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US 12,705,029 B2Granted
Methods and systems of sequential latent inference of complex knowledge
AssigneeKinaxis Inc.
InventorsPhillip Williams, Sebastien Ouellet, Nathaniel Stanley, Chantal Bisson-Krol
Life of this patent
Estimating the term…
Abstract
Methods and systems that allow for supply chain logic to be instrumented in such a way that a supply planner can see the major factors driving KPIs, as well as drill down to the lower level to see the impact of each item at the smallest possible level.
Claims20
A computer-implemented method comprising:
- instrumenting, by an auto-differentiation engine, a codebase;
- capturing during execution of the codebase, by the auto-differentiation engine, interactions of a plurality of variables in the codebase;
- executing, by a processor, the codebase, thereby generating a metric;
- extracting, by the processor, low-level data from the codebase, wherein the low-level data comprises dense data of the interactions of the plurality of variables;
- and
- determining, by the processor, an impact of each of the plurality of variables on the metric, wherein the impact for each of the plurality of variables indicates how iterative changes to that one of the plurality of variables affects the metric so that the processor can compute the incremental differences in the iterative changes at each iteration and the effect of the iterative changes on a final state of the metric.
3 more elements
A system comprising:
- a processor;
- and
- a memory storing instructions that, when executed by the processor, configure the system to:
- instrument, by an auto-differentiation engine, a codebase;
- capture during execution of the codebase, by the auto-differentiation engine, interactions a plurality of variables in the codebase;
- execute, by the processor, the codebase, thereby generating a metric;
- extract, by the processor, low-level data from the codebase, wherein the low-level data comprises dense data of the interactions of the plurality of variables;
- and
- determine, by the processor, an impact of each of the plurality variables on the metric, wherein the impact for each of the one or more variables indicates how iterative changes to that one of the plurality of variables affects the metric so that the processor can compute the incremental differences in the iterative changes at each iteration and the effect of the iterative changes on a final state of the metric.
6 more elements
A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:
- instrument, by an auto-differentiation engine, a codebase;
- capture during execution of the codebase, by the auto-differentiation engine, interactions of a plurality of variables in the codebase;
- execute, by a processor, the codebase, thereby generating a metric;
- extract, by the processor, low-level data from the codebase, wherein the low-level data comprises dense data of the interactions of the plurality of variables;
- determine, by the processor, an impact of each of the plurality variables on the metric, wherein the impact for each of the plurality of variables indicates how iterative changes to that one of the plurality of variables affects the metric so that the processor can compute the incremental differences in the iterative changes at each iteration and the effect of the iterative changes on a final state of the metric.
2 more elements
Dependencies are inferred from the claim text.