Abstract: The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

Abstract: Aspects of the present disclosure relate to obtaining task and/or list information from various types of media files. In examples, an image of an environment may be obtained, where the image may include a depiction of a plurality of tasks. The tasks may be extracted from the image and assigned to one or more users based contextual information within the image. In some examples, tasks within an image may be identified based on positional information of the text and/or character delimiters. In some examples, audio information may be received and processed such that the audio information is converted to text. The text may then be parsed to extract one or more items of a list and/or one or more tasks.

Abstract: The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

Abstract: Systems and methods can be implemented to provide suggestions to a user device to execute user tasks in a variety of applications. In various embodiments, a set of tasks of a user from a number of task sources are identified for possible consolidation. The tasks in the set can be analyzed to identify a location to accomplish the tasks, estimate times to complete the tasks at the identified locations, and compute routes to the locations from a starting location or compute routes with respect to a route to another location of another task of the set of tasks. The identified locations, the estimated times, and the computed routes can be used to determine which tasks of the set of tasks are available for consolidation. One or more suggestions of task consolidations can be generated to or within the user device. Additional systems and methods are disclosed.

Abstract: Generally discussed herein are devices, systems, and methods for task classification. A method can include modifying a representation of a source sentence of a source sample from a source corpus to more closely resemble a representation of target sentences of target samples from a target corpus, operating, using a machine learning model trained using the modified representation of the source sentence, with the target sample to generate a task label, the task label indicating whether the target sample includes a task, and causing a personal information manager (PIM) to generate a reminder, based on whether the target sample includes the task.

Abstract: Aspects of the present disclosure relate to systems and methods for generating smart notifications for comments associated with collaborative content. A machine learning model is disclosed which is operable to receive a comment and contextual information related to the comment. Based upon the received input, the machine learning model is able to determine a classification for an intent associated with the comment. Based upon the determined intent, a comment is identified as requiring action by one or more of the collaborative users. Aspects of the present disclosure generate a smart notification that can be presented as part of a collaborative user interface to highlight comments that require action.

Abstract: The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

Abstract: The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

Abstract: Aspects of the present disclosure relate to a smart coach for optimizing an ordering of tasks. In examples, a plurality of tasks associated may be received by the smart coach. In some instances, the plurality of tasks may be for one or more users. Task related information associated with at least one optimization criterion may be received at a user interface or retrieved from storage. An ordering of the plurality of tasks with respect to the at least one optimization criterion may then be generated, where the at least one optimization criterion may be based on at least one of a user optimization goal, an efficiency goal, and a task priority level. The optimized ordering of tasks may then be displayed at a user interface in a task execution order. In some examples, the ordering of tasks may be displayed as an agenda and/or in a calendar view.

Abstract: Aspects of the present disclosure relate to obtaining task and/or list information from various types of media files. In examples, an image of an environment may be obtained, where the image may include a depiction of a plurality of tasks. The tasks may be extracted from the image and assigned to one or more users based contextual information within the image. In some examples, tasks within an image may be identified based on positional information of the text and/or character delimiters. In some examples, audio information may be received and processed such that the audio information is converted to text. The text may then be parsed to extract one or more items of a list and/or one or more tasks.

Abstract: The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

Abstract: Generally discussed herein are devices, systems, and methods for task classification. A method can include modifying a representation of a source sentence of a source sample from a source corpus to more closely resemble a representation of target sentences of target samples from a target corpus, operating, using a machine learning model trained using the modified representation of the source sentence, with the target sample to generate a task label, the task label indicating whether the target sample includes a task. and causing a personal information manager (PIM) to generate a reminder, based on whether the target sample includes the task.

Abstract: A Personal Virtual Assistant (PVA) system takes existing inputs and processes them to understand the user's personality, intent, etc., through analysis of features such as the user's tone, language use, vocal volume, facial expressions, and context from device use and surroundings. As a result of the processing, the PVA system augments how it responds and interacts with the user. Such augmented responses may include simple things like changing the assistant's tone to complimenting the user's mood, as well as changing her use of language, volume, and the way she shares information, like giving good news when the user might be down, or suppressing bad news when the time is not right for the user to optimally process it.

Abstract: A Personal Virtual Assistant (PVA) system takes existing inputs and processes them to understand the user's personality, intent, etc., through analysis of features such as the user's tone, language use, vocal volume, facial expressions, and context from device use and surroundings. As a result of the processing, the PVA system augments how it responds and interacts with the user. Such augmented responses may include simple things like changing the assistant's tone to complimenting the user's mood, as well as changing her use of language, volume, and the way she shares information, like giving good news when the user might be down, or suppressing bad news when the time is not right for the user to optimally process it.

Abstract: Systems and methods can be implemented to provide suggestions to a user device to execute user tasks in a variety of applications. In various embodiments, a set of tasks of a user from a number of task sources are identified for possible consolidation. The tasks in the set can be analyzed to identify a location to accomplish the tasks, estimate times to complete the tasks at the identified locations, and compute routes to the locations from a starting location or compute routes with respect to a route to another location of another task of the set of tasks. The identified locations, the estimated times, and the computed routes can be used to determine which tasks of the set of tasks are available for consolidation. One or more suggestions of task consolidations can be generated to or within the user device. Additional systems and methods are disclosed.

Abstract: A processing system is described which generates stimulus information (SI) having one or more stimulus components (SCs) selected from an inventory of such components. The processing system then presents the SI to a group of human recipients, inviting those recipients to provide linguistic descriptions of the SI. The linguistic information that is received thereby has an implicit link to the SCs. Further, each linguistic component is associated with at least one feature of a target environment, such as a target computer system. Hence, the linguistic information also maps to the features of the target environment. These relationships allow applications to use the linguistic information to interact with the target environment in different ways. In one case, the processing system uses a challenge-response authentication task presentation to convey the stimulus information to the recipients.

Abstract: A processing system is described which generates stimulus information (SI) having one or more stimulus components (SCs) selected from an inventory of such components. The processing system then presents the SI to a group of human recipients, inviting those recipients to provide linguistic descriptions of the SI. The linguistic information that is received thereby has an implicit link to the SCs. Further, each linguistic component is associated with at least one feature of a target environment, such as a target computer system. Hence, the linguistic information also maps to the features of the target environment. These relationships allow applications to use the linguistic information to interact with the target environment in different ways. In one case, the processing system uses a challenge-response authentication task presentation to convey the stimulus information to the recipients.

Abstract: Computer-readable media, systems, and methods for intelligent information display are described. In embodiments, a display environment is monitored for one or more audience data and, upon receiving the one or more audience data, display information is processed in accordance with the one or more audience data and the processed display information is presented. In various embodiments, the audience data includes user gestures that indicate a communication with the intelligent information display, such as gestures indicating a mouse motion or a mouse click. In various other embodiments, the audience data includes demographic indicia such as the typical gender and/or typical age of an audience in a display environment.

Abstract: A transparent electromagnetic shield to protect solar panels and the like from dust deposition. The shield is a panel of clear non-conducting (dielectric) material with embedded parallel electrodes. The panel is coated with a semiconducting film. Desirably the electrodes are transparent. The electrodes are connected to a single-phase AC signal or to a multi-phase AC signal that produces a travelling electromagnetic wave. The electromagnetic field produced by the electrodes lifts dust particles away from the shield and repels charged particles. Deposited dust particles are removed when the electrodes are activated, regardless of the resistivity of the dust. Electrostatic charges on the panel are discharged by the semiconducting film. When used in conjunction with photovoltaic cells, the power for the device may be obtained from the cells themselves. For other surfaces, such as windshields, optical windows and the like, the power must be derived from an external source.