Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating composite actions for a user account. In particular, in one or more embodiments, the disclosed systems determine a set of tasks performable by the user account using software tools on a client device. In some embodiments, the disclosed systems generate a task initialization prompt to provide to a large language model. Additionally, in some implementations, the disclosed systems generate a composite action comprising a hybridized combination of the set of tasks performable by the user account along with a set of content items relevant to the set of tasks. Moreover, in some embodiments, the disclosed systems provide access to the composite action and the set of content items via a user interface of the client device. Furthermore, in some implementations, the disclosed systems generate and insert predicted content into a content item without user input.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing an aggregated feed interface that includes or presents aggregate summaries for thread data across multiple data feeds of a user account. In some embodiments, the disclosed systems generate an aggregate summary by extracting digital communications and other thread data from a variety of data feeds across multiple computer applications and by utilizing a summary generation model to generate an aggregate summary that combines and condenses the thread data from the different data feeds. For example, the disclosed systems determine topics associated with thread data from various data feeds and generates different aggregate summaries for different topics.

Abstract: Methods, systems, and media for object grouping and manipulation in immersive environments are provided. In some embodiments, a method can include: displaying a plurality of virtual objects in an immersive environment; generating a group virtual object that includes a first virtual object and a second virtual object, the group virtual object including a handle interface element for interacting with the group virtual object and a selectable indicator associated with the first virtual object and the second virtual object; displaying the group virtual object along with the handle interface element and the selectable indicator in the immersive environment; and in response to detecting a selection of the selectable indicator, displaying a user interface for interacting with the group virtual object.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and searching a hybrid search index. In some embodiments, the disclosed systems generate a hybrid search index that comprises one or more content items stored at a content management system or at external network locations linked to the content management system via software connectors along with world state data associated with the one or more content items. The disclosed systems can generate a search result from the hybrid search index in response to receiving a search query of the hybrid search index. In some cases, the disclosed systems can rank one or more content items included in the search result based on observation layer data of the one or more content items.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that dynamically capture, organize, and utilize digital media clips. For example, in one or more implementations, the disclosed systems can capture and generate digital media clips of content items that include both content metadata of the content items as well as contextual metadata of contextual signals surrounding the content item. Additionally, in some implementations, the disclosed systems analyze contextual metadata to search, retrieve, discover, and organize new and existing digital media clips. Further, in various implementations, the disclosed systems facilitate generating digital media clip libraries as well as the creation of digital media collections, where different types of digital media clips can be combined in a cohesive interactive graphical user interface.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that dynamically capture, organize, and utilize digital media clips. For example, in one or more implementations, the disclosed systems can capture and generate digital media clips of content items that include both content metadata of the content items as well as contextual metadata of contextual signals surrounding the content item. Additionally, in some implementations, the disclosed systems analyze contextual metadata to search, retrieve, discover, and organize new and existing digital media clips. Further, in various implementations, the disclosed systems facilitate generating digital media clip libraries as well as the creation of digital media collections, where different types of digital media clips can be combined in a cohesive interactive graphical user interface.

Abstract: This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.

Abstract: This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can utilize language neural networks to automatically generate draft electronic communications for a user account. For example, the disclosed systems leverage composition parameters of a user account (determined from historical electronic communications of the user account, digital content items corresponding to the user account, and/or other application data) with a neural network to automatically generate draft electronic communications that reflect a composition style of a user account and accurately addresses a context of a communication thread. In addition, the disclosed systems can generate electronic communications using the communication generation neural network and save the electronic communication as a draft (e.g., for review by a user of the user account) and/or automatically transmit the electronic message to a recipient user account.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing an intelligent assistant interface that integrates with a large language model and a knowledge graph to adaptively change its appearance for presenting and interacting with different content items from various sources. In some embodiments, the disclosed systems provide an intelligent assistant interface that includes a set of interface elements selectable to interact with a large language model. Based on an input intent, the disclosed systems can utilize the large language model to analyze a knowledge graph for accessing and/or generating content items for display within the intelligent assistant interface.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating a content stack utilizing one or more machine-learning models. In some implementations, the disclosed systems generate and provide, to a user account, a content stack that includes content items corresponding to a topic prompt for the user account. For instance, in some implementations, the disclosed systems utilize content-based signals and account-based signals to generate an account-specific stack formulation graph that represents a plurality of content items and relationships of the content items with each other and with the user account. Additionally, in some implementations, the disclosed systems analyze the account-specific stack formulation graph to generate a content stack from the plurality of content items, the content stack comprising a set of content items corresponding to the topic prompt.

Abstract: Methods, systems, and media for object grouping and manipulation in immersive environments are provided. In some embodiments, a method can include: displaying a plurality of virtual objects in an immersive environment; generating a group virtual object that includes a first virtual object and a second virtual object, the group virtual object including a handle interface element for interacting with the group virtual object and a selectable indicator associated with the first virtual object and the second virtual object; displaying the group virtual object along with the handle interface element and the selectable indicator in the immersive environment; and in response to detecting a selection of the selectable indicator, displaying a user interface for interacting with the group virtual object.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing coaching insights using a large language model to process coaching prompts. In some embodiments, the disclosed systems generate a coaching prompt from a knowledge graph encoding data from data sources, such as an observation layer and a world state. The disclosed systems also determine a pulse status of a user account to inform a coaching prompt. Additionally, the disclosed systems provide the coaching prompt to a large language model for generating a coaching insight to improve the pulse status.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.

Abstract: This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can utilize language neural networks to automatically generate draft electronic communications for a user account. For example, the disclosed systems leverage composition parameters of a user account (determined from historical electronic communications of the user account, digital content items corresponding to the user account, and/or other application data) with a neural network to automatically generate draft electronic communications that reflect a composition style of a user account and accurately addresses a context of a communication thread. In addition, the disclosed systems can generate electronic communications using the communication generation neural network and save the electronic communication as a draft (e.g., for review by a user of the user account) and/or automatically transmit the electronic message to a recipient user account.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating content clusters from topic data and focus data, generating content collections from content clusters, storing and restoring desktop scene layouts, and storing and arranging video call scenes. In some embodiments, the disclosed systems generate content clusters based on topic data and focus data associated with content items within a content management system and/or accessed via the internet. The disclosed systems can also generate content collections for a user account of the content management system from the content clusters. In some embodiments, the content scene system can further store and restore desktop scene layouts for arranging application windows presenting content items. Further, the disclosed systems can store and arrange particular desktop scene layouts for video call scenes.