Amazon Technologies, Inc.

Kiraly, Kenneth Paul

Awad, Nadim

Keljo, Jonathan White

Dolbakian, Levon

Froment, Arnaud Marie

Dumont, Michael David

Sridharan, Srinivasan

Levon Dolbakian

Arnaud Marie Froment

Kenneth Paul Kiraly

Nadim Awad

Srinivasan Sridharan

Jonathan White Keljo

Michael David Dumont

Gy Stuart Fullmer

Brett Nathan Lynnes

Sean Thomas Congden

Andrea Robin Kilpatrick

A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.

Providing relevant information based on usage data

A system and method for identifying a user of a device includes comparing audio received by a device with acoustic fingerprint information to identify a user of the device. Image data, video data and other data may also be used in the identification of the user. Once the user is identified, operation of the device may be customized based on the user. Further, once the user is identified, data can be associated with the user, for example, usage data, location data, gender data, age data, dominant hand data of the user, and other data. This data can then be used to further customize the operation of the device to the specific user.

Systems and methods for identifying users of devices and customizing devices to users

Techniques for determining positions of devices within an environment are described herein. In some instances, an environment, such as a home or office of a user, may include an array of devices, some or all of which may couple to a network or to other devices via short-range wireless connections (e.g., Bluetooth&#xae;, Zigbee&#xae;, etc.). These devices may capture an array of data for providing to a central service, which is configured to analyze the data and, based on this analysis, determine a location of the devices relative to one another. That is, the central service may analyze the data to determine relative distances and orientations between the identified devices within the environment.

Determining relative positions of user devices

Users can switch between applications using contextual interface elements. These elements can include icons for applications determined to likely be accessed by the user for a current context. Information is gathered to determine the current context, then information such as patterns of historical usage are utilized to determine and rank the applications by likelihood of use. Different contexts can include different icons, and a given context can include different icons for different points in time or locations. A user can access a contextual interface element by performing a swipe motion, for example. The user can continue the motion to an area associated with an icon of interest, and perform an action such as a tap or release to cause the associated application to be launched. Such an approach enables a user to quickly and easily launch another application independent of the application currently active on the device.

Contextual launch interfaces

A social networking system creates and manages dynamic social circles corresponding to real world social events where multiple people join in an event. The social networking system has stored conditions that, when met, for creating, closing, and deleting a social circle, and also determines which users are part of the social circle and for what time periods. Assets, such as photos, URLs, media selections, etc. that are used by members of the social circle during the event are recorded by the social networking system and access to those assets are selectively provided to members of the social circle. A social circle might be automatically opened when users congregate. A social circle closes when the event is over. Once closed, the assets might not change but continue to be available to members until the social circle is deleted. The social networking system might be a central system or a distributed system.

Dynamic social network allocation and data allocation based on real world social interaction patterns

Described herein are systems, devices and methods for presenting content based on the spatial relationship between a media device and a user of the media device. The media device may present content based on an angle between an eye axis of the user and a device axis of the media device.

Content orientation based on a user orientation

Users may access a variety of content in many locations. Described herein are systems, devices and methods for introducing users that are in close proximity to one another. Historical location data of the media devices, data indicating content usage on the media devices, or a combination of the two is used to determine a correspondence between two or more users. Once the correspondence has been determined, an introduction may be provided.

Introduction based on location and content usage data

Techniques are described for determining height, weight, or other characteristics of a user based on processed sensor data. The sensor data may include data collected by sensors on the user's computing device or other computing devices, or data collected by stationary, external sensors. Different types of sensor data may be processed to estimate at least one physical characteristic of the user, such as the user's height, weight, apparel size, age, and so forth. The estimated characteristics may be employed to perform actions based on the user's identity or category, to customize content delivery for the user, or for other purposes.

Employing device sensor data to determine user characteristics

Systems, methods, and computer-readable media are disclosed for generating a baseline use profile that indicates typical patterns of use of a device over time, transitioning the device to a challenge mode when sensor data indicates a deviation from the baseline use profile by more than a permissible tolerance, presenting challenges to the user while in the challenge mode, and determining whether to restrict or allow access to device functionality based on user responses to the challenges.

Automatic determination of device mode based on use characteristics

Approaches to enable a computing device, such as a phone or tablet computer, to compute a probability that the user currently using the device matches a profile of an authorized user and to set or change a security level of the computing device based on the computed probability. The security level can be one of many security levels each having a different scope of authorized access to data or functions of the computing device. The computing device may periodically re-compute the probability and change the security level whenever the probability crosses certain predefined thresholds.

Growing community of inventors

Los Gatos, CA, United States of America

Levon Dolbakian