Amazon Technologies, Inc.

John Gilbert Focht

Viraj Vijay Sanghvi

Geoffrey Eric Endresen

Craig Vincent Kulfan

Ian Aird Mosher

Brian Scott Cripe

Bala Anirudh Kurakula

Daniel Arthur Sommerfield

Luan Khai Nguyen

Brian J Smith

Colin Bodell

Brian Jacob Feinstein

Christopher Charles Battey

Jason Scott Wodicka

Described herein are systems, devices and methods for decrypting content based on location. A media device may decrypt content based on determination of a location-based decryption event. The location-based decryption event may include the media device being located within a location previously defined as authorized to decrypt the content. The location-based decryption event may also include the media device being located within a predetermined distance of a designated reference object.

Location based decryption

Techniques are described for generating text in a structured language, such as source code in a programming language, based on audio input. Audible tokens may be associated with higher-level constructs, including design elements such as methods, classes, design patterns, and so forth. Additionally, audible tokens may be associated with lower-level syntactic constructs of a programming language, such as programming language keywords, tokens, and so forth. Techniques may receive and parse the audio input including the audible tokens, and generate source code output. Techniques may also provide audio information indicating a development context that may otherwise be indicated visually in a development environment.

Audio input for structured languages

Certain embodiments herein relate to modeling relationships between users, network elements, and events in an organization. Organizational information regarding users and network elements may be collected and analyzed to create a relationship graph relating users and network elements. The relationship graph may include nodes representing users and network elements and edges connecting pairs of users and/or network elements. The edges may be weighted based on a number of factors, such as operational dependencies, user preferences for receiving information associated with events, and a user's historical actions, which may determine whether a user may receive an event. A relationship graph as described herein may be leveraged to provide various uses, including generating a relationship subgraph that may allow users to identify the impact of events on other users and network elements in an organization.

Systems and methods for modeling relationships between users, network elements, and events

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Kirkland, WA, United States of America

John Gilbert Focht