Data exposure for transparency in artificial intelligence

    公开(公告)号:US11783221B2

    公开(公告)日:2023-10-10

    申请号:US16428250

    申请日:2019-05-31

    IPC分类号: G06N20/00 G06F16/27 G06N5/045

    CPC分类号: G06N20/00 G06F16/27 G06N5/045

    摘要: A method, computer program product, and a system where a processor(s) obtains data from one or more sources, wherein a portion of the one or more sources comprise training data for a first artificial intelligence decision-making system. The processor(s) ingest data from each source into a corpus and ingest metadata corresponding to the data, into a volume accessible to a second artificial intelligence decision-making system. The processor(s) search public sources and obtain information describing quality and non-objective influence of the data from each source. The processor(s) provide as inputs to the second artificial intelligence decision-making system, the information and the metadata, to classify the quality and the non-objective influence of each source. The processor(s) obtains outputs comprising, for each source, a first rating classifying the quality of the source of the one or more sources. The processor(s) load the outputs into a blockchain, obtain rules, and designate, via the blockchain, based on the rules, the portion.

    Cognitive synchronization of digital files

    公开(公告)号:US11625364B2

    公开(公告)日:2023-04-11

    申请号:US16733553

    申请日:2020-01-03

    IPC分类号: G06F16/178 G06N3/08

    摘要: An embodiment includes receiving, by a processor, an indication that a first device transmitted a file having tracking metadata to a second device. The embodiment also includes receiving, by the processor, an indication of a modification to the file by the second device. The embodiment also includes evaluating, by the processor, the modification to the file using a cognitive process that analyzes the modification as it relates to profile information for a user and generates a significance value associated with the change. The embodiment also includes automatically initiating, by the processor and responsive to the generating of the significance value, a selected responsive action from among a plurality of responsive actions based at least in part on the significance value, where the automatic initiation of the selected responsive action includes automatic transmission of a notification to the first device regarding the modification to the file.

    LEARNED ROLLABLE FLEXIBLE DEVICE SOUND CREATION

    公开(公告)号:US20230092582A1

    公开(公告)日:2023-03-23

    申请号:US17448217

    申请日:2021-09-21

    摘要: One or more computer processors detect a contextual need for sound generation on a rollable display device, wherein the rollable display device comprises an array of micro-speakers mounted on one or more microfluidics panels and a plurality of embedded piezoelectric strips. The one or more computer processors identify one or more environmental parameters associated with an environment surrounding the rollable display device. The one or more computer processors determine a rolling profile associated with the rollable based on the detected contextual need and the one or more identified environmental parameters. The one or more computer processors roll the rollable display device based on the determined rolling profile utilizing the plurality of piezoelectric strips. The one or more computer processors adjust an output direction of each micro-speaker in the array of micro-speakers utilizing the respective microfluidics panel.

    IDENTIFYING RELATED MESSAGES IN A NATURAL LANGUAGE INTERACTION

    公开(公告)号:US20220309441A1

    公开(公告)日:2022-09-29

    申请号:US17837639

    申请日:2022-06-10

    摘要: By executing a natural language processing model on a set of natural language text describing a first engagement, a set of characteristics of the first engagement is generated. By executing the natural language processing model on a set of natural language text describing a future engagement, a set of characteristics of the future engagement is generated. The first engagement is determined to be above a threshold similarity with the future engagement. Using the skillset used in performing the first engagement, a required skillset of the future engagement is forecasted. By executing the natural language processing model on a set of natural language text describing a current skillset, a set of characteristics of the current skillset is generated. Using the required skillset of the future engagement and the set of characteristics of the current skillset, a learning path is generated.