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Patent Application: Validating Cached Inputs for Machine Learning Models

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Summary

The USPTO has published a patent application (US20260087400A1) detailing a method for validating cached input data for machine learning models. The application, filed on September 20, 2024, describes a hierarchical input pipeline that ensures data integrity before processing.

What changed

This document is a patent application (US20260087400A1) filed with the USPTO, describing a system and method for validating cached input components within a hierarchical pipeline for machine-learned models. The core innovation lies in a node-based validation process that relies on communication from child nodes to confirm the validity status of input data before it is passed to a parent node. This ensures that only validated context components are used in generating the final output, enhancing the reliability of machine learning systems.

As this is a patent application, it does not impose direct compliance obligations on regulated entities. However, companies involved in developing or deploying machine learning models, particularly those utilizing hierarchical data processing or caching mechanisms, may find the described techniques relevant for their internal development and intellectual property strategies. The application is published for public disclosure and potential patent grant.

Archived snapshot

Mar 26, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

Validating Cached Inputs to a Machine-Learned Model System

Application US20260087400A1 Kind: A1 Mar 26, 2026

Inventors

Branden Michael Archer, Mekhola Mukherjee

Abstract

An example method for validating data at a node in a hierarchical input pipeline for a machine-learned model system includes receiving, from a first child node of the node, a first input context component. The example method includes receiving, from a second child node of the node, a second input context component. The example method includes generating, at a context generation time, an output context component based on a validated set of context components comprising at least the first input context component. In the example method: the validated set of context components includes the second input context component based on receiving, from the second child node, a communication that indicates a valid context status for the second input context component at the context generation time; or the validated set of context components does not comprise the second input context component based on not receiving the communication that indicates the valid context status at the context generation time. The example method includes outputting, to a parent node of the node, the output context component.

CPC Classifications

G06N 20/00 H04L 9/3247

Filing Date

2024-09-20

Application No.

18891834

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Named provisions

Validating Cached Inputs to a Machine-Learned Model System

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Last updated

Classification

Agency
USPTO
Instrument
Notice
Legal weight
Non-binding
Stage
Draft
Change scope
Minor
Document ID
US20260087400A1

Who this affects

Applies to
Technology companies
Industry sector
5112 Software & Technology
Activity scope
Machine Learning Model Development
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Data Processing

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