Abstract: Distributing warehousing of products by receiving, by a distributed warehousing system, a first notification that a product was delivered to a first customer at a first location. The technology receives a designation of the delivered product for return, and then identifies a second delivery location for the designated product, the second delivery location being a location of a second customer. A second notification of pickup of the designated product from the first location is then received by the technology. The technology then directs delivery of the product to the second location, without an intermediate storage of the product at a brick-and-mortar distribution facility, in response to receiving the second notification, and receives a third notification that the product was delivered to the second location.

Abstract: Distributing warehousing of products by receiving, by a distributed warehousing system, a first notification that a product was delivered to a first customer at a first location. The technology receives a designation of the delivered product for return, and then identifies a second delivery location for the designated product, the second delivery location being a location of a second customer. A second notification of pickup of the designated product from the first location is then received by the technology. The technology then directs delivery of the product to the second location, without an intermediate storage of the product at a brick-and-mortar distribution facility, in response to receiving the second notification, and receives a third notification that the product was delivered to the second location.

Abstract: Systems and techniques are provided for an adaptive media library for application ecosystems. A request may be received for a media item from an application. The request may include an application state of the application and user data associated with a user of the application. A media item may be selected from among media items in a media database based on the application state, the user data, media selection criteria, and metadata for one or more media items. The selected media item may be sent to the application. User feedback may be received about the media item from the application. The user feedback may be stored as user feedback data. The media selection criteria may be updated based on the user feedback data and the metadata for the media items. An effect of the media items on the user may be predicted. The media item with the greatest predicted effect among the subset of media items may be selected.

Abstract: A system includes a plurality of outlet systems receivable in respective electrical boxes in a building and connected via electrical wires to an electric power supply. The plurality of outlet systems include at least one electrical receptacle connectable to an electrical appliance, a computing unit operable to monitor the electrical appliance, a switch for interrupting electrical power to the electrical appliance in response to the computing unit. The at least one electrical receptacle, the computing unit, and the switch are configured to be receivable within and connectable to the electrical box and covered by a cover plate having at least one opening for accessing the at least one electrical receptacle. A network device is operable for communicating with the plurality of outlet systems and for communicating with a global communications network.

Abstract: A system for identifying an observed phenomenon. The system includes a computing device configured for receiving disparate data streams associated with disparate data sources. The system also includes a feature extraction module communicably connected to the computing device, a classification module communicably connected to the computing device, and a consensus module communicably connected to the computing device. The feature extraction module is configured for generating a set of attributes for each data stream. The classification module is configured for soft associating labels with attributes for each set of attributes, and for generating a confidence value for each soft association. The consensus module is configured for generating an output indicative of the phenomenon. The consensus module includes a standardization module and a sequential data module. The standardization module is configured for standardizing the confidence values.