Bengio (Photo by Maryse Boyce), Hinton (Photo by Keith Penner), LeCun (Photo, courtesy of Facebook)
By Jonathan Vanian
April 2, 2019

Artificial intelligence’s growing importance, in both business and research, is largely because of Yoshua Bengio, Geoffrey Hinton, and Yann LeCun—otherwise known as the “godfathers of deep learning.”

Last week, the trio won the annual Turing Award, the technology world’s equivalent to the Nobel Prize, presented by the Association for Computing Machinery. Their research has led to huge breakthroughs in computers translating languages and identifying objects and people in photographs.

At the heart of the men’s research are neural networks, the software created decades ago to mimic how the human brain learns. The technology plays a huge role in artificial intelligence and its close cousin, deep learning.

The analogy of neural networks being like the human brain is something many A.I. researchers and neuroscientists loathe because it oversimplifies an extremely complicated process. “That’s okay,” Bengio, a University of Montreal computer science professor and co-founder of enterprise startup Element AI, said in an interview with Fortune a day before his Turing Award was publicly announced.

For years, the A.I. community ignored neural networks in favor of other techniques that are more closely related to conventional computer programming. But more advanced computer chips and access to Internet data supercharged the power of neural networks, which could now be fed enormous amounts of information so they could identify patterns and, thereby, learn.

“Because as we train these systems with more data, they just get better,” Bengio said.

He recalled how difficult it was to get funding when he initially studied neural networks. Ultimately, the Canadian government kicked in some money. Today, in contrast, artificial intelligence attracts big money from governments and venture capitalists, with most of the investment in the U.S. coming from businesses. Bengio only hopes that other technologies, especially those currently lacking buzz, also have easy access to cash.

“We need to be careful to nurture that spirit and not try to say, ‘That’s the end of it,'” he said.

LeCun, now Facebook’s chief A.I. scientist, also talked with Fortune about his early research into neural networks. During those experiments, he said he focused more on creating computers that “think” rather than how the technology would be applied in real life. But now LeCun believes big breakthroughs are imminent, mostly from businesses that specialize in areas including medical imaging, self-driving cars, and even garden maintenance (i.e. lawnmowers that know to trim only weeds instead of roses). What’s certain is that companies will use the technology in ways he never envisioned.

Says LeCun, “It’s not like we have a monopoly on good ideas.”

Jonathan Vanian

Sign up for Eye on A.I.


You May Like