US 12,477,163 B2
Machine learning model continuous training system
Kevin Sarabia Dela Rosa, Seattle, WA (US); Hao Hu, Bellevue, WA (US); and Yanjia Li, Torrance, CA (US)
Assigned to Snap Inc., Santa Monica, CA (US)
Filed by Snap Inc., Santa Monica, CA (US)
Filed on May 31, 2023, as Appl. No. 18/326,724.
Prior Publication US 2024/0406477 A1, Dec. 5, 2024
Int. Cl. H04N 21/25 (2011.01); G06V 10/774 (2022.01); G06V 20/40 (2022.01); H04N 21/234 (2011.01)
CPC H04N 21/251 (2013.01) [G06V 10/774 (2022.01); G06V 20/41 (2022.01); G06V 20/46 (2022.01); H04N 21/23418 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
at least one processor;
at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
training a machine learning model by performing a set of operations comprising:
accessing media content items associated with interaction functions initiated by users of an interaction system, wherein the media content items comprise images, videos, or content augmentations of the users posted on the interaction system enabling other users to view the posted media content items;
generating training data including labels for the media content items, wherein the labels are indicative of one or more characteristics of the media content items;
extracting features from a media content item of the media content items;
identifying additional media content items to include in the training data based on the extracted features from the media content item;
processing the training data using a machine learning model to generate a media content item output; and
updating one or more parameters of the machine learning model based on the media content item output; and
repeating the set of operations to retrain the machine learning model based on a retraining criterion being met.