Abstract: Aspects extend to methods, systems, and computer program products for privilege-based task processing at a virtual assistant. An owner of a virtual assistant can assign other users privileges for interacting with the owner's calendar through the virtual assistant. To establish user privileges, the owner can enter information about himself or herself, including user permissions, into a Privileged Associates Database (“PAD”). An administrator can also configure some or all of this privileged associate(s) information to be entered automatically in the PAD. As such, a privileged associate can request that the virtual assistant schedule an event on the owner's calendar. In response, the virtual assistant refers to the PAD and checks privileges. The virtual assistant automatically synthesizes a response accordingly (e.g., scheduling the event, displaying schedule information, requesting owner confirmation, preventing the request, etc.) based on the owner's schedule and the associate's privileges.

Abstract: A multi-use card is presented. The multi-use card can be selectively configured to operate and/or function as any one of a plurality of associated cards (including credit cards, identity cards, access cards, membership cards, loyalty cards, and the like). The multi-use card can also be configured to display one or more messages from third parties on a display area on one or more surfaces of the card. The multi-use card includes communication abilities to communicate with one or more external computing devices by way of near field communications. The multi-use card is configured with associated cards and messages via the near field communications. Additionally, the multi-use card includes a power source that is charged by way of near field communications with the card.

Abstract: A system, media, and method for realtime popularity prediction for event and queries are provided. The popularity prediction is made by a prediction engine that is coupled to a search engine, a crawler, and a sentiment component. The prediction engine determines a change in popularity for an event or a query based on content provided by the crawler, sentiments identified by the sentiment component, and queries received in realtime by the search engine. The prediction engine may also use the content, sentiments, and queries to predict an outcome for a popularity based event.