Big data has met its match. In field after field, the ability to collect data has exploded, overwhelming human insight and analysis. But the computing advances that helped deliver the data have also conjured powerful new tools for making sense of it all. In a revolution that extends across much of science, researchers are unleashing artificial intelligence (AI), often in the form of artificial neural networks, on these mountains of data. Unlike earlier attempts at AI, such “deep learning” systems don’t need to be programmed with a human expert’s knowledge. Instead, they learn on their own, often from large training data sets, until they can see patterns and spot anomalies in data sets far larger and messier than human beings can cope with.

中文翻译：

---

科学家的学徒

大数据遇到了它的对手。在一个又一个领域，收集数据的能力呈爆炸式增长，压倒了人类的洞察力和分析。但帮助提供数据的计算进步也催生了强大的新工具来理解这一切。在一场跨越大部分科学领域的革命中，研究人员正在对这些海量数据释放人工智能 (AI)，通常以人工神经网络的形式。与早期的人工智能尝试不同，这种“深度学习”系统不需要使用人类专家的知识进行编程。相反，他们自己学习，通常是从大型训练数据集中，直到他们能够看到数据集中的模式并发现异常，这些数据集远比人类可以处理的更大、更混乱。