In 2008, the National Academy of Engineering presented 14 Grand Challenges that, if solved, had the potential to radically improve the world. Thanks to recent breakthroughs in artificial intelligence – specifically, the advent of deep neural networks — we’re on pace to solve some of them, Google Senior Fellow Jeff Dean said last week at the Strata Data Conference.
The Academy certainly didn’t lack for ambition 10 years ago when it drew up the 14 Grand Challenges. Delivering a solution for any one of them – such as providing energy from nuclear fusion or finding out how to sequester carbon – could have a dramatic impact on billions of people’s lives.
As a result of advances in deep learning techniques, the presence of enormous data collections, and the availability of massive server clusters, we will be able to compute our way toward solving them, Dean told a packed room of attendees during his presentation Thursday afternoon at the San Jose McEnery Convention Center.
“I actually think machine learning is going to help with all of these,” the legendary computer scientist said. “I think there are actually going to be significant breakthroughs in some of these Grand Challenges that are at least in part fueled by the fact that we now have machine learning at scale with many of these techniques that can really push us forward in the areas of commuter vision, language understanding, speech recognition, and automating and solving engineering problems.”
Dean explained how he did an undergraduate thesis way back in 1990 on parallel training of neural networks. He was convinced that, if we could just get more compute capacity on neural networks, then we could use them to do “more interesting things.” Dean played around with the technology running on a cluster with 64 processors, which was actually pretty big for the day.
“I thought if we could get a 60x speedup, it would be great, we could tackle really big problems,” said Dean, one of Datanami‘s 2017 People to Watch. “It turned out what we actually really needed was a 1,000,000x speedup, not 60x. But we have that now. It’s affordable. That I think is why we’re here today, why we’re now seeing the power of neural networks paired with large, substantial amounts of computing really to solve problems that we didn’t know how to solve the other way.”
Here’s how deep learning has put us on the cusp of solving some of the Grand Challenges, according to Dean…
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