How Chips for AI Are Pushing Nvidia to $1 Trillion | WSJ

- [Narrator] This is the exclusive trillion dollar company club. It's made up of some of tech's biggest giants, and for a moment, on May 30th, this company, Nvidia. It's not a household name, but one day in late May, Nvidia added nearly $184 billion in market value. That's a single day sum worth more than other companies in the semiconductor industry, and just a fraction of its total value. The company's record sales have been fueled by an emerging technology. - We're the world's engine for AI. - [Narrator] Here's how an under-the-radar graphics processor is cashing in on the AI craze and what's next for its strategy. - [Character] Excellent. - [Narrator] When Nvidia was founded in 1993, it established itself as a leader in graphic processing units, or GPUs, for video games. The company's powerful chips made images crisper and less choppy. - Nature of our technology is to accelerate multimedia applications for the consumer. - [Narrator] In the years since, the company's chips have become an indispensable part of many other products, from PCs to cars to robots. Nvidia made a pivotal decision in 2006 when it started allowing software developers to play with its GPUs. - If you want to be a trillion dollar company, you can't do just one thing, kind of like opening a door. And once they opened that door, people started to tinker. - [Narrator] One of those expansions was cryptocurrency mining. The company's GPUs could handle the large amount of computational power the task required. Business flourished. Rising sales from the crypto rush helped Nvidia pass rival Intel in market value in 2020. But sales fell as crypto crashed and the gaming industry slumped. Still, the chip maker was starting to see another frontier boom: generative AI. In May, sales of chips for the data centers needed to power AI were up by 14%, thanks in large part to the growing need for Nvidia chips in AI calculations. For Nvidia, that was a decade in the making. The company's chips broke through in the AI community in 2012 with a neural network called AlexNet. - We saw early on about a decade or so ago that this way of doing software could change everything. - It was very futuristic. It was very uncertain at that point. Nobody knew how big AI was gonna be. They made that big bet at a time when a lot of other competitors were not making that kind of bet. - We risked everything to pursue deep learning. - [Narrator] Nvidia chips are suited for powering AI because of their ability to do lots of complex computations simultaneously. Traditional processing units can't do that as quickly. And other GPUs, like those from Intel and AMD, haven't gained major market share in AI computing. - If you think about how graphics work, your monitor, your computer monitor has a lot of pixels, thousands of pixels on it, and your computer needs to calculate at any given time what each of those pixels need to look like. It was discovered fairly quickly after Nvidia kind of opened up the door for people to use its chips for other things that they were actually really good at the kind of mathematics that underpins artificial intelligence. - [Narrator] In late 2022, AI exploded with the public release of OpenAI's ChatGPT and Nvidia's stock skyrocketed. While companies like Google, Microsoft, and Amazon battle it out in the AI race, Nvidia is raking in the cash. That's because its chips power most of them. - For Nvidia, it's a bonanza. All of these folks who are competing to get a slice of the generative AI pie need Nvidia. - [Narrator] In 2018, the division that focuses on AI computation made up less than half of the company's sales. By 2022, it was the majority. - It went from Wall Street expectation of 7 billion to Nvidia saying actually gonna make 11 billion. And so that really opened people's eyes. It was a real statement that, you know, this generative AI craze that everybody's talking about is more than just a hype cycle. - [Narrator] But that success is creating a different problem for the company: supply. - The demand is literally from every corner of the world. - GPUs are at this point considerably harder to get than drugs. (Elon chuckling) - [Narrator] The company's supply chain hasn't been able to keep pace. - The the chip manufacturing cycle is such that you can't just immediately make more of these things like today if you want them. - The company says it has filled out some of its supply. - [Colette] We are working on both supply today for this quarter but we have also procured a substantial amount of supply for the second half. - [Narrator] But the chip's global demand has also caught the company in the crosshairs of increasing tensions between the US and China. Last year, the company said $400 million of its quarterly sales could be subject to new US chip licensing requirements for China. In response, Nvidia began offering an alternative chip to customers in China. Despite some roadblocks, the chip industry has its eyes on Nvidia's success. - They're still riding this boom. It's no nowhere near done. The real question is whether companies can build huge, huge businesses that are based on that artificial intelligence capability. (pensive music)

Channel: Wall Street Journal

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Keywords: nvidia, ai, nvidia stock, nvidia ai, nvidia stock news, nvidia stock analysis, nvidia news, nvidia valuation 2023, nvidia share price, wsj, ai chips, chips for ai, semiconductor, chip makers, chipmakers in the usa, chipmaker stocks, nvidia ai chip, ai tool, ai stock, generative ai, nvidia semiconductor manufacturing, nvidia chips, artificial intelligence, supply chain issues, nvidia market cap, ai chat, chipmaker, ai boom, apple, microsoft, amazon, 1 trillion business, bnss

Id: OPID_b1k_cw

Length: 5min 41sec (341 seconds)

Published: Thu Jun 08 2023