Artificial intelligence has gone through some dismal periods, which those in the field gloomily refer to as AI winters. This is not one of those times; in fact, AI is so hot right now that tech giants like Google, Facebook, Apple, Baidu, and Microsoft are battling for the leading minds in the field. The current excitement about AI stems, in great part, from groundbreaking advances involving what are known as convolutional neural networks. This machine learning technique promises dramatic improvements in things like computer vision, speech recognition, and natural language processing. You probably have heard of it by its more layperson-friendly name: Deep Learning.

Few people have been more closely associated with Deep Learning than Yann LeCun, 54. Working as a Bell Labs researcher during the late 1980s, LeCun developed the convolutional network technique and showed how it could be used to significantly improve handwriting recognition; many of the checks written in the United States are now processed with his approach. Between the mid-1990s and the late 2000s, when neural networks had fallen out of favor, LeCun was one of a handful of scientists who persevered with them. He became a professor at New York University in 2003, and has since spearheaded many other Deep Learning advances.

More recently, Deep Learning and its related fields grew to become one of the most active areas in computer research. Which is one reason that at the end of 2013, LeCun was appointed head of the newly-created Artificial Intelligence Research Lab at Facebook, though he continues with his NYU duties.

LeCun was born in France, and retains from his native country a sense of the importance of the role of the public intellectual. He writes and speaks frequently in his technical areas, of course, but is also not afraid to opine outside his field, including about current events.

IEEE Spectrum contributor Lee Gomes spoke with LeCun at his Facebook office in New York City. The following has been edited and condensed for clarity.

Yann LeCun on...

IEEE Spectrum: We read about Deep Learning in the news a lot these days. Whats your least favorite definition of the term that you see in these stories?

Yann LeCun: My least favorite description is, It works just like the brain. I dont like people saying this because, while Deep Learning gets an inspiration from biology, its very, very far from what the brain actually does. And describing it like the brain gives a bit of the aura of magic to it, which is dangerous. It leads to hype; people claim things that are not true. AI has gone through a number of AI winters because people claimed things they couldnt deliver.

Spectrum: So if you were a reporter covering a Deep Learning announcement, and had just eight words to describe it, which is usually all a newspaper reporter might get, what would you say?

LeCun: I need to think about this. [Long pause.] I think it would be machines that learn to represent the world. Thats eight words. Perhaps another way to put it would be end-to-end machine learning. Wait, its only five words and I need to kind of unpack this. [Pause.] Its the idea that every component, every stage in a learning machine can be trained.

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Facebook AI Director Yann LeCun on His Quest to Unleash Deep Learning and Make Machines Smarter