Abstract: In one embodiment, a computing device establishes a secure connection with user equipment. The computing device receives a credential for a remote user account and connects to a remote user account based on the credential. The computing device generates a bonding key based on information associated with the remote user account and sends the bonding key to the user equipment through the secure connection for storage by the user equipment. Subsequent to the sending of the bonding key, proof of possession of the bonding key is required for establishing a trusted connection with the user equipment.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.

Abstract: Particular embodiments may locally store, at a client device of a first user, information associated with a plurality of nodes and a plurality of edges of a social graph received from a social-networking system. The first user may be associated with a first node of the social graph. The client device may detect that the first user is entering an input term. The client device may provide predictive typeahead results as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may correspond to one of the nodes of the social graph stored locally on the client device. Each predictive typeahead result may include at least one image associated with the corresponding node.

Abstract: In one embodiment, a computing device may execute software from a first portion of memory of the computing device. The computing device may download from a server a new version of the software. The client computing device may receive instructions from the server to request an over-the-air (OTA) download of the new version of the software. The instructions may be an out-of-band message. The new version of the software may be installed into a second portion of memory of the computing device, and the new version of the software is executed from the second portion of memory. The download of the new version of software may be pursuant to a manifest for the download to determine whether the computing device may download the new version of software.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.

Abstract: In one embodiment, in response to data to be transmitted to or from an electronic device, the electronic device determines whether the electronic device currently has a first network connection with a sufficiently high bandwidth. If the electronic device currently does not have a first network connection with a sufficiently high bandwidth, then the electronic device estimates a future time when the electronic device is likely to have a second network connection with a sufficiently high bandwidth, and schedules transmission of the data at the future time.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.

Abstract: In one embodiment, a computing device may execute software from a first portion of memory of the computing device. The computing device may download from a server a new version of the software. The client computing device may receive instructions from the server to request an over-the-air (OTA) download of the new version of the software. The instructions may be an out-of-band message. The new version of the software may be installed into a second portion of memory of the computing device, and the new version of the software is executed from the second portion of memory. The download of the new version of software may be pursuant to a manifest for the download to determine whether the computing device may download the new version of software.

Abstract: A set of customized dictionaries may be constructed for a particular user, each of the customized dictionaries including a different blending of one or more frequently used words collected from texts submitted by one or more users. A copy of the customized dictionaries may be sent to each of a plurality of electronic devices associated with the particular user to be stored on the electronic device and to aid the particular user in inputting text to the electronic device.

Abstract: In one embodiment, a computing device may execute software from a first portion of memory of the computing device. The computing device may download from a server a new version of the software. The client computing device may receive instructions from the server to request an over-the-air (OTA) download of the new version of the software. The instructions may be an out-of-band message. The new version of the software may be installed into a second portion of memory of the computing device, and the new version of the software is executed from the second portion of memory. The download of the new version of software may be pursuant to a manifest for the download to determine whether the computing device may download the new version of software.

Abstract: In one embodiment, a computing device may execute software from a first portion of memory of the computing device. The computing device may download from a server a new version of the software. The client computing device may receive instructions from the server to request an over-the-air (OTA) download of the new version of the software. The instructions may be an out-of-band message. The new version of the software may be installed into a second portion of memory of the computing device, and the new version of the software is executed from the second portion of memory. The download of the new version of software may be pursuant to a manifest for the download to determine whether the computing device may download the new version of software.

Abstract: Particular embodiments may locally store, at a client device of a first user, information associated with a plurality of nodes and a plurality of edges of a social graph received from a social-networking system. The first user may be associated with a first node of the social graph. The client device may detect that the first user is entering an input term. The client device may provide predictive typeahead results as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may correspond to one of the nodes of the social graph stored locally on the client device. Each predictive typeahead result may include at least one image associated with the corresponding node.

Abstract: In one embodiment, a computing device may execute software from a first portion of memory of the computing device. The computing device may download from a server a new version of the software. The client computing device may receive instructions from the server to request an over-the-air (OTA) download of the new version of the software. The instructions may be an out-of-band message. The new version of the software may be installed into a second portion of memory of the computing device, and the new version of the software is executed from the second portion of memory. The download of the new version of software may be pursuant to a manifest for the download to determine whether the computing device may download the new version of software.

Abstract: Particular embodiments may store, at a client device, information associated with nodes and edges of a social graph. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of the social graph. A first user may be associated with a first user node of the social graph. The client device may receive a character string from the first user, and identify, as the first user inputs the character string, an edge-type based on the character string and one or more edges of the identified edge-type, wherein the edges are locally stored on the client device. The client device may display one or more predictive typeahead results based on the identified edge-type and the identified edges. The predictive typeahead results may correspond to nodes stored locally on the client device.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.

Abstract: Particular embodiments may store, at a client device, information associated with nodes and edges of a social graph. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of the social graph. A first user may be associated with a first user node of the social graph. The client device may receive a character string from the first user, and identify, as the first user inputs the character string, an edge-type based on the character string and one or more edges of the identified edge-type, wherein the edges are locally stored on the client device. The client device may display one or more predictive typeahead results based on the identified edge-type and the identified edges. The predictive typeahead results may correspond to nodes stored locally on the client device.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.

Abstract: Particular embodiments may retrieve information associated with one or more nodes of a social graph from one or more data stores. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of a social graph. A first user may be associated with a first user node of the social graph. Particular embodiments may detect that the first user is entering an input term. Predictive typeahead results may be provided as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may include at least one image. Each predictive typeahead result may correspond to at least one node of the social graph.

Abstract: In one embodiment, collecting a plurality of words from texts submitted by one or more users; for each of a plurality of communication categories, determining a usage frequency of each of one or more of the words within the communication category based on the texts; and constructing one or more customized dictionaries that each comprise a different blending of selected words.

Abstract: In one embodiment, receiving, at a first computing device associated with a social-networking system and from a second computing device, a first request to verify an identity of a user of the social-networking system; sending, by the first computing device and to a mobile device associated with the user, a second request for information about the user; receiving, at the first computing device and from the mobile device, the information about the user; determining, by the first computing device, a confidence score indicating a probability that the identity of the user is true based on the information about the user received from the mobile device and information available to the social-networking system; and sending, by the first computing device and to the second computing device, the confidence score.