Is Nvidia overpriced? It depends on the future of AI.

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When a fan asked Nvidia CEO Jensen Huang to sign his chest earlier this month, it may have been a sign that rumors surrounding the chipmaker had reached unsustainable heights.

Over the past few years, Nvidia's computer chips — which have some technical capabilities that make them well-suited for AI applications — have propelled the company to new heights of profitability. Last week, Nvidia briefly became the world's most valuable company. Three days later, he lost the honor during a day-long selloff of his shares. Although its stock price has recovered somewhat, it is now the third most valuable company in the world with a market capitalization of $3.1 trillion, behind Microsoft and Apple.

The sale comes amid concerns that Nvidia is overvalued. Recently, Deutsche Bank financial research strategist Jim Reed warned of “signs of oversold” about Nvidia, and Nvidia executives have even sold some of their holdings in the company.

There are still plenty of reasons to be excited about Nvidia: The company has established itself as an industry-leading chipmaker, benefiting from an early bet on AI that has resulted in Chatbots like OpenAI's ChatGPT have widened the public's attention to the technology.

“It's very early in the AI ​​race,” said Daniel Newman, CEO of Futurum Group, a tech research and analysis firm. “But everyone who's been building AI up to this point has probably done at least some of their significant work at Nvidia.”

The stock market has responded accordingly. Nvidia is part of the so-called “Magnificent Seven” tech stocks that have accounted for most of the stock market's growth in the past year. Its stock is up about 155 percent since January after the market closed on Wednesday.

But whether Nvidia can continue to replicate that kind of growth depends on advances in AI, as well as to what extent — and how quickly — businesses adopt it.

How Nvidia Became One of the World's Leading Chipmakers

Nvidia has long been considered the leading producer of graphics cards for gaming. However, its graphics processing units (GPUs), which are the main component of graphics cards, gained popularity amid the rise of cryptocurrency mining, a process that involves complex mining of new cryptocurrency coins to circulate. Involves solving mathematical problems.

That's because Nvidia GPUs are highly optimized for what's called “parallel processing”—basically, dividing up a computationally difficult problem and assigning it to thousands of processor cores on the GPU simultaneously. , solving the problem faster and more efficiently than traditional computing methods. .

As it turns out, creative AI also relies on parallel processing. Every time you query ChatGPT, for example, the AI ​​model has to parse large datasets — the world's text-based online content collection, according to ChatGPT's last knowledge update — to give you an answer. Took To do this in real time and at the scale that companies like OpenAI hope to develop requires parallel processing performed in data centers that contain thousands of GPUs.

Nvidia realized what it had gained from the GPU requirements of generative AI early on. Huang cites 2018 as “the company's bet moment,” with Nvidia reimagining GPUs for AI before ChatGPT hit the scene. The company structured its research and development and merger and acquisition strategies to capitalize on the coming AI boom.

“They were playing the game when no one else was,” Newman said.

In addition to offering GPUs optimized for this purpose, Nvidia created a programming model and parallel computing platform called Compute Unified Device Architecture (CUDA) that has become the industry standard. This software makes the capabilities of Nvidia GPUs more accessible to developers.

So while Nvidia's rivals such as AMD and Intel have come to introduce similar offerings, even at lower price points, Nvidia has retained a large share of the business GPU market, in part because developers can use CUDA. They are used to it and don't want to do it. Switch

“What? [Nvidia] It became clear very quickly that if you want to win in hardware, you have to win in software,” Newman said. “A lot of developers who are building apps for AI have built them and CUDA's It's easy to build them using and run them on Nvidia hardware.”

All of this positions Nvidia to meet the ever-growing needs of generative AI.

Can Nvidia push the good times?

Nvidia's competitors likely pose no immediate threat to its status as the industry leader.

“In the long term, we expect tech titans to seek other means or in-house solutions to diversify from Nvidia in AI, but more likely, these efforts will erode Nvidia's AI dominance. will, but will not replace it,” Brian Colello, a strategist at Morningstar, wrote in a recent report.

However, Nvidia's ability to maintain the level of growth seen in the past year is tied to the future of AI generated and the extent to which it can be monetized.

Currently anyone can access ChatGPT for free, although a $20 monthly subscription fee will get you access to its latest and greatest version. But individual subscribers aren't currently where the real money is.

Rather, it is with business. And at this point, it's anyone's guess how companies will integrate generative AI into their business models in the coming years.

To make Nvidia's growth sustainable, big companies like Salesforce or Oracle — which sell software to enterprises — will have to offer new software that “uses tons of AI,” even if these big companies don't. are signing annual agreements that grant them access. The largest amount of computing power, Newman said.

“Otherwise, the central thesis of building these massive megawatt data centers around the world full of GPUs becomes a bit of a risk.”

So should you buy Nvidia stock? It depends on how excited you are about AI and its potential to permeate the economy.

“We think Nvidia's prospects will be tied to the AI ​​market, for better or worse, for quite some time,” Colello writes.

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