Although Nvidia’s stock price is down from its highs earlier this week, the stock has soared 262% over the past year, from about $242 to $875 per share at the close.
The rise of the artificial intelligence industry is accelerating demand for the hardware that powers AI applications: graphics processing units, a type of computer chip.
Nvidia is a leader in the GPU market, making GPUs used in apps such as the AI chatbot ChatGPT and major technology companies such as Facebook’s parent company Meta.
Nvidia is part of a group of companies known as the Magnificent Seven, named after the 1960 Western movie that led the stock market rally in 2023. Other companies in this cohort include Alphabet, Amazon, Apple, Meta, Microsoft, and Tesla.
But NVIDIA faces competitors looking to grab chip market share and companies looking to reduce their dependence on the company. Intel plans to launch new AI chips this year, Meta wants to use its own custom chips in its data centers, and Google has developed Cloud Tensor Processing Units that can be used to train AI models.
AI chip startups are also emerging, including names like Cerebras, Grok and Tenstren, said Matt Bryson, senior vice president of research at Wedbush Securities.
Why do we need these GPUs for AI?
Sachin Sapatnekar, a professor of electrical and computer engineering at the University of Minnesota, explained that GPUs were originally used to render computer graphics in video games.
“Ultimately, it turned out that the kind of computation needed for graphics is actually very compatible with what is needed for AI,” Sapatnekar said.
Sapatnekar said AI chips are capable of parallel processing, meaning they can process large amounts of data and handle large amounts of calculations at the same time.
What this means in practice is that an AI algorithm can now be trained on a large number of photos to figure out how to detect, for example, whether an image of a cat is of a cat, Sapatnekar explained. did. When it comes to languages, GPUs help AI algorithms train on large amounts of text.
These algorithms can generate cat-like images and human-mimicking language, among other features.
Why is NVIDIA’s stock price rising?
Today, Nvidia is a leading maker of chips for generative AI, and a highly profitable company, explains 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 its fiscal 2024 fourth quarter revenue of $22.1 billion, which was a 265% increase over last year. GAAP earnings per diluted share (earnings based on Uniform Accounting Standards and Reporting) was $4.93, an increase of 765% from last year. Non-GAAP diluted earnings per share (excluding extraordinary events) was $5.16, an increase of 486% from the prior year.
Another reason Nvidia’s stock price may have soared in recent months is that the stock’s own success is attracting additional investment, Kass said.
Kass explained that individuals and groups may jump on the train as they see it leave the station. In other words, “FOMO,” he said.
Wedbush Securities’ Bryson noted that NVIDIA’s development of CUDA, which it describes as a “parallel computing platform and programming model,” also differentiated the company.
Bryson added that Nvidia’s success doesn’t necessarily mean its GPUs are better than its competitors. However, he said the company is building a strong infrastructure around CUDA.
Nvidia has developed its own CUDA programming language and provides CUDA takeit, which includes a library of code, for developers.
“Suppose you want to perform a specific operation. You can write the code for the entire operation from scratch. Or you can use specialized code that is already streamlined on the hardware. So, Nvidia “We have libraries that are like pre-bundled packages. We’re talking about code,” Sapatnekar said.
Bryson said Advanced Micro Devices (AMD) is poised to secure the No. 2 spot in the AI chip space as Nvidia has a significant lead over its competitors. AMD makes both central processing units and GPUs, competing with Intel and others.
AMD stock has increased about 143% since last year as demand for AI chips grows.
Jeffrey Matcher, a professor of strategy, economics and policy at Georgetown University’s McDonough School of Business, said he doubts Nvidia will be able to meet the growing demand for AI chips entirely on its own.
“It’s going to be an industry with an increasing number of competitors,” Matcher said.
Do these chip companies have weaknesses?
Despite Nvidia and AMD’s success, there are wrinkles in the supply chain. Both companies rely heavily on Taiwan Semiconductor Manufacturing Co. to make their chips, leaving them vulnerable if something goes wrong with the company.
Masher said the semiconductor market used to be vertically integrated, meaning chip designers themselves were manufacturing these chips. But Nvidia and AMD are fabless companies, meaning they outsource their chip manufacturing.
As seen during the early stages of the COVID-19 pandemic, supply chain disruptions have created shortages across all sectors, Marketplace’s Meghan McCarty Carino reported.
TSMC plans to build chip factory in Arizona It may help alleviate some of these concerns. However, technology publication The Information reported that these chips “still require assembly in Taiwan.”
And TSMC’s location comes with 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, Masher said. .
Is Nvidia stock in a bubble?
Kass said he doesn’t see any similarities between Nvidia’s stock price rise and the dot-com bubble of the early 2000s. At the time, many online startups sank as their stock prices reached unrealistic levels thanks to an influx of money from venture capital firms that were overly optimistic about their investments. their potential.
Kass said some of these companies not only weren’t profitable, but weren’t even able to extract revenue, unlike Nvidia, which is supported by real profits.
He believes there may be a correction or point where NVIDIA stock is perceived to be overvalued. He explained that the larger the company, the harder it is to maintain its growth rate. If this growth rate declines, a sharp decline could occur.
But Kass said he doesn’t think the company’s downturn will be sustained or sharp.
However, the commercial viability of AI is uncertain. Bryson said there are predictions about how big the AI chip market will be, for example AMD has suggested the AI chip market will be worth $400 billion by 2027, but he would like to verify that number. said it is difficult.
Bryson compared AI to 4G, the fourth generation of wireless communications. He pointed out that apps like Uber and Instagram were made possible by 4G, and explained that AI is similar in the sense that it is the platform on which future applications will be built.
He said he’s not sure what many of those apps will be. When they launch, they will help people better assess what the market should be valued at, whether it’s $400 billion or $100 billion.
“But I also think that at the end of the day, companies are spending a lot of money on AI because it’s going to be the next Android, the next iOS, or the next Windows,” Bryson said.
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