Amazon Technologies, Inc.

Kiraly, Kenneth Paul

Awad, Nadim

Keljo, Jonathan White

Dolbakian, Levon

Froment, Arnaud Marie

Dumont, Michael David

Sridharan, Srinivasan

Arnaud Marie Froment

Kenneth Paul Kiraly

Levon Dolbakian

Nadim Awad

Srinivasan Sridharan

Jonathan White Keljo

Michael David Dumont

Gy Stuart Fullmer

Brett Nathan Lynnes

Sean Thomas Congden

Jesper Mikael Johansson

Darren Ernest Canavor

Jon Arron McClintock

Andrew Jay Roths

Chelsea Celest Krueger

Phivos Costas Aristides

Scott Donald Gregory

Vijay Rangarajan

Cory Adam Johnson

Kirill V Orlov

Ezekiel Sanborn De Asis

Andrea Robin Kilpatrick

Leo Benedict Baldwin

Manish Lachwani

John T Kim

Maxim Spivak

Jonathan Ian McCormack

Ezekiel Wade Sanborn De Asis

Wendy Chiu Fai Wong

Mark Steven Tamura

Albert William Wegener

Jacob Howard Fenton

Juergen Ahaus

Seetha Lakshmi Annamraju

Levon Dolbakain

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

An access control application for mobile devices is provided. The access control application may be configured to generate a set of security tasks based at least in part on information corresponding to a user's interactions with the mobile device. An unlock screen of the mobile device may be triggered and security tasks from the generated set of security tasks may be displayed through a user interface of the mobile device. The user's response to the security tasks may be obtained and a confidence score may be calculated, based at least in part on the response. The access control application may then determine, based at least in part on the score and one or more attributes of the environment, whether to unlock the mobile device or prompt the user to provide an additional response to another security task.

Dynamic unlock mechanisms for mobile devices

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

Described are techniques and systems for providing authentication credentials associated with a user. The user is authenticated using one or more techniques, such as multi-factor authentication using one or more biometric characteristics, biomedical data, passwords, and so forth, to generate authentication data. The authentication data may be used in conjunction with information about a wearable device ('wearable'), such as a wristband. Authentication may be confirmed upon an indication that the wearable has not been removed, tampered with, and so forth. In some implementations the wearable device may store and distribute the authentication credentials to requesting devices so long as the wearable has not been removed, tampered with, and so forth.

Authentication with wearable device

An access control application for mobile devices is provided. The access control application may be configured to generate a set of security tasks based at least in part on information corresponding to a user's interactions with the mobile device. An unlock screen of the mobile device may be triggered and a security tasks from the generated set of security tasks may be displayed through a user interface of the mobile device. The user's response to the security tasks may be obtained and a confidence score may be calculated, based at least in part on the response. The access control application may then determine, based at least in part on the score and one or more attributes of the environment, whether to unlock the mobile device or prompt the user to provide an additional response to another security task.

Systems, methods, and computer-readable media are disclosed for receiving sensor data indicative of one or more vibrational and/or environmental characteristics associated with a user device, a user of the user device, and/or an environment that includes the user device; determining a value for a metric representative of the one or more characteristics; determining a value of a gesture detection parameter based at least in part on the value of the metric; receiving input corresponding to a touch event detected at a touch-sensitive display of the device; and analyzing the input based at least in part on the value of the gesture detection parameter to determine whether the touch event corresponds to a particular type of gesture.

Adaptive gesture recognition

Growing community of inventors

San Jose, CA, United States of America

Arnaud Marie Froment