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公开(公告)号：US20220272794A1
公开(公告)日：2022-08-25
申请号：US17182418
申请日：2021-02-23
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Manoop Talasila , Guy Jacobson , John F. Murray , Mazin E. Gilbert
Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.
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公开(公告)号：US20250016887A1
公开(公告)日：2025-01-09
申请号：US18886432
申请日：2024-09-16
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Manoop Talasila , Guy Jacobson , John F. Murray , Mazin E. Gilbert
Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.
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3.发明授权公开(公告)号：US11848828B1
公开(公告)日：2023-12-19
申请号：US17821636
申请日：2022-08-23
Inventor： Manoop Talasila , Anwar Syed Aftab , Wen-Ling Hsu , Cristian Borcea , Yi Chen , Xiaopeng Jiang , Shuai Zhao , Guy Jacobson , Rittwik Jana
Abstract: An artificial intelligence (AI) automation to improve network quality based on predicted locations is provided. A method can include training, by a first device comprising a processor and according to model configuration parameters received from a second device that is not the first device, a local machine learning model with training data derived from first location data collected by the first device; transmitting, by the first device to the second device, anonymized model features associated with the local machine learning model; in response to the transmitting of the anonymized model features, receiving, by the first device from the second device, an aggregated machine learning model; and estimating, by the first device, a future position of the first device by applying the aggregated machine learning model to second location data collected by the first device.
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公开(公告)号：US20230134078A1
公开(公告)日：2023-05-04
申请号：US18092255
申请日：2022-12-31
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Guy Jacobson , Reuben Klein , John Murray , Mazin Gilbert , Manoop Talasila , Kazi Farooqui
Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.
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公开(公告)号：US11622418B2
公开(公告)日：2023-04-04
申请号：US17182418
申请日：2021-02-23
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Manoop Talasila , Guy Jacobson , John F. Murray , Mazin E. Gilbert
Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.
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Patent Agency Ranking
公开(公告)号：US20220172219A1
公开(公告)日：2022-06-02
申请号：US17106934
申请日：2020-11-30
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Wen-Ling Hsu , Guang-Qin Ma , Guy Jacobson , Jenq-Chyuan Wang , Tan Xu , Kevin McDorman , Brian Economaki , Shuai Zhao
Abstract: A method, computer-readable medium, and apparatus for providing customer care for customers are disclosed. Customer care may be provided for customers by obtaining customer care contact information for a plurality of customers where the customer care contact information includes, for each of a plurality of customers, respective customer care contact data that is based on a sequence of customer care contacts by the customer with one or more customer care agents, determining customer care contact embedding information for the plurality of customers, clustering the customer care contact embedding information for the plurality of customers to form customer care contact clusters, determining customer care contact cluster characterization information for the customer care contact clusters, selecting, from the plurality of customers based on the customer care contact cluster characterization information for the customer care contact clusters, a set of customers, and initiating a customer care action for the set of customers.
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公开(公告)号：US20230209658A1
公开(公告)日：2023-06-29
申请号：US18177368
申请日：2023-03-02
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Manoop Talasila , Guy Jacobson , John F. Murray , Mazin E. Gilbert
CPC classification number: H04W88/182 , H04L5/0048 , H04W24/02 , H04W24/08 , H04W28/0289 , H04W56/0015
Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.
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公开(公告)号：US11544617B2
公开(公告)日：2023-01-03
申请号：US15960265
申请日：2018-04-23
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Guy Jacobson , Reuben Klein , John Murray , Mazin Gilbert , Manoop Talasila , Kazi Farooqui
Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.
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公开(公告)号：US20190325353A1
公开(公告)日：2019-10-24
申请号：US15960265
申请日：2018-04-23
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Guy Jacobson , Reuben Klein , John Murray , Mazin Gilbert , Manoop Talasila , Kazi Farooqui
Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.
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公开(公告)号：US12120776B2
公开(公告)日：2024-10-15
申请号：US18177368
申请日：2023-03-02
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Syed Anwar Aftab , Manoop Talasila , Guy Jacobson , John F. Murray , Mazin E. Gilbert
CPC classification number: H04W88/182 , H04L5/0048 , H04W24/02 , H04W24/08 , H04W28/0289 , H04W56/0015
Abstract: Aspects of the subject disclosure may include, for example, receiving network-related information associated with a first RAN that includes a first RIC, obtaining, from an artificial intelligence (AI) model synchronization system associated with a second RAN, data relating to an AI model deployed by a second RIC of the second RAN, determining, based on the data relating to the AI model and the network-related information associated with the first RAN, that the AI model can be leveraged by the first RAN to improve network performance of the first RAN, performing synchronization with the AI model synchronization system to obtain the AI model, responsive to the determining that the AI model can be leveraged by the first RAN to improve the network performance of the first RAN, and causing the first RIC to deploy the AI model in the first RAN after the performing the synchronization. Other embodiments are disclosed.
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