Nvidia Could Be The Best Way To Invest In AI Right Now

Nvidia Could Be The Best Way To Invest In AI Right Now
Paul Allison, CFA

about 1 year ago7 mins

  • Nvidia’s trailblazing development of graphics processing units gave it the foundation for the success it enjoys today, as one of the most exciting and fastest-growing semiconductor companies in the world.

  • But Nvidia’s best days might be still to come if AI takes off in a big way.

  • The market likes Nvidia. And so its stock price is expensive. The question for you is: could Nvidia grow by even more than the market is expecting?

Nvidia’s trailblazing development of graphics processing units gave it the foundation for the success it enjoys today, as one of the most exciting and fastest-growing semiconductor companies in the world.

But Nvidia’s best days might be still to come if AI takes off in a big way.

The market likes Nvidia. And so its stock price is expensive. The question for you is: could Nvidia grow by even more than the market is expecting?

Mentioned in story

You don’t have to know a ton about artificial intelligence (AI) to know it’s going to be huge. And there are companies other than the Big Tech titans that have a stake in the technology. Nvidia is one of them – and it could be the single best AI investment play out there. So, let’s take a look at this innovative giant of the semiconductor world, the opportunities and risks that are right at its feet, and whether it belongs in your portfolio…

Nvidia has a market value of $476 billion. Traditional valuation metrics are high, with a price-to-earnings (P/E) of 45x and an enterprise-value-to-sales (EV/S) ratio of 17x. The firm’s enjoyed rapid sales growth – averaging 31% – over the past five years and boasts an impressive margin of 28%. Source: Finimize Markets, Google.
Nvidia has a market value of $476 billion. Traditional valuation metrics are high, with a price-to-earnings (P/E) of 45x and an enterprise-value-to-sales (EV/S) ratio of 17x. The firm’s enjoyed rapid sales growth – averaging 31% – over the past five years and boasts an impressive margin of 28%. Source: Finimize Markets, Google.

So, what’s Nvidia’s story then?

Well, it’s the undisputed leading designer of the semiconductors that currently power AI technology, for one. And its chips are behind a lot more than that. Rip apart the computers that fuel autonomous driving, aerospace simulations, and even drug discoveries, and you’ll find Nvidia’s graphics processing units, or GPUs.

Before Nvidia came along, personal computing needs were taken care of by central processing units (CPUs) – which were the “brains” of computers – simultaneously performing all the necessary tasks. But Nvidia’s founder Jensen Huang (Americanized from his Taiwanese name, Jen-Hsun Huang) saw a future where the performance of specific computing functions, like graphics, sound improvements, or network speeds, could be enhanced through specialized plug-in cards.

In the 1990s, blockbuster movies like Jurassic Park and early versions of the hugely popular 3D game Doom put the graphics industry on the cusp of a breakout. Huang believed graphics would be the springboard for a massive boom in the gaming industry. What kid of the ‘80s and ‘90s doesn’t remember obsessing about computer graphics?

Doom. Source: PekoeBlaze blog.
Doom. Source: PekoeBlaze blog.

Nvidia – cleverly named by merging invidia (literally “envy” in Latin) and NV, which was the firm’s first product name – emblazoned itself with a green logo, but it wasn’t the envy of the chip world yet. In fact, its ambitious strategic vision almost cratered the firm. See, big dog Microsoft was lying in wait, and came out with its own simplified, cheaper way for developers to make 3D graphics games. And lured by Microsoft’s gravitas, game developers flocked to the firm's standards, leaving Nvidia to plow a lonely furrow.

But Huang and Nvidia were built of stern stuff, and after a few near-death experiences and some necessary strategic pivots – including ripping up its own standards and flipping to Microsoft’s – they found a way to outmaneuver their rivals and build an unassailable lead in the 3D gaming graphics market.

In 1999, Nvidia launched the third iteration of its graphics card (GeForce 256) and called it a graphics processing unit (GPU). The move signaled the firm's intention to create a chip that could go toe-to-toe with the CPU – a modest middle finger to Intel, CPU market god.

Nvidia went on to figure out how to unleash its GPU technology and threw tons of money at scientific computing, the early breeding ground for AI. And today, Nvidia’s chips trounce the performance of CPUs, making them well-suited for the high-performance computing power needed for machine learning and AI. Think of it this way: fancy tools like ChatGPT are the output of machine learning; Nvidia’s GPUs are the input.

Where’s it headed next?

Gaming still represents nearly half of Nvidia’s revenues, and growth in the industry will be what it will be. There’s enough innovating going on – in virtual or augmented reality, for example – to assume gaming can continue to enjoy premium growth. But the industry’s become a bit long in the tooth, and won’t power the big growth rates needed to justify Nvidia’s share price valuation. The same is probably true for the firm’s professional visualization business (8% of revenue), which is ultimately hostage to the amount of money its mature industrial customers want to spend.

Nvidia’s quickly accelerating auto business is a bit more exciting. Electric vehicles (EVs) and autonomous driving cars consume a lot more computing power – twice the semiconductor content in fact – than regular cars, and Nvidia has a small (2% of revenues) but booming auto chips business.

And then there’s AI. Nvidia makes around 40% of its revenues by selling products to datacenter service providers like Microsoft and Amazon, and it’s inside those datacenters that machine learning and AI are being cultivated. No one really knows how AI will infiltrate our lives on a day-to-day basis, but as the world tries to figure that out, it’ll consume a gluttonous amount of semiconductors. Putting a number on that is impossible, and that’s precisely the point. Investors love a theme whose upside is difficult to quantify because it pops a cork on valuations. In other words, if AI turns out to be as exciting as everyone thinks, you can tear up the rule book for valuing Nvidia shares: they will probably be moon-bound.

What could go wrong?

Now, all that blue-sky thinking should, of course, be balanced with a healthy dose of skepticism. Nvidia’s out in front right now, but AMD and others will keep snapping at its heels, and as Nvidia’s own history has shown, you’re only a semiconductor cycle away from having your lead usurped. And that’s important to be aware of. There’s also the risk, of course, that AI’s a flash in the pan. With all the ChatGPT hype out there, that might seem unlikely, but there has been misplaced excitement about technologies before. Just ask Meta shareholders how they feel about the metaverse right now...

Closer to the here and now, Nvidia has a tricky year or so to navigate. It’ll have to find its way through an economic downturn that will put a dent in its more cyclical businesses. Semiconductor cycles are amplified versions of economic cycles, after all, and that means the ups can be euphoric but the downs are outright depressing. And right now the market is weighing up just how bad the pending down cycle will be.

So, is it a good investment?

First the punchline: by my math, the market’s expecting Nvidia to grow its cash flow somewhere around 20% a year for the next 10 years. That sounds like a lot, but the firm’s posted an average of 27% cash flow growth, (which came from 27% sales growth, and 30% profit growth) a year over the past ten years.

For rapid-growth firms like Nvidia, traditional valuation multiples like price-to-earnings (P/E) are a bit meaningless. See, despite its historical success, the stock price reflects future cash flows. So all Nvidia’s 45x P/E tells you is that the market has high hopes. Your best bet is to try and get your head around what those hopes are. Forecasting profit is hard, so I use a rough discounted cash flow (DCF) analysis for a temperature check. I wrote more about it here. Basically, all you need to do is play around with some growth numbers until the sheet computes a value for Nvidia that equates to the current market value: that’d be 20% growth for 10 years and 3% thereafter.

Source: Finimize, Koyfin.
Source: Finimize, Koyfin.

Now, DCFs are by no means precise but when used in this way they’re useful because they give you a reference point – and from that, you can draw your own conclusion. In this case, the question is whether you believe Nvidia will do better or worse than that 20% a year cash flow growth.

If you think the firm’s cyclical businesses will suffer a prolonged downturn or you’re not convinced AI will take off any time soon, then that 20% growth probably looks overly optimistic to you. But, if you’re pretty sure that AI is ready to start taking over the world – not in some evil, dystopian way, of course – then 20% growth might seem on the low side. And in that case, you could consider buying shares in Nvidia (NVDA), or in the Wisdomtree Artificial Intelligence and Innovation Fund (ticker: WTAI; expense ratio: 0.45%).

Disclaimer: These articles are provided for information purposes only. Occasionally, an opinion about whether to buy or sell a specific investment may be provided. The content is not intended to be a personal recommendation to buy or sell any financial instrument or product, or to adopt any investment strategy as it is not provided based on an assessment of your investing knowledge and experience, your financial situation or your investment objectives. The value of your investments, and the income derived from them, may go down as well as up. You may not get back all the money that you invest. The investments referred to in this article may not be suitable for all investors, and if in doubt, an investor should seek advice from a qualified investment advisor.

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