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Accenture Patent, ML Ensemble Streaming Data, Granted Apr 21

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Summary

The USPTO granted Patent US12608658B2 to Accenture Global Solutions Limited on April 21, 2026, for dynamically updated ensemble-based machine learning classification for streaming data. The patent, filed March 31, 2022 (Application No. 17711017), contains 19 claims under CPC classification G06N 20/20. The invention covers methods where new ML classifiers replace older ones in an ensemble when labels are obtained for previously unlabeled streaming data, enabling adaptation to statistical distribution changes.

“Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support dynamically updated ensemble-based machine learning (ML) classification.”

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GovPing monitors USPTO Patent Grants - AI & Computing (G06N) for new telecom & technology regulatory changes. Every update since tracking began is archived, classified, and available as free RSS or email alerts — 32 changes logged to date.

What changed

The USPTO granted Patent US12608658B2 to Accenture Global Solutions Limited on April 21, 2026, covering dynamically updated ensemble-based machine learning classification systems and methods for streaming data. The patent discloses an ensemble approach where trained ML classifiers generate predictions on unlabeled data streams, and newly labeled data is used to train replacement classifiers that learn changes in statistical distribution across recent input data.

Technology companies and ML practitioners should note this patent covers specific methods for dynamically updating ensemble classifiers in streaming data environments. The 19 granted claims may be relevant for freedom-to-operate analyses in similar ML deployment scenarios. Licensing discussions may be appropriate for parties developing comparable streaming ML systems.

Archived snapshot

Apr 23, 2026

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← USPTO Patent Grants

Dynamically updated ensemble-based machine learning for streaming data

Grant US12608658B2 Kind: B2 Apr 21, 2026

Assignee

Accenture Global Solutions Limited

Inventors

Sourav Ghosh, Paritosh Pramanik, Jyoti Singh, Theerthala Siva Rama Sarma, Nivetha Suruliraj

Abstract

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support dynamically updated ensemble-based machine learning (ML) classification. An ensemble of ML classifiers may be created from a plurality of trained ML classifiers. These initial ML classifiers may be trained using labeled data to generate predictions based on input data. When an unlabeled data stream is received, the unlabeled data stream may be provided as input to the ensemble to generate predictions. After obtaining labels for the received data, the labels and the unlabeled data stream may be used to train new ML classifiers. The new ML classifiers may replace older ML classifiers in the ensemble. In this manner, the ensemble of ML classifiers is used to perform predictions on high volume streaming data while being dynamically updated with ML classifiers that have learned changes in statistical distribution across more recent input data.

CPC Classifications

G06N 20/20

Filing Date

2022-03-31

Application No.

17711017

Claims

19

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Last updated

Classification

Agency
USPTO
Published
April 21st, 2026
Instrument
Rule
Branch
Executive
Legal weight
Binding
Stage
Final
Change scope
Minor
Document ID
US12608658B2

Who this affects

Applies to
Technology companies
Industry sector
5112 Software & Technology
Activity scope
Patent granting IP licensing
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence

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