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US Patent 10360214 Ensuring reproducibility in an artificial intelligence infrastructure

Patent 10360214 was granted and assigned to Pure Storage on July, 2019 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Pure Storage
Pure Storage
Current Assignee
Pure Storage
Pure Storage
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10360214
Date of Patent
July 23, 2019
Patent Application Number
16045814
Date Filed
July 26, 2018
Patent Citations Received
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US Patent 12093747 Workload orchestration in a multi-cloud environment
3
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US Patent 12067466 Artificial intelligence and machine learning hyperscale infrastructure
4
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US Patent 12080294 System and method for voice controlled automatic information access and retrieval
5
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US Patent 11494692 Hyperscale artificial intelligence and machine learning infrastructure
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US Patent 11556280 Data transformation for a machine learning model
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US Patent 11620262 Generation of a metadata-driven artificial intelligence platform
10
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US Patent 11657819 Selective use of tools for automatically identifying, accessing, and retrieving information responsive to voice requests
11
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US Patent 11768636 Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure
...
Patent Primary Examiner
‌
Grace Park
Patent abstract

Ensuring reproducibility in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, by a unified management plane, one or more transformations applied to a dataset by the artificial intelligence infrastructure, wherein applying the one or more transformations to the dataset causes the artificial intelligence infrastructure to generate a transformed dataset; storing, within the one or more storage systems, information describing the dataset, the one or more transformations applied to the dataset, and the transformed dataset; identifying, by the unified management plane, one or more machine learning models executed by the artificial intelligence infrastructure using the transformed dataset as input; and storing, within the one or more storage systems, information describing one or more machine learning models executed using the transformed dataset as input.

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