US 12,248,815 B2
Client-configurable retention periods for machine learning service-managed resources
Ramyanshu Datta, Campbell, CA (US); Ishaaq Chandy, Bellevue, WA (US); Arvind Sowmyan, Seattle, WA (US); Wei You, Kirkland, WA (US); Kunal Mehrotra, Kirkland, WA (US); Kohen Berith Chia, Seattle, WA (US); Andrea Olgiati, Gilroy, CA (US); Lakshmi Naarayanan Ramakrishnan, Redmond, WA (US); and Saurabh Gupta, Sammamish, WA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Apr. 22, 2024, as Appl. No. 18/642,668.
Application 18/642,668 is a continuation of application No. 17/482,276, filed on Sep. 22, 2021, granted, now 11,995,476.
Prior Publication US 2024/0272953 A1, Aug. 15, 2024
Int. Cl. G06F 9/46 (2006.01); G06F 9/50 (2006.01)
CPC G06F 9/5038 (2013.01) [G06F 9/5022 (2013.01); G06F 9/5055 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
performing, at a cloud computing environment, respective operations of one or more categories of preparatory operations prior to executing, at a particular computing resource, a first machine learning task on behalf of a client, wherein the first machine learning task is executed at the particular computing resource without receiving input from the client specifying that the particular computing resource is to be used for the first machine learning task;
providing, from the cloud computing environment to the client, an indication that the particular computing resource is available for re-use for a first time interval after completion of the first machine learning task; and
in response to determining, at the cloud computing environment, that a result of a particular operation of the respective operations can be re-used for a second machine learning task, wherein the second machine learning task is requested by the client prior to expiration of the first time interval, and wherein the particular operation belongs to a first category of the one or more categories, executing the second machine learning task at the particular computing resource without performing an operation of the first category for the second machine learning task.