US 11,669,377 B2
Providing application programming interface endpoints for machine learning models
David Lisuk, New York, NY (US); and Simon Slowik, London (GB)
Assigned to Palantir Technologies Inc., Denver, CO (US)
Filed by Palantir Technologies Inc., Denver, CO (US)
Filed on Feb. 25, 2022, as Appl. No. 17/680,859.
Application 17/680,859 is a continuation of application No. 16/990,233, filed on Aug. 11, 2020, granted, now 11,288,110.
Claims priority of provisional application 62/889,942, filed on Aug. 21, 2019.
Prior Publication US 2022/0179723 A1, Jun. 9, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 9/54 (2006.01); G06N 20/00 (2019.01); G06F 9/455 (2018.01); H04L 67/133 (2022.01)
CPC G06F 9/547 (2013.01) [G06F 9/45558 (2013.01); G06N 20/00 (2019.01); H04L 67/133 (2022.05); G06F 2009/45562 (2013.01); G06F 2009/45591 (2013.01); G06F 2009/45595 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
instantiating, at each virtual machine of one or more virtual machines, a machine learning model execution environment for an instance of a machine learning model;
loading, by a processing device, a respective instance of the machine learning model to each machine learning model execution environment;
associating each loaded instance of the machine learning model with an application programming interface (API) endpoint, the API endpoint configured to receive input data for the loaded instance of the machine learning model from a client device and to return output data produced by the loaded instance of the machine learning model based on the input data;
receiving a request by the client device to configure the API endpoint; and
identifying configuration information specified by the request, wherein an identifier of the machine learning model and a resource locator of the API endpoint are specified by the configuration information.