Tractable Big Data and Big Models in Machine Learning

在几乎所有的科学和工程领域，我们收集的数据量都在以前所未有的速度增长。我们不再生产从MB到GB的数据大小，而是从TB到PB(甚至更高)。机器学习是我们用来理解这些不断增长的数据量(大数据)的关键工具之一，现在它正被用来解决非常复杂的任务，方法是将越来越复杂的模型适应这些巨大的数据集(“大模型”)。机器学习被用于日常技术，如电子邮件垃圾邮件过滤、产品推荐系统、广告排名系统、新的运动传感设备，以及最近在语音识别方面的改进。机器学习仍然有巨大的潜力，可以影响从物理到生物，从教育技术到人机交互的各种应用。

In nearly all fields of science and engineering, the amount of data we collect is growing at unprecedented rates. We no longer produce data sizes from megabytes to gigabytes, but rather from terabytes to petabytes (and beyond). Machine learning is one of the key tools we use to make sense of these ever-growing quantities of data ('big data'), and it is now being used to solve very complicated tasks by fitting increasingly-complicated models to these huge data sets ('big models'). Machine learning is used in everyday technologies like e-mail spam filtering, product recommendation systems, advertisement ranking systems, new motion sensing devices, and recent improvements in speech recognition. There remains a huge potential for machine learning to impact applications ranging from physics to biology and from education technology to human-computer interaction.