Nvidia Bets Big On Deep Learning

NVIDIA NVIDIA knows how to swing for the fences, and they did just that at this years GTC (GPU Technology Conference). At GTC 2015, NVIDIA CEO Jen Hsun Huang announced a multitude of new products, all of them having a very strong focus on Deep Learning. Deep Learning is a term coined by the industry which combines the broad field of machine learning with the application of deep neural networks. In fact, all three of NVIDIAs major keynotes were all about deep learning in one way or another, in addition to the four new product announcements focused on Deep Learning. This event, which has always traditionally been more technical and research heavy has always had a decent amount of graphics technology and graphics talks, but this year was incredibly heavy on the Deep Learning.

Why is NVIDIA betting on Deep Learning?

NVIDIA has a lot of different business segments, their mobile business is mostly being driven by their automotive business which both share similar if not the same SoCs. However, NVIDIA has been challenged to get their mobile SoCs into big volumes of smartphones, which is really where the volumes are in the mobile SoC business. They can win a few high-end tablets where gaming is really appreciated, including perhaps a design of their own, but that will unlikely bring profitability to their mobile SoC business. Thankfully, their automotive business appears to be taking off and they keep getting more and more significant design wins that continue to give them momentum in automotive. If nothing else, they have the thought-leader crown in automotive.

In addition to their relatively small size of the mobile SoC business, NVIDIA already has more than 75% share in the discrete GPU market and has even more share in professional discrete graphics. This has been the case for years, and NVIDIA is using Deep Learning as a way to expand the professional market in which they want to win in the future. NVIDIA stated at GTC (GPU Technology Conference) that in the past 7 years, there has been a 10x growth in GPU computing with more than 3 million CUDA downloads, 319 applications, 800 universities teaching, 60,000 academic papers and over 450,000 Tesla GPUs. All of that comes out to 54 Petaflops (54,000 Teraflops) of GPU compute power compared to just 77 Teraflops in 2008. They want to continue to grow the overall size of the professional graphics market and encourage those new buyers of GPUs to buy NVIDIA graphics cards. That leads us into NVIDIAs four major announcements.

NVIDIA CEO Jen-Hsun Huang talks about GPU Compute Growth (Credit: Anshel Sag)

What bets is NVIDIA making in Deep Learning?

NVIDIAs bet on Deep Learning is a fairly big one, but it likely wont manifest itself in the short term as much of Deep Learning still requires lots of post-graduate and graduate-level research at universities which can eventually trickle into the private sector. We are already starting to see the beginnings of that with Google and Baidu Baidu, but for it to become a large industry, there will need to be more people working on Deep Learning problems than there are now.

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Nvidia Bets Big On Deep Learning