The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 05, 2025
Filed:
Nov. 19, 2021
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Jasmine Grace Schlichting, Seattle, WA (US);
Bhuvan Malladihalli Shashidhara, Bellevue, WA (US);
Ramakoti R. Bhimanadhuni, Bothell, WA (US);
Emily Nicole Wilson, Seattle, WA (US);
Farah Farzana, Redmond, WA (US);
Michael Wayne Stephenson, Woodinville, WA (US);
Pallavi Baral, Redmond, WA (US);
Josh Charles Moore, Lynnwood, WA (US);
Christina Margaret Tobias, Seattle, WA (US);
John A. Strange, Everett, WA (US);
Peter Hanpeng Jiang, Kirkland, WA (US);
Sebastien Nathan R Levy, Seattle, WA (US);
Brett Kenneth Dodds, Boise, ID (US);
Arhatha Bramhanand, Redmond, WA (US);
Juan Arturo Herrera Ortiz, Seattle, WA (US);
Ahu Oral, Seattle, WA (US);
Charlotte Gauchet, Redmond, WA (US);
Daniel Sebastian Berger, Seattle, WA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
The disclosure herein describes training and using an uncorrectable error (UE) state prediction model based on telemetry error data. Sets of UE state labels and non-UE state labels are generated from a first set of collected telemetry data, wherein the UE state labels each reference a UE and telemetry data of an interval prior to the referenced UE. Statistical features are extracted from telemetry data of the sets of UE state labels and non-UE state labels, and the extracted statistical features are used to train a UE state prediction model. A second set of collected telemetry data is obtained, and a UE event is predicted based on the second set of collected telemetry data using the trained UE state prediction model. A preventative operation is performed on a memory page of the system based on the predicted UE event, whereby the predicted UE event is prevented from occurring.