Abstract: Techniques for providing digital assistant devices with the capability to plan and execute complex macrotasks. In an aspect, a digital assistant device queries an online macrotask repository for task templates associated with a macrotask. The task templates may be designed and configured by Internet crowd-sourcing, with oversight from human editors. Based on a retrieved task template, a digital assistant device may automatically execute autonomous microtasks specified by the task template, and further elicit user input for executing certain microtasks requiring user oversight and/or confirmation. The online macrotask repository enables digital assistant devices to execute a broad range of complex macrotasks that would otherwise be difficult to execute in a satisfactory manner.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: Systems, methods, and apparatuses are provided for generating a merged media playlist. A plurality of playlists is obtained, each playlist including a plurality of identifiers that identify an item of media content, such as a song. For each item of media content identified in each of the playlists, a feature value is obtained. The feature value may be, for instance, a value representing a characteristic associated with the item of media content. A feature score may be generated for each of the one or more features that is based on the number of occurrences of the feature value associated with the particular feature in a given playlist. The feature scores may then be used to generate a media content item score for each item of media content in each playlist. Based, at least on the media content item scores, a merged media playlist may be generated and ordered.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: A method disclosed herein for allows users to avoid such undesirable encounters by determining whether an undesirable contact of the user has opted for sharing location information, in response to determining that the undesirable contact has opted for sharing location information, collecting location signal from the undesirable contact, forecasting anticipated locations of the undesirable contact over a period based on the location signal of the undesirable contact, forecasting anticipated locations of the user over the period, determining potential of encounter between the user and the undesirable contact based on analysis of anticipated locations of the user and the anticipated locations of the undesirable contact over the period, generating an undesirable contact avoidance scheme based on the potential of encounter, and optionally notifying the user of the undesirable contact avoidance scheme.

Abstract: Techniques for providing digital assistant devices with the capability to plan and execute complex macrotasks. In an aspect, a digital assistant device queries an online macrotask repository for task templates associated with a macrotask. The task templates may be designed and configured by Internet crowd-sourcing, with oversight from human editors. Based on a retrieved task template, a digital assistant device may automatically execute autonomous microtasks specified by the task template, and further elicit user input for executing certain microtasks requiring user oversight and/or confirmation. The online macrotask repository enables digital assistant devices to execute a broad range of complex macrotasks that would otherwise be difficult to execute in a satisfactory manner.

Abstract: In various implementations, routing factors are identified based on a routing request associated with a user, where the routing factors include route preferences of the user. Routes are generated based on the routing request. Preference weights are determined for the route preferences, where the preference weights correspond to machine learning models based on sensor data provided by one or more sensors in association with the user. Route scores are determined for the routes based on the preference weights. A suggested route is provided to a user device associated with the user, where the suggested route corresponds to a selected route of the routes and is provided based on the route score of the selected route.

Abstract: In various implementations, routing factors are identified based on a routing request associated with a user, where the routing factors include route preferences of the user. Routes are generated based on the routing request. Preference weights are determined for the route preferences, where the preference weights correspond to machine learning models based on sensor data provided by one or more sensors in association with the user. Route scores are determined for the routes based on the preference weights. A suggested route is provided to a user device associated with the user, where the suggested route corresponds to a selected route of the routes and is provided based on the route score of the selected route.