Abstract: A system implements a method that comprises receiving end user information of end users to produce synthesized user research data, storing the synthesized user research data in a knowledge corpus, and segmenting the end users into one or more end user segments based on end user roles or end user categories. For each end user segment, a persona is generated, each representing a composite of end users in a respective end user segment. The method further comprises training each persona with training data from the synthesized user research data of the end users in the respective end user segment, and generating a dialog engine for each persona based on the training. An avatar is connected to each persona, and each avatar is made accessible for dialog with metaverse users in the Metaverse, which is a 3D virtual reality environment.

Abstract: A computer-implemented method, a computer system and a computer program product predict and project vehicle movements in an augmented reality (AR) environment. The method includes obtaining telemetry data from a vehicle in an environment, where the telemetry data is selected from a group consisting of: video data, audio data and text data. The method also includes determining a path for the vehicle based on the telemetry data. The method further includes identifying an augmented reality device in the path, where the augmented reality device is associated with a user proximate to the path. Lastly, the method includes displaying the path using the augmented reality device in the augmented reality (AR) environment.

Abstract: An audio stream received from an audio transceiver. The audio stream is in an environment that includes audio of a first user. An acoustic communication of the first user is detected from the audio stream. An audio intent trigger of the first user is identified from the audio stream and based on the acoustic communication. An assistance action for the first user is initiated in response to the audio intent trigger and by a voice-based interface.

Abstract: A computer-implemented method, a computer system and a computer program product generate a contextual display for a mobile computing device. The method includes identifying a task for the mobile computing device, wherein the task comprises a set of applications on the mobile computing device. The method also includes obtaining application usage data for each application in the set of applications and determining an application context for the task based on the application usage data and the set of applications, wherein the application context includes usage requirements for each application. In addition, the method includes generating a tile view for each application in the set of applications, wherein each tile view is laid out based on the usage requirements. Lastly, the method includes displaying a task view on the mobile computing device, wherein the task view is generated by laying out the tile views based on the usage requirements.

Abstract: In an approach for optimizing project and team success, prior to a user initiating a project, a processor creates a digital profile. A processor sets up the digital profile with a set of data gathered from one or more project related documents for a set of previous projects of the user. Responsive to the user initiating the project, a processor identifies one or more documents related to the project. A processor analyzes the one or more documents related to the project. A processor predicts an outcome of the project using machine learning, wherein the outcome of the project is a set of measures indicating a success factor, a quality factor, and a risk factor of the project. A processor generates an optimization suggestion, wherein the optimization suggestion is a suggestion to adjust one or more parameters of the project. A processor outputs the optimization suggestion to the user.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: storing into a storage device a video data file; examining video file data defining the video data file, wherein the examining includes determining a relevancy of a section of the video data file; reducing a size of file data defining the section of the video data file in dependence on the determining the relevancy of the section of the video data file; storing a reduced-size version of the video data file into the storage device, the reduced-size version of the video data file having a reduced size relative to the video data file by performance of the reducing the size of file data defining the section of the video data file in dependence on the determining the relevancy of the section of the video data file.

Abstract: A computer-implemented process for facilitating generation of a user interface design. The computer-implemented method provides for one or more processors to identify one or more elements added to a screen design by a first designer. The one or more processors predict one or more next elements of the screen design, based on the identified one or more elements added to the screen design and a learning model trained by machine learning techniques using a convolutional neural network. The one or more processors present the one or more next design elements as a recommendation to the first designer. The one or more processors determine a selection decision made by the first designer of the one or more next elements from the recommendation, and the one or more processors update learning model, based on selection decisions made by the first designer.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: storing into a storage device a video data file; examining video file data defining the video data file, wherein the examining includes determining a relevancy of a section of the video data file; reducing a size of file data defining the section of the video data file in dependence on the determining the relevancy of the section of the video data file; storing a reduced-size version of the video data file into the storage device, the reduced-size version of the video data file having a reduced size relative to the video data file by performance of the reducing the size of file data defining the section of the video data file in dependence on the determining the relevancy of the section of the video data file.

Abstract: Artificial intelligence is employed to assess a user's workflow on a task by receiving data regarding a workflow of a user completing a task, and assessing the data to identify attributes of the workflow that is expressed in a series of steps. The steps of the workflow are analyzed to identify areas of improvement. Augmentations may be generated from a plurality of technology fitments matched to the areas for improvement in the steps of the workflow. A user experience template is generated, in which content of the user experience template is selected based upon at least an archetype for which the generating the augmentation from the plurality of technology fitments was performed. The augmentations are formatted in the user experience template and sent to a user device for communicating to the user.

Abstract: System and methods for type ahead search amelioration based on image processing are provided. In embodiments, a method includes: capturing, by a computing device, image data based on images viewed by a user during a computing session; converting, by the computing device, the image data to text using image processing; and storing, by the computing device, the text in a temporary buffer of a type ahead search function, wherein the text constitutes image context data for use by the type ahead search function.

Abstract: Aspects of the present disclosure relate to generating and visualizing subgroups of participants within web-based conferences. Participant data for each of a plurality of participants attending a web-based conference can be obtained. The participant data can be analyzed for each of the plurality of participants. Each of the participants can be mapped to a subgroup of two or more subgroups based on the analysis. The two or more subgroups can then be visualized within the web-based conference to the participants.

Abstract: An approach for creating avatars of team members on a project team. The approach retrieves data associated with team members of a project team. The approach creates avatars of the team members based on the data. The approach displays the avatars to the team members, requesting permission to from the team members to use the avatars to represent the team members. With permission, the approach creates a plurality of avatars of different dimensions to use on different platforms. The approach displays the avatars during online team meetings as a representation of the respective team member.

Abstract: An approach for predicting team dynamics based on changing circumstances. The approach retrieves profiles associated with a group of first team members of a project team. The approach selects a virtual reality (VR) scenario to interact with the group of first team members. The approach executes the VR scenario based on the profiles. The approach receives VR input from an interacting team member interacting with the VR scenario. The approach predicts responses of the group of first team members to the VR input. The approach analyzes the responses and provides the interacting team member a ranked list of scenario outcomes.

Abstract: An approach for optimizing the selection of team members on a project team. The approach retrieves data associated with prospective members of a project team. The approach generates team member personality scores based on a machine learning model. The approach generates a team compatibility score based on a portion of the prospective team member personality scores. The approach calculates a predicted project success score based on the team compatibility score. The approach assigns prospective team members to the team based on maximizing the predicted project success score.

Abstract: System and methods for type ahead search amelioration based on image processing are provided. In embodiments, a method includes: capturing, by a computing device, image data based on images viewed by a user during a computing session; converting, by the computing device, the image data to text using image processing; and storing, by the computing device, the text in a temporary buffer of a type ahead search function, wherein the text constitutes image context data for use by the type ahead search function.

Abstract: In an approach to resource monitoring and allocation recommendation, a computer determines a work activity for a risk assessment. A computer determines one or more resources assigned to the work activity. A computer determines one or more current activities associated with the one or more resources assigned to the work activity. Based on the one or more resources assigned to the work activity and on the one or more current activities associated with the one or more resources assigned to the work activity, a computer determines a confidence level associated with successful completion of the work activity. A computer determines the confidence level does not exceed a pre-defined threshold. A computer determines one or more resource scenarios to improve the confidence level. A computer ranks the one or more resource scenarios. A computer generates a resource allocation recommendation based on the ranked one or more resource scenarios.

Abstract: Artificial intelligence is employed to assess a user's workflow on a task by receiving data regarding a workflow of a user completing a task, and assessing the data to identify attributes of the workflow that is expressed in a series of elements. The elements of the workflow are analyzed to identify areas of improvement. Augmentations may be generated from a plurality of technology fitments matched to the areas for improvement in the elements of the workflow. The augmentations are sent to a user device for communicating to the user. The method may further include receiving confirmation of fitment to business practices of persona; and adjusting augmentation responsive to confirmation of fitment.

Abstract: An apparatus for an mentor and expertise matching includes a profile module configured to populate a mentee profile in response to receiving information from the mentee. The mentee profile includes information about skills and preferences of the mentee. A scoring module compares information from the mentee profile with a plurality of mentor profiles from a mentor database to determine, using a mentor scoring algorithm, a mentor score for each of the plurality of mentor profiles. A selection module is configured to receive a mentee selection of a mentor from one or more mentors presented to the mentee. Each of the mentors presented to the mentee includes a higher mentor score than other mentors. A mentorship tracking module is configured to track interactions between the mentor and the mentee, and a mentor feedback module is configured to update a mentor profile of the mentor based on feedback from the interactions.

Abstract: Aspects of the present disclosure relate to generating and visualizing subgroups of participants within web-based conferences. Participant data for each of a plurality of participants attending a web-based conference can be obtained. The participant data can be analyzed for each of the plurality of participants. Each of the participants can be mapped to a subgroup of two or more subgroups based on the analysis. The two or more subgroups can then be visualized within the web-based conference to the participants.

Abstract: Aspects of the present invention disclose a method for recommending an activity based on a social media profile, IoT devices, and historical engagements of the user. The method includes one or more processors determining a past activity of a user based at least in part on social media posts and internet of things (IoT) enabled devices of the user. The method further includes determining a set of historical conditions corresponding to the past activity, wherein the set of conditions correspond to a positive sentiment of the user. The method further includes identifying a location of the user. The method further includes generating an activity recommendation based on the location of the user and the set of historical conditions corresponding to the past activity, wherein the activity recommendation includes a set of future conditions of a future activity, wherein the set of future conditions correlate with the set of historical conditions.