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:
Sep. 30, 2025

Filed:

Mar. 13, 2024
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Noam Shazeer, Palo Alto, CA (US);

Daniel De Freitas Adiwardana, Mountain View, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/35 (2020.01); G06F 8/38 (2018.01); G06F 16/903 (2019.01); G06F 16/9032 (2019.01); G06F 16/9038 (2019.01); G06F 40/20 (2020.01); G06F 40/279 (2020.01); G06F 40/284 (2020.01); G06N 3/045 (2023.01); G06N 3/092 (2023.01); G06N 20/00 (2019.01); G10L 13/02 (2013.01);
U.S. Cl.
CPC ...
G06F 40/35 (2020.01); G06F 8/38 (2013.01); G06F 16/90332 (2019.01); G06F 16/90335 (2019.01); G06F 16/9038 (2019.01); G06F 40/20 (2020.01); G06F 40/279 (2020.01); G06F 40/284 (2020.01); G06N 3/045 (2023.01); G06N 3/092 (2023.01); G06N 20/00 (2019.01); G10L 13/02 (2013.01);
Abstract

The present disclosure is directed to systems and methods that include and/or leverage one or more machine-learned language models that generate intermediate textual analysis (e.g., including usage of structural tools such as APIs) in service of contextual text generation. For example, a computing system can obtain a contextual text string that includes one or more contextual text tokens. The computing system can process the contextual text string with the machine-learned language model to generate one or more intermediate text strings that include one or more intermediate text tokens. The computing system can process the one or more intermediate text strings with the machine-learned language model to generate an output text string comprising one or more output text tokens. The one or more intermediate text strings can include textual analysis of the contextual text string that supports the output text string.


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