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公开(公告)号：US11416740B2
公开(公告)日：2022-08-16
申请号：US15952887
申请日：2018-04-13
申请人： ADTRAN, Inc.
发明人： Armand Nokbak Nyembe , Sheila Knight , Michael Arnold , Ramya Raghavendra , Jeremy Lyon , Venkata Mallikarjunarao Kosuri , Zack Whaley
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an artificial intelligence system. In one aspect, a system includes multiple artificial intelligence skill agents that have each been trained to perform different actions in a telecommunications system. The system also includes an orchestrator agent that interacts with each of the artificial intelligence skill agents and coordinates which of the artificial intelligence agents performs actions in response to user inputs. The orchestrator agent receives a user input and determines an intent expressed by the user input. The orchestrator agent transmits an instruction to an artificial intelligence skill agent to perform an action that provides a response to the intent. In response to receiving the instruction from the orchestrator agent, the artificial intelligence skill agent performs the action when the artificial intelligence skill agent is capable of carrying out the action.
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公开(公告)号：US20190318238A1
公开(公告)日：2019-10-17
申请号：US15952887
申请日：2018-04-13
申请人： ADTRAN, Inc.
发明人： Armand Nokbak Nyembe , Sheila Knight , Michael Arnold , Ramya Raghavendra , Jeremy Lyon , Venkata Mallikarjunarao Kosuri , Zack Whaley
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an artificial intelligence system. In one aspect, a system includes multiple artificial intelligence skill agents that have each been trained to perform different actions in a telecommunications system. The system also includes an orchestrator agent that interacts with each of the artificial intelligence skill agents and coordinates which of the artificial intelligence agents performs actions in response to user inputs. The orchestrator agent receives a user input and determines an intent expressed by the user input. The orchestrator agent transmits an instruction to an artificial intelligence skill agent to perform an action that provides a response to the intent. In response to receiving the instruction from the orchestrator agent, the artificial intelligence skill agent performs the action when the artificial intelligence skill agent is capable of carrying out the action.
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公开(公告)号：US11140063B2
公开(公告)日：2021-10-05
申请号：US16659066
申请日：2019-10-21
申请人： ADTRAN, Inc.
摘要： Systems and techniques are disclosed for using machine learning to dynamically detect physical impairments in lines of a subscriber network. In some implementations, per-tone data for a line of a subscriber network and data indicating a set of one or more scores is obtained. Each score included in the set of scores indicates a conditional likelihood that the line has a type of impairment with respect to a different feature subset ensemble. The per-tone data and the data indicating the set of one or more scores is provided as input to a model. The model is trained to output, for each of different sets of feature subset ensembles, a confidence score representing an overall likelihood that a particular line has a physical impairment. Data indicating a particular confidence score representing an overall likelihood that the line has the physical impairment is obtained. The particular confidence score is provided for output.
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公开(公告)号：US20200274789A1
公开(公告)日：2020-08-27
申请号：US16659066
申请日：2019-10-21
申请人： ADTRAN, Inc.
摘要： Systems and techniques are disclosed for using machine learning to dynamically detect physical impairments in lines of a subscriber network. In some implementations, per-tone data for a line of a subscriber network and data indicating a set of one or more scores is obtained. Each score included in the set of scores indicates a conditional likelihood that the line has a type of impairment with respect to a different feature subset ensemble. The per-tone data and the data indicating the set of one or more scores is provided as input to a model. The model is trained to output, for each of different sets of feature subset ensembles, a confidence score representing an overall likelihood that a particular line has a physical impairment. Data indicating a particular confidence score representing an overall likelihood that the line has the physical impairment is obtained. The particular confidence score is provided for output.
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