Abstract: A system for providing a personalized assistant within a network-based communication session includes a processor and a memory storage device storing instructions. The system determines when a first communication session participant joins the network-based communication session after a threshold duration of time subsequent to the start time of the session. Upon determining the first participant has joined, the system obtains content associated with the session and creates request data for a pre-trained generative language model. The request data includes an instruction requesting a predetermined number of suggested utterances not present in the content, each utterance relating to one or more topics corresponding to the content. The system transforms the request data to a command based on a command template and provides the command to the generative language model.

Abstract: A system for providing a personalized assistant within a network-based communication service includes one or more processors and a memory storage device storing instructions thereon. During a network-based communication session, the system receives a query from a computing device of a first communication session participant and processes the query by determining that a second communication session participant has shared content via a content sharing feature of the network-based communication service. In response, the system provides the query and at least a portion of the shared content as input to a model, which dynamically constructs a prompt for use as input with a generative language model. The system then presents the prompt as input to the generative language model, receives a response as output from the generative language model, and causes presentation of the response to be presented to the communication session participant.

Abstract: Methods and systems are disclosed for scheduling a task of a user based on a cyber-physical-social (CPS) context of activities. The present disclosure is directed to increasing the efficiency of performing tasks by grouping tasks with the same or similar task CPS contexts so that they are performed in conjunction with one another. A stream of user activities is received that encompasses the CPS context, tasks are identified and classified based on a CPS context model. The CPS model is trained using CPS context and annotations for identified tasks as input to create classes of tasks. The classes of tasks from the model are used to group similar tasks. The present disclosure enables users to receive recommendations on clustering tasks with the same or similar contexts based on an online tool, a location, and collaborators to be performed together to improve productivity.

Abstract: Methods and systems are disclosed for scheduling a task of a user based on a cyber-physical-social (CPS) context of activities. The present disclosure is directed to increasing the efficiency of performing tasks by grouping tasks with the same or similar task CPS contexts so that they are performed in conjunction with one another. A stream of user activities is received that encompasses the CPS context, tasks are identified and classified based on a CPS context model. The CPS model is trained using CPS context and annotations for identified tasks as input to create classes of tasks. The classes of tasks from the model are used to group similar tasks. The present disclosure enables users to receive recommendations on clustering tasks with the same or similar contexts based on an online tool, a location, and collaborators to be performed together to improve productivity.