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:
Apr. 21, 2026

Filed:

Jan. 27, 2021
Applicant:

Salesforce, Inc., San Francisco, CA (US);

Inventors:

Yuliya L. Feldman, Campbell, CA (US);

Seyedshahin Ashrafzadeh, Foster City, CA (US);

Alexandr Nikitin, El Sobrante, CA (US);

Manoj Agarwal, Cupertino, CA (US);

Assignee:

Salesforce, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/0455 (2023.01); G06F 9/455 (2018.01); G06F 9/50 (2006.01); G06N 20/00 (2019.01); G06F 8/71 (2018.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 9/45558 (2013.01); G06F 9/5077 (2013.01); G06F 8/71 (2013.01); G06F 2209/501 (2013.01);
Abstract

Using container and model information to select containers for executing models is described. A system receives a request from an application and identifies a version of a machine-learning model associated with the request. The system identifies model information associated with machine learning models corresponding to a cluster of available serving containers associated with the version of the machine-learning model. The system uses the model information to select a serving container from the cluster of available serving containers. If the machine-learning model is not loaded in the serving container, the system loads the machine-learning model in the serving container. If the machine-learning model is loaded in the serving container, the system executes, in the serving container, the machine-learning model on behalf of the request. The system responds to the request based on executing the machine-learning model on behalf of the request.


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