4 Reasons to Invest in Nvidia's AI in 2022 – Motley Fool

Returns as of 01/13/2022
Returns as of 01/13/2022
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Nvidia (NASDAQ:NVDA) has a long history of creating innovative and in-demand technology, and it’s doing it again with artificial intelligence. In this Backstage Pass clip from “The AI/ML Show” recorded on Jan. 5, Motley Fool contributor Danny Vena explains why Nvidia is a top pick for investors interested in this space. 

Danny Vena: When you talk about a company that’s been around for a while, Nvidia actually is one of the pioneers in graphics processing. If you go back, there were other graphics processors in their simplest form, they’ve been available as early as 1976. But Nvidia revolutionized the field, introduced the modern graphics processor or GPU in 1999. The thing that really revolutionized this area of graphics processing, or the secret sauce, was the fact that modern GPUs enabled something called parallel processing, which is the ability to conduct a multitude of complex mathematical calculations simultaneously. That, in turn, produced more life-like graphics in video games.
This is a company that has been around for a while and it’s interesting if you go back a few years, folks were dismissing Nvidia out of hand essentially saying, once the gaming market gets saturated, it’s game over for Nvidia. That turned out not to be the case. Jensen Huang, who is the CEO of Nvidia, is a genius by all accounts and had some other ideas. First, let’s talk a little bit about Nvidia and it’s gaming segment. Nvidia holds a commanding 83 percent share of the discrete desktop GPU market according to Jon Peddie Research. AMD lost share to Nvidia in the most recent quarter, slipping to 17 percent from 19 percent. Not everybody agrees on the exact market share. Steam’s numbers are a little different. They put Nvidia, AMD at 75 percent and 15 percent of the market, with Intel commanding the remaining 10 percent share. But regardless of which numbers you use, anybody that is a serious gamer has an Nvidia GPU as their primary gaming chip. I’m sure that’s something that Jose could probably back me up on, right?
Jose Najarro: Yeah. More importantly, as a creator, when I do my video editing, I tend to look for a laptop or a desktop that usually has one of the high-end Nvidia graphics cards.
Danny Vena: Absolutely. What is impressive to me is that Nvidia is now more than just games. This is where the AI part comes in, a few years ago, when researchers were trying to build the first AI models that really worked, technology had not caught up with the idea yet. We needed massive lakes of data and we needed processors that could move that data around. At the time that this first came about in the ’80s, the idea of deep learning, which is a specific technique within AI and it involves a computer model that’s inspired by the structure and function of the human brain. We didn’t have the technology to bring that to life yet.
But in the last few years, we’ve overcome some of those technological hurdles and researchers found that the parallel processing of a GPU that renders these more lifelike graphics was also perfectly suited to the unique needs of artificial intelligence. What it does is it uses sophisticated algorithms and millions of data points to reproduce the capacity of the human brain to learn. They develop these models, they feed them multitudes and legions of examples so it can differentiate and discover relationships and similarities, but also to distinguish differences. In the simplest form that the AI that Nvidia chips enable involves pattern recognition and making associations.
This massive computing power that’s required is what the GPU provides, essentially accelerating the training of these deep learning systems. I think that that was a really important moment in Nvidia’s history because the company’s ability to pivot on this and essentially repurpose the humble old GPU to artificial intelligence. They didn’t stop there, they also created packages, which essentially was hardware and software packaged together in such a way that it enabled companies to basically turnkey AI operations. A company that had never done anything with AI before could come in and they could buy one of Nvidia’s supercomputers that had all of the AI functionality and could basically start AI models on Day 1. That was a really important, and that shows the forward thinking that comes from Nvidia’s management.
When you think about the progression of AI, nowadays if you want to use AI, it’s available in all of the world’s major cloud computing providers have it. Nvidia expanded into the cloud. Really high-end versions of Nvidia GPUs are used in all of the major cloud computing operations. This includes, and you’ll recognize all these names, Amazon‘s AWS, Microsoft Azure, Alphabet‘s Google Cloud, Alibaba Cloud, IBM Cloud, Baidu AI Cloud, Tencent Cloud, Oracle Cloud. They all use Nvidia GPUs for their high-performance computing needs and to power their AI systems. Now, this is important because this is an ongoing thing. These cloud computing operations, the amount of data that we’re generating in the world is ridiculously high and it’s doubling every few years. As that happens, they’re going to need to build more data centers to handle the data. When they build more data centers, they’re going to have to buy more Nvidia chips to run those data centers. You’ve got data centers, cloud computing, AI, all of these hot button areas of growth. Nvidia, you think back to the Gold Rush days.
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