Technology for optimizing artificial intelligence pipelines
AssigneeInternational Business Machines Corporation
InventorsDhavalkumar C. Patel, Shrey Shrivastava, Wesley M. Gifford
Life of this patent
Estimating the term…
Abstract
Machine logic to change steps included in and/or parameters/parameter value used in artificial intelligence (“AI”) pipelines. For example, the machine logic may control what types of data (for example, sensor data) are received by the AI pipeline and/or have the data is culled in the pipeline prior to application of a machine learning and/or artificial intelligence algorithm.
Claims20
A computer-implemented method (CIM) for use with an original artificial intelligence pipeline (AIP), the CIM comprising:
- orchestrating, by a pipeline deployment tool, an examination of the original AIP to yield a set of pipeline revision(s);
- producing, by the pipeline deployment tool, a revised version of the AIP, along with associated metadata;
- and
- deploying the revised version of the AIP.
A computer program product (CPP) for use with an original artificial intelligence pipeline (AIP), the CPP comprising:
- a set of storage device(s);
- and
- computer code stored on the set of storage device(s), with the computer code including data and instructions for causing a processor(s) set to perform the following operations:
- orchestrating, by a pipeline deployment tool, an examination of the original AIP to yield a set of pipeline revision(s),
- producing, by the pipeline deployment tool, a revised version of the AIP, along with associated metadata, and
- deploying the revised version of the AIP.
A computer-implemented method (CIM) comprising:
- receiving computer code corresponding to an original version of a machine learning module (ML mod) structured and/or programmed to:
- (i) receive input data that includes X input parameter values respectively corresponding to X parameters, where X is an integer greater than one, (ii) to select Y input parameter values of the X input parameters to obtain Y selected/extracted parameter values, where Y is an integer less than or equal to X, and (iii) apply an ML algorithm, which has been developed, at least in part, by ML, to the Y selected/extracted parameter values to obtain a recommendation;
- performing feature selection, by machine logic, to obtain updated value(s) for at least one of the following variables:
- X and/or Y;
- and
- revising, by machine logic, the original version of the ML mod to obtain an updated version of the ML mod that is characterized by the updated value(s) for X and/or Y.
Dependencies are inferred from the claim text.