Large-Scale Deep Learning for Building Intelligent Computer Systems

被引:9
作者
Dean, Jeff [1 ]
机构
[1] Google, Res Grp, Google Brain Team, Mountain View, CA 94043 USA
来源
PROCEEDINGS OF THE NINTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (WSDM'16) | 2016年
关键词
Neural networks; distributed systems; machine learning; deep learning; computer vision; speech recognition; language understanding;
D O I
10.1145/2835776.2835844
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For the past five years, the Google Brain team has focused on conducting research in difficult problems in artificial intelligence, on building large-scale computer systems for machine learning research, and, in collaboration with many teams at Google, on applying our research and systems to dozens of Google products. Our group has recently open-sourced the TensorFlow system (tensorflow.org), a system designed to easily express machine ideas, and to quickly train, evaluate and deploy machine learning systems. In this talk, I'll highlight sonic of the design decisions we made in building TensorFlow, discuss research results produced within our group, and describe ways in which these ideas have been applied to a variety of problems in Google's products, usually in close collaboration with other teams. This talk describes joint work with many people at Google.
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页码:1 / 1
页数:1
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