Machine-learning technology powers many aspects of modern 
society: from web searches to content filtering on social net works to recommendations on e-commerce websites, and 
it is increasingly present in consumer products such as cameras and 
smartphones.Perhaps more 
surprisingly, deep learning has produced extremely promising results 
for various tasks in natural language understanding14, particularly 
topic classification, sentiment analysis, question answering15 and lan guage translation16,17.For decades, con structing a pattern-recognition or machine-learning system required 
careful engineering and considerable domain expertise to design a fea ture extractor that transformed the raw data (such as the pixel values 
of an image) into a suitable internal representation or feature vector 
from which the learning subsystem, often a classifier, could detect or 
classify patterns in the input.