The AI ​​boom is causing chip company Nvidia’s business to grow explosively

he artificial intelligence helped the chip company Nvidia achieve excellent business figures. The chip company is the largest provider of specialized chips for computing-hungry AI applications.

The AI ​​boom is causing chip company Nvidia’s business to grow explosively. In the last quarter, the Silicon Valley company doubled its sales year-on-year to $13.5 billion. Profits jumped from $656 million to just under $6.2 billion, which corresponds to 5.7 billion euros.

Chips and software from Nvidia are particularly suitable for applications based on artificial intelligence. The chip company is the largest provider of specialized chips for computing-hungry AI applications such as ChatGPT from OpenAI. That’s why the demand for Nvidia products is currently correspondingly high. Management expects a further increase in sales to around $16 billion for the third quarter, which runs until the end of October.

Analyst Harlan Sur from the US bank JP Morgan comments that the expansion of generative artificial intelligence (AI) and significant language and translator models further drives the demand for the chip manufacturer’s network platforms and software solutions. Current Nvidia figures also support the stock exchanges in Asia and Germany today.

In the same league as the tech giants

CEO Jensen Huang spoke of a change in the computer industry toward accelerated computing processes and generative AI. Analysts estimate that demand for Nvidia’s chips from this sector exceeds supply by at least 50 per cent. This imbalance is, therefore, likely to persist in the coming quarters. Competitor AMD hmarket share from Nvidia in the coming year. However, according to experts, Nvidia’s CUDA software is years ahead of AMD’s ROCm variant.

This is also reflected in the company’s market value. At the end of May, Nvidia reached a market value of more than a trillion dollars. The price of the share has already tripled this year. This brought the company into the exclusive circle of companies with a market capitalization of more than a trillion dollars.

Otherwise, only the technology group Apple, the software giant Microsoft, the online trading giant Amazon, Google’s parent company Alphabet, and the Saudi Arabian oil company Aramco have such a market value.

Nvidia depends on functioning supply chains.

The chip company has spoken out against tightening US restrictions on semiconductor deliveries to China. CFO Colette Kress said the current measures served their purpose. At Nvidia, revenue from China accounted for between 20 and 25 per cent of its data center business in the last quarter .

Given the global demand, Nvidia does not expect any immediate significant losses even if further possible restrictions are imposed. However, long-term, this will destroy the US chip industry’s opportunities in the vast Chinese market.

Nvidia does not produce its chips but develops them and outsources manufacturing to other companies. Therefore, Nvidia is heavily dependent on functioning supply chains.

“A long-term change”

Nvidia was founded 30 years ago by US-Taiwanese Jen-Hsun “Jensen” Huang. The company initially focused on graphics cards that offered computer gamers better-resolution images. High-performance microchips are now also used in the development of artificial intelligence. Huang emphasized that there is currently a “long-term change” in the world’s data centers from classic processors to the chip architectures offered by Nvidia.

These chips are “more difficult to get than drugs,” said technology billionaire Elon Musk, who recently founded his own company to develop artificial intelligence, xAI.

There are only four companies globally valued at over $2 trillion. These include Apple, Microsoft, the oil company Saudi Aramco, and, as of 2024, Nvidia. If you’re unfamiliar with Nvidia, it’s understandable, as the company does not produce a popular consumer product like Apple. Nvidia specializes in designing chips that are embedded deep within computers, focusing on a seemingly niche product that sees increasing reliance.

In 2019, Nvidia’s market value stood at around $100 billion. Its rapid ascension to a size 20 times that was largely fueled by one factor—the AI ​​​​craze. Nvidia has emerged as a major beneficiary in the AI ​​​​industry. For comparison , OpenAI, the maker of ChatGPT, which propelled this obsession into the mainstream, is currently valued at approximately $80 billion. According to research from Grand View Research, the entire global AI market was valued at slightly below $200 billion in 2023, both of which are small in comparison to Nvidia’s worth. With all attention focused on the company’s remarkable evolution, the prevailing question is whether Nvidia can maintain its dominant position. Here’s how the company reached this pinnacle.

Back in 1993, long before the widespread presence of AI-generated art and entertaining AI chatbots on our social media feeds, a startup was founded by three electrical engineers in Silicon Valley. This startup was focused on an exciting and rapidly growing segment in personal computing : video games.

Nvidia was established to develop a specific type of chip known as a graphics card, also referred to as a GPU (graphics processing unit), responsible for producing intricate 3D visuals on a computer screen. The quality of visuals rendered on a computer depends on the performance of the graphics card, a critical component for activities such as gaming and video editing. In its pre-IPO prospectus in 1999, Nvidia highlighted that its future success would hinge on the continued growth of computer applications reliant on 3D graphics. For the most part of its existence, game graphics were Nvidia’s primary focus.

Ben Bajarin, CEO and principal analyst at the tech industry research firm Creative Strategies, acknowledged that until recently, Nvidia had been “relatively isolated to a niche part of computing in the market.”

Nvidia became a dominant player in the realm of video game cards—an industry that generated over $180 billion in revenue last year. However, the company recognized the importance of diversifying beyond gaming graphics card production. While not all of its endeavors were successful, Nvidia’s attempt over a decade ago to establish itself as a major presence in the mobile chip market proved futile. Presently, Android phones utilize a variety of non-Nvidia chips, while iPhones are equipped with Apple-designed ones.

However, another initiative not only proved successful, but also became the reason behind Nvidia’s current prominence. In 2006, the company introduced a programming language called CUDA, which effectively harnessed the capabilities of its graphics cards for general computing tasks. This enabled its chips to efficiently handle tasks unrelated to rendering game graphics. It turned out that graphics cards were even better at multitasking than the CPU (central processing unit), often described as the central “brain” of a computer.

This made Nvidia’s GPUs ideal for computation-intensive tasks such as machine learning and crypto mining. 2006 coincided with Amazon’s launch of its cloud computing business, and Nvidia’s foray into general computing coincided with the burgeoning presence of massive data centers across the globe.

Nvidia has entered the league of tech giants known as the “Magnificent Seven”

Nvidia’s current status as a powerhouse is particularly noteworthy because for a significant part of Silicon Valley’s history, another chip-making behemoth, Intel, held a dominant position. Intel produces both CPUs and GPUs, along with other products, and manufactures its own semiconductors. However, due to several missteps, including delays in investing in the development of AI chips, the rival chipmaker’s preeminence has waned to some extent. In 2019, when Nvidia’s market value was slightly over $100 billion, Intel’s value was twice that amount. Now, Nvidia has joined the league of prominent tech stocks identified as the “Magnificent Seven,” a select group of tech stocks with a combined value surpassing the entire stock market of numerous affluent G20 countries.

Gil Luria, a senior analyst at the financial firm DA Davidson Companies, noted, “Their competitors were asleep at the wheel.” “Nvidia has long talked about the fact that GPUs are a superior technology for handling accelerated computing.”

Nvidia currently serves four primary markets: gaming, professional visualization (such as 3D design), data centers, and the automotive industry, providing chips for self-driving technology. A few years ago, gaming accounted for the largest portion of revenue at about $5.5 billion, surpassing the data center segment which generated approximately $2.9 billion.

However, with the onset of the pandemic, people spent more time at home, leading to increased demand for computer parts, including GPUs. In the fiscal year 2021, Nvidia’s gaming revenue surged by an impressive 41%, while data center revenue experienced an even more remarkable increase of 124%. By 2023, the revenue had grown by 400% compared to the previous year. tested, data centers have surpassed gaming in revenue, even during a gaming boom.

When Nvidia went public in 1999, it had 250 employees. Now, it boasts over 27,000 employees. Jensen Huang, Nvidia’s CEO and co-founder, currently possesses a personal net worth of around $70 billion, signifying an increase of over 1,700% since 2019 .

Chances are, you have encountered Nvidia’s products without even realizing it. Older gaming consoles like the PlayStation 3 and the original Xbox featured Nvidia chips, while the current Nintendo Switch utilizes an Nvidia mobile chip., additionally many mid- to high-range laptops come Equipped with Nvidia graphics cards.

With the surge in AI technology, the company aims to play a more pivotal role in people’s daily tech usage. For instance, Tesla cars’ self-driving feature and major tech companies’ cloud computing services leverage Nvidia chips, serving as a backbone for various daily internet activities, such as streaming content on Netflix or using office and productivity apps. OpenAI utilized tens of thousands of Nvidia’s AI chips to train ChatGPT.

Many people underestimate their daily reliance on AI, not realizing that some of the automated tasks they depend on have been enhanced by AI. Popular apps and social media platforms like TikTok, Instagram, X (formerly Twitter), and even Pinterest offer various AI functionalities Slack, a widely used messaging platform in workplaces, recently introduced AI capabilities to generate thread summaries and recaps of Slack channels.

Nvidia’s chips continue to sell out quickly due to high demand. However, substantial demand allows the company to charge awkwardly high prices for its chips. The chips used for AI data centers can cost tens of thousands of dollars, with top-of-the- line products occasionally selling for over $40,000 on platforms like Amazon and eBay. Notably, last year, some clients faced up to an 11-month wait for Nvidia’s AI chips.

Nvidia’s gaming business is thriving, and the price gap between its high-end gaming card and a similarly performing one from AMD continues to widen. In its last financial quarter, Nvidia reported a gross margin of 76%, meaning it cost them just 24 cents to make a dollar in sales. In contrast, AMD’s most recent gross margin was only 47%.

Advocates of Nvidia contend that its leading position is warranted due to its early investment in AI technology. They argue that Nvidia’s chips are worth the price due to their superior software and the extensive AI infrastructure built around Nvidia’s products. Nevertheless, Erik Peinert, a research manager and editor at the American Economic Liberties Project, suggests that Nvidia has benefited from TSMC, the world’s largest semiconductor maker, struggling to meet demand.

Furthermore, a recent report from The Wall Street Journal hinted at Nvidia wielding its influence to maintain dominance. The CEO of an AI chip startup named Groq alleged that customers feared Nvidia would retaliate with order delays if they sought other chip makers.

While it’s indisputable that Nvidia made significant investments in the AI ​​industry earlier than others, its hold on the market is not unassailable. A host of competitors, ranging from smaller startups to well-funded opponents like Amazon, Meta, Microsoft, and Google —each of which currently employs Nvidia chips—are rapidly advancing. Luria notes, “The biggest challenge for Nvidia is that their customers want to compete with them.”

It cannot be denied that Nvidia made significant investments in courting the AI ​​industry well before others caught on, but its dominance in the market is not unassailable. A host of rivals are emerging, ranging from small startups to well-funded adversaries such as Amazon, Meta, Microsoft, and Google, all of which currently utilize Nvidia chips. “Nvidia’s biggest challenge is that their customers are looking to compete with them,” says Luria.

The issue is not just that their customers are seeking a share of Nvidia’s substantial profits—they simply cannot continue to bear the high costs. Luria notes that Microsoft “went from allocating less than 10 percent of their capital expenditure to Nvidia to nearly 40 percent. That is not sustainable.”

Furthermore, the fact that over 70 percent of AI chips are purchased from Nvidia has concern among antitrust regulators worldwide— the EU has recently begun an investigation into the industry for potential antitrust violations. When Nvidia proposed a staggering $40 billion acquisition of Arm Limited in late 2020, a company that designs a chip architecture utilized in most modern smartphones and newer Apple computers, the FTC intervened to block the deal. “It was evident that the acquisition was intended to gain control over a software architecture that the majority of the industry relied on,” says Peinert. “The fact that they wield significant pricing power and face no effective competition is a genuine concern.”

Will the enthusiasm for AI wane? Whether Nvidia will sustain its status as a $2 trillion company— or soar to even greater heights— hinges fundamentally on the enduring interest of both consumers and investors in AI. Silicon Valley has witnessed the emergence of numerous newly established AI companies, but what proportion of them will thrive, and for how long will investors continue to inject funds into them?

The widespread awareness of AI arose because ChatGPT was an easily accessible— or at least, easily-demonstrated-on-social-media— novelty that captivated the general public. However, a significant portion of AI research is still focused on AI training as opposed to what is known as AI inferencing, which involves trained AI models to complete a task, such as the way ChatGPT responds to a user’s query or how facial recognition technology identifies individuals.

While the AI ​​inference market is expanding (and perhaps more rapidly than expected), a substantial portion of the sector is anticipated to continue to devote extensive time and resources to training. For training, Nvidia’s top-tier chips are likely to remain highly coveted, at least for a while. However, once AI inferencing gains momentum, the demand for such high-performance chips may decrease, potentially leading to Nvidia’s primacy slipping.

Several financial analysts and industry experts have expressed caution regarding Nvidia’s stratospheric valuation, suspecting that the excitement around AI may abate and that there may already be an excessive amount of capital being funneled into the production of AI chips. Traffic to ChatGPT has declined since last May , and some investors are scaling back their investments.

“Every major technology undergoes an adoption cycle,” says Luria. “As it gains visibility, it generates tremendous hype. Eventually, the hype becomes excessive, and then it wanes, leading to a period of disillusionment.” Luria anticipates that this will soon happen with AI—although this does not necessarily mean it is a bubble.

Nvidia’s revenue last year amounted to approximately $60 billion, reflecting a 126 percent increase from the previous year. However, its lofty valuation and stock price are not solely based on that revenue, but also on its anticipated sustained growth— for reference, Amazon, with a lower market value than Nvidia, generated nearly $575 billion in sales last year. For some experts, the path to Nvidia achieving profits substantial enough to justify the $2 trillion valuation appears daunting, particularly with the intensifying competition.

There is also the possibility that Nvidia could be hindered by the rapid advancement of microchip technology. Progress in this field has been rapid over the past few decades, but there are indications that the rate at which more transistors can be integrated into a microchip— allowing them to become smaller and more powerful— is slowing. Bajarin suggests that maintaining Nvidia’s ability to offer significant hardware and software enhancements that persuade its customers to invest in its latest AI chips could pose a challenge.

Despite potential challenges, it is likely that Nvidia will soon achieve the same level of recognition as Apple and Google. The reason for Nvidia’s trillion-dollar valuation is the widespread enthusiasm for AI, which in turn is largely driven by Nvidia.

Great expectations for AI

Investing a trillion dollars in something reflects a strong belief in its potential, and Silicon Valley truly believes in the transformative power of AI. In 2018, Google CEO Sundar Pichai famously stated that “AI is one of the most important things humanity is working on. It’s more profound than, I don’t know, electricity or fire.”

It’s universally agreed that fire is crucial. Some might even consider it as humanity’s first groundbreaking invention. However, tech leaders like Pichai believe that the potential of achieving effectiveness, general artificial intelligence is just as revolutionary as the discovery of fire. Following the release of OpenAI’s ChatGPT in November 2022, which revealed the true marvel of large language models (LLMs), a race began to emerge as to which company could harness that potential.

Investors hurried to support promising LLM startups such as OpenAI (currently valued at $80 billion or more) and Anthropic (estimated at $18.4 billion). In 2023, AI startups in the US raised $23 billion in capital, and there are over 200 such companies globally that are valued at $1 billion or more.

The significant amount of investment reflects the tech industry’s confidence in the enormous potential growth of the AI ​​​​market. According to a forecast by PwC, AI could contribute nearly $16 trillion to the global economy by 2030, mainly through significantly improved labor productivity.

Coupled with ample cash reserves held by tech giants, there is fierce competition among them to be at the forefront of AI development. Pichai highlighted on a recent earnings call that “the risk of underinvesting is dramatically greater than the risk of overinvesting,” emphasizing the belief that the AI ​​industry will be worth trillions, with the greatest value going to the early pioneers.

Nevertheless, as generative AI is costly to develop and operate, expenses continue to escalate.

Addressing the costs

OpenAI’s Sam Altman has described OpenAI as “the most capital-intensive startup in history” due to the increasing costs of training ever-larger models. Not only is the cost of developing the models high, but so too is the expense of running them. An analysis estimated that OpenAI began $700,000 in daily expenses to operate ChatGPT, primarily due to the extensive compute-intensive server time. As the usage of ChatGPT and other LLMs increases, these costs escalate further.

While Silicon Valley may not have originated the saying “you have to spend money to make money,” it certainly adheres to it. However, the revenue generated from these companies, mainly through subscriptions to their premium models, only covers a fraction of their expenses According to The Information, OpenAI could incur losses as high as $5 billion this year, nearly 10 times the amount lost in 2022.

This trajectory is concerning, as are the user numbers for ChatGPT. Tech analyst Benedict Evans recently highlighted that although many individuals and companies experiment with AI services like ChatGPT,fewer continue to utilize them. Notably, the usage of ChatGPT appears to decrease significantly during school holidays, indicating the user demographics.

Impressive as the capabilities of LLMs may be, particularly when compared to what was deemed feasible a decade ago, the promises of artificial general intelligence that could replace entire workforces have yet to materialize. Currently, the industry seems to face a common Silicon Valley issue: a lack of product-market fit. Chatbots are not yet a fully developed product, and the potential market size for them remains uncertain. This is why experts, ranging from Wall Street banks such as Goldman Sachs to tech venture capital firms like Sequoia Capital, have expressed concerns about the AI ​​industry, and it appears that investors are beginning to take notice.

Nevertheless, this is not to suggest that AI lacks revolutionary potential or that the industry will not ultimately fulfill those lofty aspirations. The dot com crash in the early 2000s was partly due to the overinvestment and overvaluation of startups at the time, yet what remained paved the way for today’s tech giants like Google and Meta. The same could one day be true for AI companies. However, unless the financial performance improves, it might not be these AI companies that will ultimately succeed.

Is Nvidia stock too highly valued?

When a fan requested Nvidia CEO Jensen Huang to autograph her chest earlier this month, that might have indicated that the excitement around the chipmaker might have reached unsustainable levels.

In recent years, Nvidia’s computer chips — which possess certain technical features that make them well-suited for AI applications — propelled the company to new levels of profitability. Nvidia briefly held the title of the world’s most valuable company last week; however, it lost that position a few days later during a days-long sell-off of its shares. While there has been some recovery in its stock price since then, it is currently the world’s third most valuable company with a market capitalization of $3.1 trillion, after Microsoft and Apple.

The sell-off occurred amid concerns that Nvidia might be overvalued. Financial research strategist Jim Reid of Deutsche Bank recently cautioned about “signs of over-exuberance” regarding Nvidia, and some of Nvidia’s executives have even sold off some of their stake in the company .

Despite the concerns, there are still numerous reasons to be optimistic about Nvidia: The company has established itself as a leading chipmaker in the industry, benefiting from an early bet on AI that has paid off as AI applications like OpenAI’s ChatGPT have brought broader public attention to the technology.

“It’s still early in the AI ​​competition,” said Daniel Newman, CEO of the Futurum Group, a tech research and analysis firm. “But virtually everyone who has been developing AI up to this point has likely done at least some of their most important work on Nvidia.”

The stock market has responded accordingly, with Nvidia being a part of the so-called “Magnificent Seven” tech stocks that contributed to a significant portion of stock market growth last year. Its stock price had surged by nearly 155 percent since January as of the market closing on Wednesday.

However, whether Nvidia can maintain such growth depends on advancements in AI and the extent to which businesses will adopt it.

How Nvidia rose to become one of the world’s most crucial chipmakers

Nvidia has long been recognized as the foremost producer of graphics cards for gaming. However, its graphics processing units (GPUs), the primary component of graphics cards, gained popularity during a surge in cryptocurrency mining, a process that involves solving complex mathematical problems to release new cryptocurrency coins into circulation.

This is due to the highly optimized nature of Nvidia GPUs for “parallel processing” — essentially, dividing a computationally challenging problem and assigning its various parts to thousands of processor cores on the GPU at once, solving the problem more quickly and efficiently than traditional computing methods.

estimated, generative AI also relies on parallel processing. Whenever you interact with ChatGPT, for instance, the AI ​​model needs to analyze large data sets — essentially, the world’s text-based online content at the time of ChatGPT’s last knowledge update — to provide you with an answer. Achieving this in real time and at the scale that companies like OpenAI aim for necessitates parallel processing carried out at data centers that house thousands of GPUs.

Nvidia recognized the potential gains from the GPU requirements of generative AI early on. Huang has described 2018 as a “bet the company moment” in which Nvidia reimagined the GPU for AI, well before the emergence of ChatGPT. The company strategically aligned its research and development as well as acquisitions to benefit from the impending AI boom.

“They were playing the game before anyone else,” Newman commented.

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

Therefore, despite Nvidia’s competitors like AMD and Intel introducing similar offerings, even at lower price points, Nvidia has retained the majority of the GPU market share for businesses, partly because developers have grown accustomed to CUDA and are reluctant to switch.

“What [Nvidia] realized very early on is that if you want to dominate in hardware, you need to excel in software,” Newman explained. “Many of the developers who are creating AI applications have established them and feel comfortable creating them using CUDA and running them on Nvidia hardware.”

All of these factors have positioned Nvidia to capitalize on the ever-increasing demands of generative AI.

Can Nvidia sustain its current prosperity?

Nvidia’s competitors are unlikely to pose an immediate threat to its status as an industry leader.

“In the long term, we anticipate tech giants to seek out alternative sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will probably eat into, but not replace, Nvidia’s dominance in AI,” Brian Colello, a strategist for Morningstar, wrote in a recent report.

However, Nvidia’s ability to maintain the level of growth it has experienced in the past year is linked to the future of generative AI and the extent to which it can be monetized.

Access to ChatGPT is currently open to everyone at no cost, but a $20 monthly subscription will provide access to the most advanced version. However, the primary revenue stream does not come from individual subscribers at the moment. Instead, it is derived from businesses. It remains uncertain how companies will incorporate generative AI into their business models in the years to come.

For Nvidia’s growth to be sustainable, it is crucial that major companies such as Salesforce or Oracle, known for selling software to enterprises, develop new software that heavily utilizes AI. This would lead to these large companies signing yearly contracts to gain access to extensive computing power, according to Newman.

“Otherwise, the fundamental concept of establishing large data centers around the world filled with GPUs becomes somewhat risky.”

The decision on whether to invest in Nvidia stock depends on how optimistic you are about the penetration of AI into the economy.”We anticipate that Nvidia’s future will be closely linked to the AI ​​market, for better or worse, over an extended period,” Collelo notes.