What you need to know about Nvidia and the AI ​​chip arms race

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While Nvidia’s share price is down from its peak earlier in the week, its stock is up 262% in the past year, going from about $242 a share to $875.

The booming artificial intelligence industry has fueled demand for the hardware that powers AI applications: graphics processing units, a type of computer chip.

Nvidia is the GPU market leader, making GPUs that are used by apps like AI chatbot ChatGPT and by big tech companies like Facebook’s parent company, Meta.

Nvidia is part of a group of companies known as The Magnificent Seven, a reference to the 1960s Western film, that benefited in the 2023 stock market. Others in the group include Alphabet, Amazon, Apple, Meta, Microsoft and Tesla.

But Nvidia faces rivals who want a share of the chip market and businesses that want to reduce their reliance on the company. Intel plans to launch a new AI chip this year, Meta wants to use custom chips in its data centers and Google has developed cloud tensor processing units, which can be used to train AI models. Is.

AI chip startups are also popping up, including names like Cerebras, Groq and Tenstorren, said Matt Bryson, senior vice president of research at Wedbush Securities.

Why are GPUs important for AI?

Sachin Saptnekar, a professor of electrical and computer engineering at the University of Minnesota, explained that GPUs were originally used in video games to render computer graphics.

“Ultimately, it turned out that the kinds of computations required for graphics are actually very compatible with what is required for AI,” said Saptnekar.

Sapatnekar said AI chips can do parallel processing, which means they process a large amount of data and handle a large number of computations at the same time.

In practice, this means that AI algorithms are now capable of being trained on large numbers of images to determine whether a photo of a cat is a cat or not, Saptnekar explained. When it comes to language, GPUs help train AI algorithms on large amounts of text.

These algorithms can then produce images resembling a cat or tongue that mimic a human, among other functions.

Why is Nvidia’s share price rising?

Right now, Nvidia is the leading maker of chips for generative AI, and it’s a very profitable company, explained David Kass, a clinical professor at the University of Maryland’s Robert H. Smith School of Business.

Nvidia controls 80% of the entire global GPU semiconductor chip market. In its latest earnings report, Nvidia reported revenue of $22.1 billion for the fourth quarter of fiscal 2024, up 265% from last year. Its GAAP earnings (earnings based on uniform accounting standards and reporting) were $4.93 per diluted share, up 765% from last year. Its non-GAAP earnings (excluding extraordinary items) were $5.16 per diluted share, up 486% from the prior year.

Kass said another reason Nvidia’s share price has skyrocketed in recent months is that the stock’s success itself is attracting additional investment.

Cass explained that individuals and organizations are jumping on the train as they watch it leave the station. Or, in other words: FOMO, he said.

Bryson of Wedbush Securities pointed out that the company was also able to differentiate itself through the development of CUDA, which Nvidia describes as a “parallel computing platform and programming model.”

Bryson added that Nvidia’s success doesn’t necessarily mean its GPUs are superior to the competition. But he said the company has built a powerful infrastructure around CUDA.

Nvidia has developed its own CUDA programming language and offers the CUDA takeit which includes code libraries for developers.

“Let’s say you want to do a specific operation. You can write the code for the entire operation from scratch. Or you can have specific code that’s already implemented on the hardware. So Nvidia has These are libraries of pre-bundled packages. of code,” said Saptnekar.

With Nvidia far ahead of the competition, Bryson said Advanced Micro Devices, or AMD, is trying to position itself as the number two player in the AI ​​chip space. AMD makes both central processing units, which compete with the likes of Intel and GPUs.

AMD’s share price has risen nearly 143 percent over the past year as demand for its AI chips has surged.

Jeffrey Macher, a professor of strategy, economics and policy at Georgetown University’s McDonough School of Business, said he questions whether Nvidia will be able to meet the growing demand for AI chips on its own.

“This is going to be an industry that will see an increasing number of competitors,” Macher said.

Do these chip companies have weak points?

Despite Nvidia and AMD’s success, their supply chains have wrinkles. Both rely heavily on a Taiwanese semiconductor manufacturing company to make their chips, which would leave them vulnerable if something went wrong with the company.

Macher said the semiconductor market used to be vertically integrated, meaning chip designers produced the chips themselves. But Nvidia and AMD are virtual companies, meaning they are companies that outsource their chip manufacturing.

As we saw during the early stages of the COVID-19 pandemic, supply chain disruptions led to shortages in all sorts of different sectors, Marketplace’s Meghan McCarty Carino reports.

TSMC plans to build Arizona chip plants That can help alleviate some of these concerns. But tech publication The Information reported that these chips “will still require assembly in Taiwan.”

And TSMC’s location carries geopolitical risks. If China invades Taiwan and TSMC becomes a Chinese company, U.S. companies may be reluctant to use TSMC for fear that the Chinese government will appropriate their designs, Machar said.

Is Nvidia stock a bubble?

Kass said he sees no parallel between Nvidia’s soaring stock and the dot-com bubble of the early 2000s, when many online startups tanked after their share prices reached unrealistic levels thanks to An influx of cash from venture capital firms was over-optimistic. their ability.

Some of these companies not only failed to turn a profit, but unlike Nvidia, which is backed by real earnings, didn’t even manage to generate any revenue, Kass said.

He thinks there may be a correction or a point where Nvidia stock will be considered overvalued. He explained that the bigger your company, the harder it is to maintain your growth rate. Once that growth rate comes down, sales can be rapid.

But Kass said he doesn’t think there will be a permanent and/or severe downturn for the company.

However, the commercial viability of AI is uncertain. Bryson said there are predictions of how big the AI ​​chip market will become — AMD, for example, suggested the AI ​​chip market will reach $400 billion by 2027 — but those numbers are hard to verify.

Bryson compared AI to 4G, the fourth generation of wireless communications. He pointed out that apps like Uber and Instagram were enabled by 4G, and explained that AI is similar in that it is a platform on which a set of future applications will be built.

“We’re not really sure what many of these apps will look like,” he said. When they launch, it will help people better estimate what the market should be worth – whether it’s $400 billion or $100 billion.

“But I also think that at the end of the day, the reason companies spend so much on AI is because it’s going to be the next Android or the next iOS or the next Windows,” Bryson said.

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