10 years, 4 months ago

A Googler's Quest to Teach Machines How to Understand Emotions

Quoc Le sees the world as a series of numbers. He works on the Google Brain, the search giant's foray into "deep learning," a form of artificial intelligence that processes data in ways that mimic the human brain—at least in some ways. Le was one of the main coders behind the widely publicized first-incaration of the Google Brain, a system that taught itself to recognize cats on YouTube images, and since then, the 32-year-old Vietnam-native has been instrumental in helping to build Google systems that recognize your spoken words on Android phones and automatically tag your photos on the web, both of which are powered by deep-learning technology. Called Word2Vec, the system determines how different words on the web are related, and Google is now using this as a means of strengthening its "knowledge graph"—that massive set of connections among related concepts that makes the Google search engine work so well. "We learn from a lot of unlabeled data," says Le, who studied artificial intelligence at Stanford with Andrew Ng, now the head of research at Baidu and one of the founders of the Google Brain project.

Wired
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