Amazon Technologies, Inc.

Snap Inc.

Activision Publishing, Inc.

Microsoft Technology Licensing, LLC

Other

Microsoft Corporation

Michael David Marr

Matthew David Klein

Michael Ronald Cieslak

Zahra Ferdowsi

Jun Huang

Jiayao Yu

Samuel James McKelvie

Keith Stuart Kaplan

Farnaz Azmoodeh

Kai Chen

Jagwinder Singh Brar

Pradeep Vincent

James Robert Hamilton

Tyson James Lamoreaux

Nachiketh Rao Potlapally

Nathan T Lewis

Matthew T Corddry

Darin Lee Frink

David Edward Bryan

Peter George Ross

Mark Y Kelly

Ian Paul Nowland

Justin Oliver Pietsch

Anirudh Balachandra Aithal

Peter Nicholas Desantis

Mark Noel Kelly

Jacob Adam Gabrielson

Richendra Khanna

Edward L Wallace

Justin Mason

Daniel Todd Cohn

Chao Pang

John L Manferdelli

Aleksandr Zhang

Finn Parnell

Mariusz Hieronim Jakubowski

Alan Michael Judge

Vinay Krishnaswamy

Scott A Brender

Jeremy Volkman

Rachit Chawla

Eric Jason Brandwine

Donald Lee Bailey, Jr

Christopher Nathan Watson

Max Jesse Wishman

Adam Douglas Morley

Philip J Lafornara

Yi Xu

Caleb Ogden

Xiaolin Shi

Olamide Valerie Olatunji

David Boyle

Claire Reinert

Aysegul Cansizoglu

Hussein Mehanna

Kenneth D Ray

Anurag Windlass Gupta

Paul England

Matthew Loukas Hanover

Yan Valerie Leshinsky

Dhritiman Sagar

James Powderly

Aaron Joseph Coon

Sergei Korolev

Daniel Colascione

Robert Ian Oliver

Michael Darweesh

Scott Myers

Alan M Judge

John Linden

Marcin Piotr Kowalski

Bryan M Willman

Octavian Tony Ureche

Fedir Poliakov

Brandon S Baker

Charles F Rose

Rushmi U Malaviarachchi

Pavel Zeman

James Frederick Blinn

Adrian Secchia

Peter N De Santis

Donald P Mitchell

Varugis Kurien

Tony Ureche

Istvan Marton

Bradley S Serbus

Andrew C Godfrey

James R Watkins, Iii

Ryan H Medeiros

Paul G Pasteris

Timothy J Oerting

Matthew R Corddry

Cristian Zaloj

Philip LaFornara

Tyson J Lemoreaux

Marcin P Kowalski

Bryan Mark Willman

Providing branch prediction of APIs to determine the best API for an application to use when performing a function. An API history buffer stores a history of performance data in association with APIs when the function is performed by an application. An API map dynamically stores application performance data in association with APIs. This history data and the API map is used by a circumstance engine and a circumstance engine service to provide a suggested API to an application when it is ready to perform a function.

Branch prediction for APIs

A system and method is provided for continuous gameplay in a multiplayer video game through an unbounded gameplay session. Players may join, exit, and later rejoin a given unbounded gameplay session at any time. A given unbounded gameplay session may therefore continue indefinitely so long as at least one player wishes to continue to gameplay. To facilitate an unbounded gameplay session, the system may score players using time-based or other parameters in a manner that is fair to players who have been playing in the unbounded gameplay session longer than other players.

Systems and methods for converting a bounded gameplay session to an unbounded gameplay session

Clustering a plurality of client devices running an application as a function of a data structure such that the plurality of client devices are each assigned a cluster. Client devices having similar performance metrics are assigned the same cluster. An operation of the application is modified as a function of the performance metrics of the client device. The modification of application operation is performed by turning certain features of the application on and off using a rule based on device cluster.

Device clustering

Systems, devices, media, and methods are presented for testing the capability of a mobile device to run a particular feature of an application. Each feature may include a package of code, a call, a state, and a condition; each condition correlated with a specific state. The call is a query that includes instructions to evaluate whether the application will run successfully if a particular feature is running. If the call fails, the feature condition remains Off, resulting in a rollback of the feature. If the call succeeds, the feature condition is changed to On. The system may include an experimentation framework on each mobile device for registering features, executing calls, logging results, and maintaining states and conditions.

Feature rollback for incapable mobile devices

Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Staged release of updates with anomaly monitoring

A gesture-based wake process for an AR system is described herein. The AR system places a hand-tracking input pipeline of the AR system in a suspended mode. A camera component of the hand-tracking input pipeline detects a possible visual wake command being made by a user of the AR system. On the basis of detecting the possible visual wake command, the AR system wakes the hand-tracking input pipeline and places the camera component in a fully operational mode. If the AR system, using the hand-tracking input pipeline, verifies the possible visual wake command as an actual wake command, the AR system initiates execution of an AR application.

Visual and audio wake commands

A system and method is provided that generates a game log that specifies game events during gameplay to enable efficient distribution of video game playback, facilitates the annotation of gameplay through content from users and others, and generates a video game stream that includes the game log and content. The system facilitates the efficient sharing of video game playback, as well as annotations from users and others. For example, e-sportscasters may use the system to broadcast video game playback with their commentary and/or graphical overlays. Video game players may use the system to share video game playback efficiently with other users. The system may also facilitate the sharing of loadout conditions and micro-transactions relevant to video game playback.

Methods and systems for enabling users to experience previously hidden information during a playable recreation of a video game session

Aspects of the present disclosure involve systems and methods for performing operations comprising providing a messaging application comprising a feature to a client device, the feature being implemented by operations having alternative complexity levels, wherein a first complexity level represents a first amount of device resources consumed by a first set of operations, and wherein a second complexity level represents a second amount of device resources consumed by a second set of operations; determining that the first configuration rule is satisfied by a first property of the client device; and in response to determining that the first configuration rule is satisfied by the first property of the client device, causing the feature to be implemented on the client device by the first set of operations having the first complexity level that consume a greater amount of device resources than the second set of operations having the second complexity level.

Automated scaling of application features based on rules

Generally described, systems and methods are provided for monitoring and detecting causes of failures of network paths. The system collects performance information from a plurality of nodes and links in a network, aggregates the collected performance information across paths in the network, processes the aggregated performance information for detecting failures on the paths, analyzes each of the detected failures to determine at least one root cause, and initiates a remedial workflow for the at least one root cause determined. In some aspects, processing the aggregated information may include performing a statistical regression analysis or otherwise solving a set of equations for the performance indications on each of a plurality of paths. In another aspect, the system may also include an interface which makes available for display one or more of the network topology, the collected and aggregated performance information, and indications of the detected failures in the topology.

Monitoring and detecting causes of failures of network paths

Systems, devices, media, and methods are presented for assigning configuration parameters to unknown devices by comparing characteristics of unknown devices to characteristics of known devices. Characteristics of an unknown device are compared to characteristics of known devices to identify a similar device having known configuration parameters. The unknown devise is then assigned the configuration parameters of the identified similar device.

Device configuration parameter determination

A system and method is provided that simulates gameplay of non-player characters (NPCs) distributed across networked end user devices. The system may identify end user devices that are connected to the system through a network and are available to participate in a simulation in which each participating end user device is provided with one or more NPCs to be executed. An end user device may be available to participate when it has sufficient computing capacity, such as when in an idle or standby state. As such, the system may leverage spare computing capacity of networked end user devices to execute NPCs at networked end user devices during a simulation. In this manner, the behavior of an NPC may be tested using real-world conditions that may affect gameplay, such as a network connection quality, user-to-user game engine coordination and data exchanges, and/or other real-world conditions associated with networked end user devices.

Methods and systems for continuing to execute a simulation after processing resources go offline

A system and method for providing dynamically variable maps in a video game is disclosed. A map is provided that defines a playable space available to one or more game players in a video game. Gameplay is monitored in real-time for the detection of a trigger event. Upon detection of a trigger event, a map management engine dynamically modifies a configuration of the map to improve the gameplay experience based on the type of trigger event. Dynamic modification of a map may comprise altering one or more of the map boundary, and/or the location, position, size, number, state, etc. of one or more static map objects or dynamic map objects. As a result of the dynamic modification of the map, the map may transform from its initial (or first or beginning) configuration to a modified (or new or second) configuration.

System and method for providing dynamically variable maps in a video game

Systems, devices, media, and methods are presented for determining performance metrics of client devices on a network using benchmark applications. Benchmark applications are distributed to client devices to produce performance metrics for the client devices. Performance metrics of the client devices received from the client devices are grouped to obtain performance metrics for different types of client devices.

Network device performance metrics determination

Systems, devices, media, and methods are presented for throttling (i.e., adjusting) the workload of an application (e.g., number of task requests) in order to improve processor core usage within a heterogeneous multiprocessor system. When high-performance processing is beneficial to the application, the number of task requests may be increased in order to have high-performance processor cores within the heterogeneous multiprocessor system core processor perform the tasks. On the other hand, when high-performance processing is not beneficial, the number of task requests may be decreased in order to have low-performance processor cores within the heterogeneous multiprocessor system perform the tasks. Processor core usage is monitored, and the number of tasks being performed are adjusted to match the processor core usage to a target processor core usage for functions the application is performing.

Core targeting in heterogeneous multiprocessor systems

Growing community of inventors

Monroe, WA, United States of America

Michael David Marr