); G06N 3/0455 (2023.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06F 9/45508 (2013.01); G06F 8/10 (2013.01); G06F 8/35 (2013.01); G06F 8/70 (2013.01); G06F 11/3612 (2013.01); G06F 21/53 (2013.01); G06V 30/10 (2022.01); G06V 40/161 (2022.01); G06F 3/012 (2013.01); G06F 3/0619 (2013.01); G06F 3/0653 (2013.01); G06F 3/0664 (2013.01); G06F 3/067 (2013.01); G06F 8/33 (2013.01); G06F 9/5077 (2013.01); G06F 11/0766 (2013.01); G06F 11/0793 (2013.01); G06F 11/3608 (2013.01); G06F 40/20 (2020.01); G06F 40/40 (2020.01); G06N 3/0455 (2023.01); G06V 10/44 (2022.01); G06V 40/172 (2022.01);
Abstract

Disclosed herein are methods, systems, servers, and computer-readable media for interpreting computer code with a multimodal machine learning model. In an embodiment, this comprises: receiving, an input comprising at least one of a text prompt, file prompt, or data object, determining, using a multimodal machine learning model, that the input requires implementing computer code, and in response to determining the input requires implementing computer code: generating computer code based on the input, executing the generated computer code using a code interpreter, and providing, through an interface, an output based on the generated computer code.


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