Abstract: Embodiments include devices and methods for using a personal device to interact with a peripheral device. Methods can include receiving a pairing message, generated by the peripheral device, in response to a user interaction with the peripheral device, and detecting, at the personal device, a user gesture that is associated with use of the peripheral device. The methods can also include establishing a dedicated wireless connection with the peripheral device in response to detecting the user gesture, receiving a real-time data stream over the wireless connection, and outputting information at least partially based on data received from the peripheral device via the real-time data stream to the user.

Abstract: A computer system detects a first event. In response to detecting the first event: if first criteria are met as a result of the first event, wherein the first criteria require that the orientation of the display generation component is a first orientation, and that the computer system is charging, in order for the first criteria to be met, the computer system displays a first customizable user interface that was not displayed prior to detecting the first event; and, if the first criteria are not met as a result of the first event, the computer system forgoes displaying the first customizable user interface.

Abstract: The techniques herein are directed generally to determining or categorizing movement of a user via their user device, and specifically to detection of aircraft travel by a mobile device. In particular, according to one or more embodiments described herein, methods and/or apparatus are shown for determining that a user is in a particular mode of travel (e.g., traveling by aircraft) via a mobile device such as a smart phone by using various detected parameters including data from the sensors on that device or a sibling device such as the Inertial Measurement Unit (IMU) bearing an accelerometer, magnetometer, and/or gyroscope, and the device's atmospheric pressure barometer.

Abstract: Embodiments include devices and methods for using a personal device to interact with a peripheral device. Methods can include receiving a pairing message, generated by the peripheral device, in response to a user interaction with the peripheral device, and detecting, at the personal device, a user gesture that is associated with use of the peripheral device. The methods can also include establishing a dedicated wireless connection with the peripheral device in response to detecting the user gesture, receiving a real-time data stream over the wireless connection, and outputting information at least partially based on data received from the peripheral device via the real-time data stream to the user.

Abstract: A method of generating a marketing offer includes: receiving first data with offers for sale of a product; adding a respective incentive to a corresponding offer, wherein: a magnitude of the respective incentive is incremented toward a corresponding maximum based on a quantity of users that have redeemed the corresponding offer; and the maximum for the respective incentive is determined based on historical data of engagement rates of users for offers with a variety of incentives.

Abstract: A computer-implemented method of generating a marketing offer for a user associated with a mobile device may include: receiving first data that includes offers for sale of a product; generating and transmitting a stream of the offers to the mobile device; adding a respective incentive to a corresponding offer in the stream, wherein: a magnitude of the respective incentive is incremented toward a corresponding maximum based on a quantity of users that have redeemed the corresponding offer; and the maximum for the respective incentive is determined based on a first machine learning model configured to optimize a net present value of offers, the first machine learning model being trained using historical data of engagement rates of users for offers with a variety of incentives; receiving historical user information associated with the user; and using a second machine learning model, selecting a particular offer from the stream and transmitting a notification to the mobile device, separate from the stream, that i

Abstract: A computer-implemented method of generating a marketing offer for a user associated with a mobile device may include: receiving first data that includes offers for sale of a product; generating and transmitting a stream of the offers to the mobile device; adding a respective incentive to a corresponding offer in the stream, wherein: a magnitude of the respective incentive is incremented toward a corresponding maximum based on a quantity of users that have redeemed the corresponding offer; and the maximum for the respective incentive is determined based on a first machine learning model configured to optimize a net present value of offers, the first machine learning model being trained using historical data of engagement rates of users for offers with a variety of incentives; receiving historical user information associated with the user; and using a second machine learning model, selecting a particular offer from the stream and transmitting a notification to the mobile device, separate from the stream, that i

Abstract: A computer system for maintaining a social networking address book is provided. The computer system includes a user interface configured to present a social networking contact list to a user. The social networking contact list includes a plurality of contact entries related to a plurality of existing contacts of the user. The computer system further includes a search engine enabling the user to search the social networking contact list based on a user specified criteria. The computer system may store any desired contact information of personal connections the user may have, including not only conventional phone numbers, mailing addresses, and e-mail addresses, but also social networking user-names and account IDs. A social network created by the social networking address book may be implemented as a decentralized mesh network including a plurality of meshed nodes.