Abstract: In one embodiment, a method includes receiving, from a client system associated with a user, a first user request that includes a reference to a target object and one or more of an attribute or a relationship of the target object. Visual data including one or more images portraying the target object may then be accessed, and the reference may be resolved to the target object portrayed in the one or more images. Object information of the target object that corresponds to the referenced attribute or relationship of the first user request may be determined based on a visual analysis of the one or more images. Finally, responsive to receiving the first user request, the object information of the target object may be stored in a multimodal dialog state.

Abstract: In one embodiment, a method includes receiving a first user request from a first user for generating a media montage from a client system during a dialog session with the first user, generating an initial media montage during the dialog session based on media collections associated with the first user, sending instructions for presenting the initial media montage to the client system during the dialog session, receiving a second user request from the first user from the client system during the dialog session for editing the initial media montage, generating an edited media montage from the initial media montage during the dialog session based on the second user request and a memory graph associated with the first user, and sending instructions for presenting the edited media montage to the client system during the dialog session.

Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.

Abstract: In one embodiment, a method includes receiving a first user input from a user from a client system associated with the user, accessing a memory-data store comprising digital memories, wherein each digital memory comprises media content items, temporal information associated with the media content items, and relational information pointing to second digital memories, selecting priming digital memories from the digital memories based on the first user input, proactively selecting related digital memories based on the relational information associated with the priming digital memories, generating a priming response based on the priming digital memories and a proactive suggestion based on the related digital memories, and sending instructions for presenting the priming response and the proactive suggestion to the client system responsive the first user input.

Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.