Abstract: An architecture related to the creation of, and attribution to, experiences based on location, popularity, captured media, and/or objects. A method can comprise receiving social media data associated with a user associated with a user identity, generating an attributable identity token based on the social media data and a learning model, wherein the attributable identity token is associated with the user identity and is representative of location data and experience data, and wherein the learning model comprises a collection of rules, and disseminating, by the device, the attributable identity token to a group of user identities associated with a social media operator entity.

Abstract: Tasks associated with users can be managed for efficient workflow management. A task management component (TMC) can analyze, including performing artificial intelligence-based analysis on, task-related information relating to associated with a user(s), assessment information relating to assessing performance or expertise associated with a task, biometric information relating to health, diet, and activity associated with the user(s), and/or user(s) feedback information. Based on the analysis, TMC can adaptively adjust respective attributes associated with respective tasks, resulting in respective adjusted attributes associated with the respective tasks. Based on the respective adjusted attributes, TMC can determine task information and can present the task information to a device(s) associated with the user(s) to facilitate performance of the tasks.

Abstract: Aspects of the subject disclosure may include, for example, obtaining contextual information associated with a user, wherein the user is engaged in an immersive environment using a target user device, and wherein the contextual information comprises user profile data, data regarding a location of the user, data regarding one or more inputs provided by the user, or a combination thereof, receiving data regarding a metaverse object in the immersive environment, determining a relevance of the metaverse object to the user based on the contextual information and the data regarding the metaverse object, responsive to the determining the relevance of the metaverse object to the user, generating a personalized recommendation or review of the metaverse object for the user, and causing the personalized recommendation or review to be provided to the user in the immersive environment for user consumption. Other embodiments are disclosed.

Abstract: Virtual assistants (VAs) can be managed in interactions with users, other VAs, and devices, including in connection with medical care associated with users. A VA management component (VAMC) can analyze medical information and other information relating to users, including information obtained by a VA(s) from a user(s). Based on the analysis, VAMC can determine a model relating to medical care associated with users. VAMC can determine a proposed action relating to the health or medical care associated with a user based on the model. A VA can present action information relating to the proposed action, or other information relating to health or medical care associated with the user, to the user or a device associated with the user. VAMC can determine drug-drug or drug-food interactions or side effects, and the VA can notify the user regarding the drug-drug or drug-food interactions or side effects.

Abstract: In one example, a method performed by a processing system including at least one processor includes downloading at least one digital resource relating to a user-defined location, acquiring data about the user-defined location from a sensor located in the user-defined location, while the user is present in the user-defined location, detecting a user need based on the data from the sensor, augmenting the at least one digital resource with the data from the sensor to produce content that is responsive to the user need, and presenting the content that is responsive to the user need.

Abstract: Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: detecting a target behavior of a person and a first location of the person using a computer vision system in a monitored location; confirming the first location detected by the computer vision system matches a mobile location of a mobile device possessed by the person, wherein the mobile device is connected to a network providing communication services at the monitored location, and wherein the mobile location is determined by the network; and providing a reward to the mobile device responsive to the target behavior detected and the first location matching the mobile location. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device with a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of ingesting facilities infrastructure data for more than one facility; training a machine-learning (ML) model from the facilities infrastructure data, wherein the ML model infers features absent in the facilities infrastructure data and yields a score of a facility described by the facilities infrastructure data; receiving a query for a region from a user; identifying one or more facilities provided in the region; generating a map of the one or more facilities using the ML model; and providing a visualization interface to the user including the map and the score of the one or more facilities responsive to the query. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of constructing a composite machine-learning (ML) model for facilities infrastructure from facilities infrastructure data; training the composite ML model with historical availability data, historical performance data, and historical error rates, wherein the composite ML model yields quality of the facilities infrastructure; receiving a query of a facility in an area from a user; predicting a quality of the facility based on recent facilities data using the composite ML model; and providing the quality of the facility responsive to the query. Other embodiments are disclosed.

Abstract: A volumetric content enhancement system (“the system”) can annotate at least a portion of a plurality of voxels from a volumetric video with contextual data. The system can determine at least one actionable position within the volumetric video. The system can create an annotated volumetric video that includes the volumetric video, an annotation with the contextual data, and the at least one actionable position. The system can provide the annotated volumetric video to a volumetric content playback system. The system can obtain viewer feedback associated with the viewer and can determine an emotional state of the viewer based, at least in part, upon the viewer feedback. The system can receive viewer position information that identifies a specific actionable position of the viewer. The system can generate manipulation instructions to instruct the volumetric content playback system to manipulate the annotated volumetric content to achieve a desired emotional state of the viewer.

Abstract: Aspects of the subject disclosure may include, for example, obtaining portions of video content from a video game from video game server(s) associated with a video game provider, selecting a first portion of video content from the portions of the video content, and providing the first portion to device(s) associated with viewer(s). Each device presents the first portion of the video content. Further embodiments include obtaining popularity information from the device(s) according to feedback based on presenting the first portion of the video content to the device(s), determining that the popularity information satisfies a popularity threshold associated with the video content, determining a subject matter corresponding to the first portion of the video content, and identifying a second portion of the video content from the video game to be recorded according to the subject matter. Other embodiments are disclosed.

Abstract: A system for embedding users' preferences and behaviors based on interactions with an array of devices.

Abstract: A volumetric content enhancement system (“the system”) can annotate at least a portion of a plurality of voxels from a volumetric video with contextual data. The system can determine at least one actionable position within the volumetric video. The system can create an annotated volumetric video that includes the volumetric video, an annotation with the contextual data, and the at least one actionable position. The system can provide the annotated volumetric video to a volumetric content playback system. The system can obtain viewer feedback associated with the viewer and can determine an emotional state of the viewer based, at least in part, upon the viewer feedback. The system can receive viewer position information that identifies a specific actionable position of the viewer. The system can generate manipulation instructions to instruct the volumetric content playback system to manipulate the annotated volumetric content to achieve a desired emotional state of the viewer.

Abstract: A volumetric content enhancement system (“the system”) can annotate at least a portion of a plurality of voxels from a volumetric video with contextual data. The system can determine at least one actionable position within the volumetric video. The system can create an annotated volumetric video that includes the volumetric video, an annotation with the contextual data, and the at least one actionable position. The system can provide the annotated volumetric video to a volumetric content playback system. The system can obtain viewer feedback associated with the viewer and can determine an emotional state of the viewer based, at least in part, upon the viewer feedback. The system can receive viewer position information that identifies a specific actionable position of the viewer. The system can generate manipulation instructions to instruct the volumetric content playback system to manipulate the annotated volumetric content to achieve a desired emotional state of the viewer.

Abstract: Aspects of the subject disclosure may include, for example, a method of receiving, by a processing system including a processor, viewership data for a plurality of viewers watching a program; identifying, by the processing system, an anomalous event from the viewership data, wherein the viewership data includes data points per viewer logged on a per second basis, and wherein the processing system identifies the anomalous event using a pattern recognition algorithm; analyzing, by the processing system, the viewership data to determine a reason for the anomalous event; and providing, by the processing system, a user interface that presents a comparison of the anomalous event versus a standard and indicia for the reason for the anomalous event. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a processing system including a processor and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving immersive media content; creating foreground information for rendering foreground video content of the immersive media content; receiving a first point-of-view (PoV) of a first viewer operating a first display device; generating a background video content from the immersive media content; sending the foreground information to the first display device; and sending a first portion of the background video content to the first display device, wherein the first portion is based on the first PoV. Other embodiments are disclosed.

Abstract: A system for embedding users' preferences and behaviors based on interactions with an array of devices.

Abstract: Aspects of the subject disclosure may include, for example, engaging in first communications between a device and a first user device, the first communications comprising a first visual representation sent from the first user device to the device of first actions performed by a first user; engaging in second communications between the device and a second user device, the second communications comprising a second visual representation sent from the second user device to the device of second actions performed by a second user, the second communications occurring substantially simultaneously with the first communications; making a first determination via machine learning, based at least in part upon the first visual representation, whether performance of a first task by the first user has been completed; making a second determination via the machine learning, based at least in part upon the second visual representation, whether performance of the first task by the second user has been completed; responsive to th

Abstract: Aspects of the subject disclosure may include, for example, a method of receiving, by a processing system including a processor, viewership data for a plurality of viewers watching a program; identifying, by the processing system, an anomalous event from the viewership data, wherein the viewership data includes data points per viewer logged on a per second basis, and wherein the processing system identifies the anomalous event using a pattern recognition algorithm; analyzing, by the processing system, the viewership data to determine a reason for the anomalous event; and providing, by the processing system, a user interface that presents a comparison of the anomalous event versus a standard and indicia for the reason for the anomalous event. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a method that includes determining, by a processing system including a processor, that a viewer is viewing primary content for a first time; capturing, by the processing system, an emotive response of the viewer as the primary content is viewed during the first time; determining that the viewer is viewing the primary content at a subsequent time, wherein the subsequent time is later than the first time; detecting the emotive response of the viewer as the primary content is viewed during the subsequent time; retrieving external media responsive to detecting the emotive response; and displaying the external media. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a processing system including a processor and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving immersive media content; creating foreground information for rendering foreground video content of the immersive media content; receiving a first point-of-view (PoV) of a first viewer operating a first display device; generating a background video content from the immersive media content; sending the foreground information to the first display device; and sending a first portion of the background video content to the first display device, wherein the first portion is based on the first PoV. Other embodiments are disclosed.