How CoLink Links Entities Between Different Knowledge Graphs
This article is part of the Academic Alibaba series and is taken from the paper entitled “CoLink: An Unsupervised Framework for User Identity Linkage” by Zexuan Zong, Yong Cao, Mu Guo, and Zaiqing Nie, first published in 2018 by the Association for the Advancement of Artificial Intelligence.
Bots Chat with Humans
How CoChat is Using the Human Factor to Improve Customer-Service AI
How to Create a Stream System with Tens of Millions of Feeds?
A Technical Interpretation of Alibaba's Databases: China’s biggest shopping day, known as “Singles Day”, has broken yet more records this year with a whopping 325,000 transactions and 256,000 payments per second. Such high volumes however generate vast amounts of data. At Alibaba, this data is analyzed in real-time to ensure any system failures are detected instantly and reported as quickly as possible so continual improvements can be made to customer experience.
Zhou Zhengzhong, Dou Xianming
Training Deeper Models by GPU Memory Optimization on TensorFlow@NIPS'17
When training deep learning models on GPU is popular, the problems of model complexity and memory resource limitation become ever more salient. Alibaba’s Machine Learning team came up with effective GPU memory optimization strategies that overcome memory limitations and are seamlessly integrated into TensorFlow. The paper is included in the ML Systems Workshop @ NIPS 2017. Read the paper:
11.11: Alibaba’s AI-Powered Shopping Extravaganza
With so many sales in so little time, it’s no surprise that artificial intelligence is playing a growing role in the largest online shopping event in human history.
Every November 11, Chinese consumers embark on an online shopping spree that stops only when they “chop off” their hands, as the saying goes. This year, 11.11 sales totaled US$25.3 billion across e-commerce giant Alibaba’s eight shopping platforms, mostly Taobao and Tmall. The figure is double that of Black Friday and Cyber Monday totals combined.