Specialists describe deep learning as akin to a rocketship that needs a really big engine (a model) and a lot of fuel (the data) in order to go anywhere interesting. To get a better understanding of the issues involved in building compute systems for deep learning, I spoke with one of the foremost experts on this subject: Greg Diamos, senior researcher at Baidu. Diamos has long worked to combine advances in software and hardware to make computers run faster. In recent years, he has focused on scaling deep learning to help advance the state-of-the-art in areas like speech recognition.

How Big Compute is Fueling the Deep Learning Rocketship

One person, one interview, one story. Join us as we explore the impact of AI on our world, one amazing person at a time -- from the wildlife biologist tracking endangered rhinos across the savannah here on Earth to astrophysicists analyzing 10 billion-year-old starlight in distant galaxies to the Walmart data scientist grappling with the hundreds of millions of parameters lurking in the retailer’s supply chain. Every two weeks, we’ll bring you another tale, another 25-minute interview, as we build a real-time oral history of AI that’s already garnered nearly 3.4 million listens and been acclaimed as one of the best AI and machine learning podcasts. Listen in and get inspired.

https://blogs.nvidia.com/ai-podcast/

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How Big Compute is Fueling the Deep Learning Rocketship

O'Reilly Radar