US 12,236,287 B2
Systems and methods for implementing an intelligent application program interface for an intelligent optimization platform
Alexandra Johnson, San Francisco, CA (US); Patrick Hayes, San Francisco, CA (US); and Scott Clark, San Francisco, CA (US)
Assigned to Intel Corporation, Santa Clara, CA (US)
Filed by Intel Corporation, Santa Clara, CA (US)
Filed on May 31, 2023, as Appl. No. 18/326,467.
Application 18/326,467 is a continuation of application No. 17/516,296, filed on Nov. 1, 2021, granted, now 11,709,719.
Application 17/516,296 is a continuation of application No. 16/741,895, filed on Jan. 14, 2020, granted, now 11,163,615, issued on Nov. 2, 2021.
Application 16/741,895 is a continuation of application No. 16/559,846, filed on Sep. 4, 2019, granted, now 10,565,025, issued on Feb. 18, 2020.
Application 16/559,846 is a continuation of application No. 16/450,891, filed on Jun. 24, 2019, granted, now 10,445,150, issued on Oct. 15, 2019.
Application 16/450,891 is a continuation of application No. 16/359,107, filed on Mar. 20, 2019, granted, now 10,379,913, issued on Aug. 13, 2019.
Application 16/359,107 is a continuation of application No. 16/173,737, filed on Oct. 29, 2018, granted, now 10,282,237, issued on May 7, 2019.
Claims priority of provisional application 62/578,886, filed on Oct. 30, 2017.
Prior Publication US 2023/0385129 A1, Nov. 30, 2023
Int. Cl. G06F 9/54 (2006.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01)
CPC G06F 9/54 (2013.01) [G06F 11/3495 (2013.01); G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
13. A method comprising:
accessing, by executing an instruction using programmable circuitry, a request to tune a machine learning model from a client, the request accessed at an application programming interface (API), the request conveyed to the API using a hypertext transfer protocol (HTTP) message, the request to include an identification of the machine learning model to be tuned and information to be used in the tuning of the machine learning model;
validating, by executing an instruction using the programmable circuitry, an API key provided via the request to tune the machine learning model;
after validating the API key, queuing execution of the tuning of the machine learning model; and
providing a response message to the client.