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公司:Uber

关联话题: 优步

优步(英语:Uber,/ˈuːbər/)是一间交通网络公司,总部位于美国加利福尼亚州旧金山,以开发移动应用程序连结乘客和司机,提供载客车辆租赁及媒合共乘的分享型经济服务。乘客可以透过应用程序来预约这些载客的车辆,并且追踪车辆的位置。营运据点分布在全球785个大都市。人们可以透过网站或是手机应用程序进入平台。

优步的名称大多认为是源自于德文über,和over是同源,意思是“在…上面”。 (页面存档备份,存于互联网档案馆)

然而其营业模式在部分地区面临法律问题,其非典型的经营模式在部分地区可能会有非法营运车辆的问题,有部分国家或地区已立法将之合法化,例如美国加州及中国北京及上海。原因在于优步是将出租车行业转型成社群平台,叫车的客户透过手机APP(应用程序),就能与欲兼职司机的优步用户和与有闲置车辆的租户间三者联系,一旦交易成功即按比例抽佣金、分成给予反馈等去监管化的金融手法。

2019年5月10日,优步公司透过公开分发股票成为上市公司,但首日即跌破分发价。

据估算,优步在全球有1.1亿活跃用户,在美国有69%的市占率。优步亦在大中华区开展业务,目前优步已在香港和台湾建成主流召车服务平台,并于中国大陆通过换股方式持有该市场最大网约车出行平台滴滴出行母公司小桔科技17.7%经济权益。

From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey

In the past few years, the Machine learning (ML) adoption and impact at Uber have accelerated across all business lines. Today, ML plays a key role in Uber’s business, being used to make business…

DragonCrawl: Generative AI for High-Quality Mobile Testing

Quality and testing go hand in hand, and in 2023 we took on a new and exciting challenge to change how we test our mobile applications. Specifically, we are training ML models to test our applications…

Ensuring Precision and Integrity: A Deep Dive into Uber’s Accounting Data Testing Strategies

The financial accounting services platform at Uber operates at an internet scale– approximately 1.5 billion journal entries (JEs) per day and 120 million transactions per day via ETL and data…

Improving Uber Eats Home Feed Recommendations via Debiased Relevance Predictions

Uber Eats’ mission is to make eating effortless, at any time, for anyone. The Uber Eats home feed is an important tool for fulfilling this goal, as it aims to provide a magical food browsing…

Supercharge the Way You Render Large Lists in React

Rendering large lists in React can be a challenging task for developers. As the size of the list grows, the DOM (Document Object Model) tree also grows, leading to performance issues like slow…

Uber: GC Tuning for Improved Presto Reliability

Uber uses open-source Presto to query nearly every data source, both in motion and at rest. Presto’s versatility empowers us to make intelligent, data-driven business decisions. We operate around 20…

Palette Meta Store Journey

The Uber Michelangelo feature store, called Palette, is a database of Uber-specific curated and internally crowd-sourced features that are easy to use in machine learning projects. It comes to solve…

Stopping Uber Fraudsters Through Risk Challenges

As a marketplace-based, consumer-facing app, Uber encounters a multitude of sources of fraud across its platform. In one of the most common cases of fraud, bad actors use various methods to attempt to…

DataCentral: Uber’s Big Data Observability and Chargeback Platform

Discover real-time query analytics and governance with DataCentral: Uber’s big data observability powerhouse, tackling millions of queries in petabyte-scale environments.

Jupiter: Config Driven Adtech Batch Ingestion Platform

Uber’s mission is to reimagine the way the world moves for the better and provide earning opportunities globally through its marketplace. One effective approach to bring the Uber brand and marketplace…

How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache

Docstore is Uber's in-house, distributed database built on top of MySQL®. Storing tens of PBs of data and serving tens of millions of requests/second, it is one of the largest database engines at Uber…

Building Scalable, Real-Time Chat to Improve Customer Experience

Uber is a global business, and has a customer base that’s spread throughout the world. Uber’s customer base is divided into many user personas, predominantly riders, drivers, eaters, couriers, and…

Network IDS Ruleset Management with Aristotle v2

If you were to ask a veteran SOC (Security Operations Center) analyst about Network IDS (Intrusion Detection Systems) or IPS (Intrusion Prevention Systems), the response would probably contain phrases…

Load Balancing: Handling Heterogeneous Hardware

This blog post describes Uber's journey towards utilizing hardware efficiently via better load balancing. The work described here lasted over a year, involved engineers across multiple teams, and…

Balancing HDFS DataNodes in the Uber DataLake

Uber has one of the largest Apache HadoopⓇ Distributed File System (HDFS) deployments in the world, with exabytes of data across tens of clusters. HDFS team at Uber had to solve the problem of…

Model Excellence Scores: A Framework for Enhancing the Quality of Machine Learning Systems at Scale

With the introduction of Model Excellence Scores at Uber, we're setting a new standard for measuring, monitoring, and maintaining ML model quality–read how this innovative approach aims to enhance ML…

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