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公开(公告)号：US12209882B2
公开(公告)日：2025-01-28
申请号：US17126072
申请日：2020-12-18
Applicant: Intel Corporation
Abstract: Various aspects are related to a map representation system including one or more processors configured to: obtain operation task data, the operation task data indicating one or more operation tasks associated with an operation of one or more autonomous agents within a corresponding operating space; and obtain operation task specific map data as a function of the operation task data, the operation task specific map data representing the operating space corresponding to the one or more operation tasks.
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公开(公告)号：US12174606B2
公开(公告)日：2024-12-24
申请号：US17130025
申请日：2020-12-22
Applicant: Intel Corporation
Inventor： Rajesh Poornachandran , Omesh Tickoo , Vinayak Honkote , John Charles Weast , Rita H. Wouhaybi , Stanley Mo
IPC: G05B19/042 , B25J19/00 , G05B13/02
Abstract: According to various aspects, a controller for an automated machine may include: one or more processors configured to: obtain a message from a further automated machine in accordance with a communication protocol, the message including a first result of a first sensing process that the further automated machine performs; and determine an assessment of the automated machine based on the first result and based on a second result of a second sensing process that the automated machine performs.
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63.发明授权公开(公告)号：US12079665B2
公开(公告)日：2024-09-03
申请号：US17023161
申请日：2020-09-16
Applicant: Intel Corporation
Inventor： Kaushik Balasubramanian , Rajesh Poornachandran , Karan Puttannaiah
CPC classification number: G06F9/5077 , G06F9/5038 , G06F9/5055 , G06F21/51
Abstract: Systems, apparatuses and methods may provide for technology that automatically determines a first proposed change to an existing resource allocation associated with a first application in a first node, wherein the first proposed change is determined at least partially based on a requested resource allocation associated with a pending application and a first tolerance associated with the first application. The technology may also issue the first proposed change to the first application and automatically conduct the first proposed change if the first application accepts the first proposed change.
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公开(公告)号：US20240223611A1
公开(公告)日：2024-07-04
申请号：US18147492
申请日：2022-12-28
Applicant: Intel Corporation
Inventor： Rajesh Poornachandran , Ned M. Smith , Sunil K. Cheruvu
IPC: H04L9/40 , H04L41/0866
CPC classification number: H04L63/20 , H04L41/0866
Abstract: The technology described herein includes determining a security quality of service (Qos) profile matching configuration attributes of a first computing system, generating an interdependency flow graph based at least in part on the security QoS profile and the configuration attributes, generating a recommended configuration for the first computing system from the interdependency flow graph, and sending the recommended configuration to a second computing system.
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公开(公告)号：US20240070926A1
公开(公告)日：2024-02-29
申请号：US18466141
申请日：2023-09-13
Applicant: Intel Corporation
Inventor： Joydeep Ray , Ben Ashbaugh , Prasoonkumar Surti , Pradeep Ramani , Rama Harihara , Jerin C. Justin , Jing Huang , Xiaoming Cui , Timothy B. Costa , Ting Gong , Elmoustapha Ould-ahmed-vall , Kumar Balasubramanian , Anil Thomas , Oguz H. Elibol , Jayaram Bobba , Guozhong Zhuang , Bhavani Subramanian , Gokce Keskin , Chandrasekaran Sakthivel , Rajesh Poornachandran
CPC classification number: G06T9/002 , G06F12/023 , G06T15/005 , G06F2212/302 , G06F2212/401
Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.
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Patent Agency Ranking
公开(公告)号：US20230412699A1
公开(公告)日：2023-12-21
申请号：US18456102
申请日：2023-08-25
Applicant: Intel Corporation
Inventor： Rajesh Poornachandran , Vincent Zimmer , Subrata Banik , Marcos Carranza , Kshitij Arun Doshi , Francesc Guim Bernat , Karthik Kumar
IPC: H04L67/51 , H04L41/5009 , H04L9/32 , H04L67/562
CPC classification number: H04L67/51 , H04L41/5009 , H04L9/3278 , H04L67/562 , H04L9/50
Abstract: An apparatus to facilitate provenance audit trails for microservices architectures is disclosed. The apparatus includes one or more processors to obtain provenance metadata for a microservice from a local blockchain of provenance metadata maintained for the hardware resource executing a task performed by the microservice, the provenance metadata comprising identification of the microservice, operating state of at least one of a hardware resource or a software resource used to execute the microservice and the task, and an operating state of a sidecar of the microservice during the task; access one or more policies established for the microservice; analyze the provenance metadata with respect to the one or more policies to identify if there is a violation of the one or more policies; and generate one or more evaluation metrics based on whether the violation of the one or more policies is identified.
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公开(公告)号：US11836721B2
公开(公告)日：2023-12-05
申请号：US16024676
申请日：2018-06-29
Applicant: INTEL CORPORATION
Inventor： Ned M. Smith , Rajesh Poornachandran , Michael Nolan , Simon N. Peffers
IPC: G06Q20/40 , G06Q20/22 , G06Q20/38 , H04L9/06 , H04L9/32 , H04W56/00 , G06F16/23 , H04L9/00 , G06F21/64
CPC classification number: G06Q20/401 , G06F16/2379 , G06Q20/223 , G06Q20/389 , G06Q20/4016 , H04L9/0637 , H04L9/0643 , H04L9/3239 , H04L9/3297 , H04W56/001 , G06Q2220/00 , H04L9/50 , H04L2209/56 , H04L2209/805
Abstract: In some examples, an apparatus uses a blockchain to agree on a time in an information exchange network. A first node includes a processor communicatively coupled to a storage device including instructions. When executed by the processor, the instructions cause the processor to verify a time estimate from each of one or more other node, to determine a time match of a time estimate of the first node with the time estimates from the one or more other node, and if the time match is determined, to commit to the blockchain a transaction that includes a time stamp.
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公开(公告)号：US20230344873A1
公开(公告)日：2023-10-26
申请号：US18345865
申请日：2023-06-30
Applicant: Intel Corporation
Inventor： Ned Smith , Satish Jha , S M Iftekharul Alam , Vesh Raj Sharma Banjade , Kathiravetpillai Sivanesan , Arvind Merwaday , Liuyang Yang , Rajesh Poornachandran
CPC classification number: H04L63/20 , H04L63/107 , G06Q20/389
Abstract: Methods and apparatus for secured information transfer are disclosed. An example apparatus includes programmable circuitry to execute instructions to determine characteristics of an asset associated with a first entity that utilizes a first type of decentralized security, assign the asset to a carrier for transport to a second entity that utilizes a second type of decentralized security, obtain attested information for the asset from the carrier, and transmit the attested information to the second entity via a first gateway, the first gateway to transmit the attested information for the asset to a second gateway of the second entity.
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公开(公告)号：US11710034B2
公开(公告)日：2023-07-25
申请号：US16287313
申请日：2019-02-27
Applicant: Intel Corporation
Inventor： Glen J. Anderson , Rajesh Poornachandran , Kshitij Doshi
IPC: G06F7/00 , G06N3/08 , G06N20/00 , G06F16/906 , G06F16/901 , G06N5/04 , G06F18/214 , G06F18/40 , G06F18/21 , G06V10/776 , G06V10/778
CPC classification number: G06N3/08 , G06F16/901 , G06F16/906 , G06F18/217 , G06F18/2148 , G06F18/41 , G06N5/04 , G06N20/00 , G06V10/776 , G06V10/7788
Abstract: A mechanism is described for facilitating misuse index for explainable artificial intelligence in computing environments, according to one embodiment. A method of embodiments, as described herein, includes mapping training data with inference uses in a machine learning environment, where the training data is used for training a machine learning model. The method may further include detecting, based on one or more policy/parameter thresholds, one or more discrepancies between the training data and the inference uses, classifying the one or more discrepancies as one or more misuses, and creating a misuse index listing the one or more misuses.
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公开(公告)号：US20230230289A1
公开(公告)日：2023-07-20
申请号：US18152643
申请日：2023-01-10
Applicant: Intel Corporation
Inventor： Joydeep Ray , Ben Ashbaugh , Prasoonkumar Surti , Pradeep Ramani , Rama Harihara , Jerin C. Justin , Jing Huang , Xiaoming Cui , Timothy B. Costa , Ting Gong , Elmoustapha Ould-ahmed-vall , Kumar Balasubramanian , Anil Thomas , Oguz H. Elibol , Jayaram Bobba , Guozhong Zhuang , Bhavani Subramanian , Gokce Keskin , Chandrasekaran Sakthivel , Rajesh Poornachandran
CPC classification number: G06T9/002 , G06F12/023 , G06T15/005 , G06F2212/401 , G06F2212/302
Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.
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