Microsoft Technology Licensing, LLC

Pure Storage, Inc.

Apollo Autonomous Driving USA LLC

Beijing Baidu Netcom Science Technology Co., Ltd

Hao Liu

Lei Zhang

Jian Zhou

Yucao Wang

Ao Guo

Miao Zou

Tianjing Xu

Shanshan Liu

Shu Jiang

Boris Feigin

Lubomir I Birov

Daniel A Molina

Vladimir Yuryevich Morozov

David Benjamin Liu

Ian Juch

Stephen James Styrchak

Szu-Hao Wu

Haijie Xiao

Helen K Pan

Danmeng Liu

Rachel M Falzone Schaw

Christian Crowser

Gordon James Coleman

Sanjay Sachdev

Haofeng Kou

Bita Gorjiara

Xiaoyi Zhu

Edward Wu

Yingfeng Oh

Yiwen Sun

Jeong Ho Lyu

Xinruo Jing

Rongsheng Liang

Dominic Law

Xiaokang Zhang

Luke Kopakowski

Linpeng Cheng

Fuyang Zhao

Jianhong Fang

Shangcheng Ying

Hailin Wu

David Liu

In one embodiment, a system configures an image signal processor (ISP) of an autonomous driving vehicle (ADV) with a first set of ISP configuration parameters, where the ISP is used to process raw image data of an image sensor of the ADV based on the first set of ISP configuration parameters. The system determines whether one or more criteria is satisfied, where the one or more criteria corresponds to an expected change in a characteristic of ambient light being perceived by the image sensor of the ADV. In response to determining that the one or more criteria is satisfied, the system configures the ISP of the ADV with a second set of ISP configuration parameters, where the ISP is used to apply an image processing algorithm to raw image data based on the second set of ISP configuration parameters to generate an image.

On-board tuning of image signal processor for cameras of autonomous vehicles

In one embodiment, a microcontroller unit (MCU) receives an expected state of an autonomous driving vehicle (ADV) from a controller of the ADV, where the controller controls motions of the ADV using a control algorithm. The MCU receives sensor data from one or more sensors of the ADV. The MCU determine an actual state of the ADV based on the sensor data. The MCU determines a performance metric of the control algorithm based on the expected state and the actual state. In response to determining the performance metric has satisfied a predetermined condition, the MCU determines a plurality of weight values for the control algorithm. The MCU sends the plurality of weight values to the control system to tune one or more weight parameters of the control algorithm using the plurality of weight values, where the controller controls the ADV using the tuned control algorithm.

On-board parameter tuning for control module for autonomous vehicles

A storage system determines a change in storage system geometry that affects at least one previously formed resiliency group of storage system resources. The storage system forms at least one resiliency group of storage system resources in accordance with rules that emphasize stability of formation of resiliency groups. The storage system accesses data stripes across storage system resources of resiliency groups.

Optimizing resiliency group formation stability

Fabric modules in a storage system offer differing device IDs from a deterministic sequence to a storage device being added to the storage system. The storage device that is being added accepts a device ID that is higher in the deterministic sequence. The fabric module that offered the device ID same as was accepted by the storage device determines to proceed with initializing the storage device.

Multiple device IDs in a multi-fabric module storage system

The present disclosure provides technical solutions related to intelligent cloud management based on profile. Artificial intelligent is applied to cloud management and cloud management suggestion may be proposed intelligently. In daily work, behaviors in using cloud resources may show characteristics of cloud users or cloud tenants themselves. The technical solution of intelligent cloud management of the present disclosure generates profile identifying cloud using characteristics by extracting behavior data in using cloud and intelligently proposes cloud management suggestions based on the profile.

Intelligent cloud management based on profile

The present disclosure provides technical solutions related to action undo service based on cloud platform. Related operations dependent on target operations to be undone may be obtained by dependency analysis and the target operations and the related operations may be undone by time sequence so as to reduce the conflict caused by the undo operations.

Action undo service based on cloud platform

Intelligent assistant for cloud management

Techniques for avoiding race conditions in a content delivery system are provided. Multiple content delivery campaigns that are affected by at least one remapping in a set of remappings are identified. Each remapping in the set of remappings maps an old identifier to a new identifier that is different than the old identifier. For at least some of the plurality of content delivery campaigns, identification data that identifies the content delivery campaign is sent to a particular service. In response to the particular service receiving the identification data, the particular service retrieves targeting data associated with the content delivery campaign. The particular service applies a subset of the set of remappings to the targeting data to generate updated targeting data. The particular service causes the updated targeting data to be stored in association with the content delivery campaign.

Race condition avoidance in a multi-database environment

A data center management system is described herein which implements techniques for receiving an event at a first data system and updating data objects stored at another data system. The first data system may receive multiple events within a given a time frame and perform the proper updates to the other data system when certain criteria are met. The data center management system may be responsible for at least two different types of data systems. For example, the first data system may be of the first type of data system and the second data system may be of the second type of data system. The first type of data system may have different technical requirements (e.g., latency, responsiveness, or other requirements), different than the second type of data system.

Managing systems hosted at data centers

Techniques for handling the dynamic reassignment of entities among multiple data centers are provided. In one technique, for each task of a plurality of tasks that are associated with a first data center of a plurality of data centers, an entity identifier that is associated with the task is identified. A call to an entity routing service is initiated, where the call includes the entity A response to the call is received from the entity routing service, where the response indicates a particular data center. An entity processor that is different than the entity routing service processes the task only if the particular data center is the first data center. If the particular data center is different than the first data center, then a data structure that stores the task is updated to indicate the particular data center and the task is eventually processed in the particular data center.

Dynamic adjustment of entity assignment in a multi-data center environment

Techniques for assigning entities to data centers are provided. In one technique, usage data associated with a particular entity that is assigned to a first data center is generated. The usage data indicates activity of multiple users relative to the particular entity. It is determined, based on the usage data, whether the particular entity is to be assigned to another data center. If so, then the particular entity is assigned to a second data center.

Dynamically adjusting an entity's assigned data center based on traffic patterns

An object model is provided that allows .NET developers to customize the Office Ribbon user interface according to a .NET Ribbon model rather than the Ribbon XML/callback model of Office applications. The .NET Ribbon model implements the IRibbonExtensibility interface and provides properties and events for Ribbon components. At runtime, the .NET Ribbon model generates and provides an Office application or document with the XML needed to render the custom Ribbon user interface. A visual designer tool uses the .NET Ribbon model to provide .NET developers with a component view architecture that allows developers to set component properties and generate events.

.Net ribbon model for a ribbon user interface

.NET ribbon model for a ribbon user interface

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Sunnyvale, CA, United States of America

Hao Liu