NVIDIA’s (NVDA, Financial) quarterly revenues have been surging at double-digit rates in the last three quarters and, looking at the guidance for the next quarter, it’s clear that the company is expecting the growth rate to continue unabated in the near future. One of the key factors that has added fuel to their engines is NVIDIA’s new growth drivers: the data center segment and auto segment.
In the most recent quarter, NVIDIA’s data center unit reported $151 million in sales, a growth of 109.72% compared to the prior period. The growth in data center revenues is much higher than other segments, and there are several reasons why this growth can, in fact, continue its breakneck pace for several more quarters.
Here’s why NVIDIA can keep growing
NVIDIA’s expertise in the GPU segment has given it a range of must-have products for hyperscale data centers. The reason they are called hyperscale data centers is because the workloads they operate on are highly demanding, much more so than what regular data centers typically process on a day to day basis.
“Hyperscale computing is a distributed computing environment in which the volume of data and the demand for certain types of workloads can increase exponentially yet still be accommodated quickly in a cost-effective manner.”
So, these systems process large workloads and they should be ready to scale them in massively when required. As the output is very different from what we normally see, the hardware that powers them has to be different also. This is the sweet spot where NVIDIA has struck gold with its GPUs.
"GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering applications. Pioneered in 2007 by NVIDIA, GPU accelerators now power energy-efficient data centers in government labs, universities, enterprises, and small-and-medium businesses around the world. They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.”
NVIDIA has been working on these products since 2007, a long time before the cloud companies and cloud data centers became mainstream. Today the entire world is gradually moving towards cloud infrastructure, and the tech majors are slowly stepping up their offerings by exploiting machine learning and deep learning, which are sort of specialized branches of artificial intelligence.
Aside from cloud providers such as Amazon (AMZN, Financial), Microsoft (MSFT, Financial) and IBM (IBM, Financial), who offer machine learning as a part of their cloud offerings, there is plenty of action going on in the AI world. All virtual assistants like Siri, Alexa, Cortana and the bots that are so eager to help us through voice chat have AI working in the background. In fact, two years ago Google (GOOG, Financial) bought a UK-based startup called DeepMind - for a reported $600 million - that has been working on AI technology for nearly four years before that. You can tell from the investment size alone how valuable this segment has become for most of the major tech companies.
As the proliferation of AI increases and it finds more meaningful applications, the requirement for GPUs over CPUs is on the uptick. And companies building data centers obviously want their solutions to be as cutting edge as possible, and at this moment only NVIDIA’s products have earned that reputation from the market.
Intel (INTC, Financial) has recently announced their intention to step their game in the AI data center market, and they will be doing their best because this industry has plenty of potential to grow thanks to the high level of competition amongst the top tech companies. But until the competition catches up it will be NVIDIA’s market to rule, and just the sheer number of companies that are already using NVIDIA’s components in their AI projects is a huge validation to their products.
“Hyperscale companies are the fastest adopters of deep learning, accelerating their growth in our Tesla business. Starting from infancy three years ago, hyperscale revenue is now similar to that from high performance computing. NVIDIA GPUs today accelerate every major deep learning framework in the world. We power IBM Watson and Facebook's Big Sur server for AI, and we're in AI platforms at hyperscale giants such as Microsoft, Amazon, Alibaba and Baidu for both training and real-time inference. Twitter has recently said they use NVIDIA GPUs to help users discover the right content among the millions of images and videos shared every day.” - NVIDIA Earnings Call
So the demand is obviously there, and NVIDIA seems to be the only supply solution of such scale and capability at the moment. You can bet they’re going to exploit that advantage as much as they can before the competition catches up, but the odds of any other company coming close to them will be quite low considering the level of expertise and number of key clients they have attained thus far.
As such, this is definitely one stock you will want to own and keep for the next several decades at least. But watch out for their valuation, though. Companies with this kind of growth prospect are obviously irresistible to most investors, so you might want to wait for the dips and build into a strong position over time.
Disclosure: I have no positions in any of the stocks mentioned above and no intention to initiate a position in the next 72 hours.
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