Hybrid cognitive system for AI/ML data privacy

    公开(公告)号:US12050714B2

    公开(公告)日:2024-07-30

    申请号:US18363533

    申请日:2023-08-01

    Abstract: Systems, methods, and devices are disclosed for cognitive collaboration systems on a hybrid node. A query is received by a virtual assistant running on a public cloud, and it is determined whether the query pertains to data available on a public cloud resource, or the query pertains to data available on a private cloud resource. When it is determined that the query pertains to the data available on the public cloud resource, the query is interpreted by using a first model trained on at least one machine learning technique on data from the public cloud. When it is determined that the query pertains to the data available on the private cloud resource, the query is interpreted by using a second model trained on at least one machine learning technique on the data from the private cloud.

    HYBRID COGNITIVE SYSTEM FOR AI/ML DATA PRIVACY

    公开(公告)号:US20240104242A1

    公开(公告)日:2024-03-28

    申请号:US18363533

    申请日:2023-08-01

    Abstract: Systems, methods, and devices are disclosed for cognitive collaboration systems on a hybrid node. A query is received by a virtual assistant running on a public cloud, and it is determined whether the query pertains to data available on a public cloud resource, or the query pertains to data available on a private cloud resource. When it is determined that the query pertains to the data available on the public cloud resource, the query is interpreted by using a first model trained on at least one machine learning technique on data from the public cloud. When it is determined that the query pertains to the data available on the private cloud resource, the query is interpreted by using a second model trained on at least one machine learning technique on the data from the private cloud.

    AUDIO WATERMARKING TO PREVENT MEETING HOWL
    54.
    发明公开

    公开(公告)号:US20240078077A1

    公开(公告)日:2024-03-07

    申请号:US17902005

    申请日:2022-09-02

    CPC classification number: G06F3/165 G10L19/018 G10L25/78 H04R3/005

    Abstract: Presented herein are techniques in which a first device connects to a communication session in which a plurality of devices communicates. The plurality of devices includes the first device and a second device. The first device outputs first audio that includes a first audio watermark associated with the communication session and the second device outputs second audio that includes a second audio watermark associated with the communication session. The first device detects the second audio watermark in the second audio outputted by the second device and one or more actions are performed in response to detecting the second audio watermark

    Hybrid cognitive system for AI/ML data privacy

    公开(公告)号:US11763024B2

    公开(公告)日:2023-09-19

    申请号:US17104639

    申请日:2020-11-25

    Abstract: Systems, methods, and devices are disclosed for cognitive collaboration systems on a hybrid node. A query is received by a virtual assistant running on a public cloud, and it is determined whether the query pertains to data available on a public cloud resource, or the query pertains to data available on a private cloud resource. When it is determined that the query pertains to the data available on the public cloud resource, the query is interpreted by using a first model trained on at least one machine learning technique on data from the public cloud. When it is determined that the query pertains to the data available on the private cloud resource, the query is interpreted by using a second model trained on at least one machine learning technique on the data from the private cloud.

    Audio fingerprinting for meeting services

    公开(公告)号:US11488612B2

    公开(公告)日:2022-11-01

    申请号:US17084915

    申请日:2020-10-30

    Abstract: The present technology can receive audio segments from sources within one or more conference room, and can create audio fingerprints from the sources. The audio fingerprints are optimized for audio in conference room environments, which include distortions from room impulse responses, and various encoding used by telecommunication networks. In some embodiments, when two audio segments are matched, a user equipment can be instructed to mute its speakers to avoid feedback. In some embodiments, when two audio segments are matched, a user equipment can be given instructions to join a conference taking place in the room in when the audio segment originated.

    GENERATING MEETING THREADS USING DIFFERENT COLLABORATION MODALITIES

    公开(公告)号:US20210168177A1

    公开(公告)日:2021-06-03

    申请号:US16701511

    申请日:2019-12-03

    Abstract: In accordance with an embodiment, a method is provided. First text is obtained by speech-to-text conversion of speech of a first participant of a collaboration event. Second text typed by a second participant of the collaboration event, who is connected as a text-only participant to the collaboration event, is received. A meeting thread is generated in a message space of the collaboration event using the first text and the second text. The meeting thread is provided for display on user devices associated at least with the first participant and the second participant.

    HYBRID COGNITIVE SYSTEM FOR AI/ML DATA PRIVACY

    公开(公告)号:US20210081564A1

    公开(公告)日:2021-03-18

    申请号:US17104639

    申请日:2020-11-25

    Abstract: Systems, methods, and devices are disclosed for cognitive collaboration systems on a hybrid node. A query is received by a virtual assistant running on a public cloud, and it is determined whether the query pertains to data available on a public cloud resource, or the query pertains to data available on a private cloud resource. When it is determined that the query pertains to the data available on the public cloud resource, the query is interpreted by using a first model trained on at least one machine learning technique on data from the public cloud. When it is determined that the query pertains to the data available on the private cloud resource, the query is interpreted by using a second model trained on at least one machine learning technique on the data from the private cloud.

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