US 12,287,785 B2
Obtaining inferences to perform access requests at a non-relational database system
Akshat Vig, Seattle, WA (US); Amit Gupta, Redmond, WA (US); Palak Agrawal, Cupertino, CA (US); Amit Purohit, Issaquah, WA (US); and Benjamin Donald Wood, Seattle, WA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Jun. 27, 2023, as Appl. No. 18/342,569.
Application 18/342,569 is a continuation of application No. 17/347,420, filed on Jun. 14, 2021, granted, now 11,726,999.
Prior Publication US 2023/0334046 A1, Oct. 19, 2023
Int. Cl. G06F 16/2453 (2019.01); G06F 16/2455 (2019.01); G06F 16/25 (2019.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06F 16/24542 (2019.01) [G06F 16/2455 (2019.01); G06F 16/258 (2019.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
one or more processors; and
a memory, that stores program instructions that, when executed by the at least one processor, cause the one or more processors to implement a non-relational database service, configured to implement a non-relational database service, configured to:
receive a request to create a machine learning model that generates, as an inference, a targeted value for a data item using one or more existing data items specified according to a query language compatible with both a relational data model and a non-relational data model;
obtain the one or more existing data items specified according to the query language;
cause the one or more existing items to be formatted for a machine learning system to train the machine learning model;
cause the machine learning system to train the machine learning model using the formatted one or more data items; and
associate the machine learning model for performing access requests to a data set hosted by the non-relational database service that includes the one or more existing items.