Jensen Huang, co-founder and chief executive officer of Nvidia Corp., during the Nvidia GPU Technology Conference (GTC) in San Jose, California, US, on Tuesday, March 19, 2024.
David Paul Morris | Bloomberg | Getty Images
Nvidia’s 27% rally in May pushed its market cap to $2.7 trillion, behind only Microsoft and Apple among the most-valuable public companies in the world. The chipmaker reported a tripling in year-over-year sales for the third straight quarter driven by soaring demand for its artificial intelligence processors.
Mizuho Securities estimates that Nvidia controls between 70% and 95% of the market for AI chips used for training and deploying models like OpenAI’s GPT. Underscoring Nvidia’s pricing power is a 78% gross margin, a stunningly high number for a hardware company that has to manufacture and ship physical products.
Rival chipmakers Intel and Advanced Micro Devices reported gross margins in the latest quarter of 41% and 47%, respectively.
Nvidia’s position in the AI chip market has been described as a moat by some experts. Its flagship AI graphics processing units (GPUs), such as the H100, coupled with the company’s CUDA software led to such a head start on the competition that switching to an alternative can seem almost unthinkable.
Still, Nvidia CEO Jensen Huang, whose net worth has swelled from $3 billion to about $90 billion in the past five years, has said he’s “worried and concerned” about his 31-year-old company losing its edge. He acknowledged at a conference late last year that there are many powerful competitors on the rise.
“I don’t think people are trying to put me out of business,” Huang said in November. “I probably know they’re trying to, so that’s different.”
Nvidia has committed to releasing a new AI chip architecture every year, rather than every other year as was the case historically, and to putting out new software that could more deeply entrench its chips in AI software.
But Nvidia’s GPU isn’t alone in being able to run the complex math that underpins generative AI. If less powerful chips can do the same work, Huang might be justifiably paranoid.
The transition from training AI models to what’s called inference — or deploying the models — could also give companies an opportunity to replace Nvidia’s GPUs, especially if they’re less expensive to buy and run. Nvidia’s flagship chip costs roughly $30,000 or more, giving customers plenty of incentive to seek alternatives.
“Nvidia would love to have 100% of it, but customers would not love for Nvidia to have 100% of it,” said Sid Sheth, co-founder of aspiring rival D-Matrix. “It’s just too big of an opportunity. It would be too unhealthy if any one company took all of it.”
Founded in 2019, D-Matrix plans to release a semiconductor card for servers later this year that aims to reduce the cost and latency of running AI models. The company raised $110 million in September.
In addition to D-Matrix, companies ranging from multinational corporations to nascent startups are fighting for a slice of the AI chip market that could reach $400 billion in annual sales in the next five years, according to market analysts and AMD. Nvidia has generated about $80 billion in revenue over the past four quarters, and Bank of America estimates the company sold $34.5 billion in AI chips last year.
Many companies taking on Nvidia’s GPUs are betting that a different architecture or certain trade-offs could produce a better chip for particular tasks. Device makers are also developing technology that could end up doing a lot of the computing for AI that’s currently taking place in large GPU-based clusters in the cloud.
“Nobody can deny that today Nvidia is the hardware you want to train and run AI models,” Fernando Vidal, co-founder of 3Fourteen Research, told CNBC. “But there’s been incremental progress in leveling the playing field, from hyperscalers working on their own chips, to even little startups, designing their own silicon.”
AMD CEO Lisa Su wants investors to believe there’s plenty of room for many successful companies in the space.
“The key is that there are a lot of options there,” Su told reporters in December, when her company launched its most recent AI chip. “I think we’re going to see a situation where there’s not only one solution, there will be multiple solutions.”
Other big chipmakers
Lisa Su displays an AMD Instinct MI300 chip as she delivers a keynote address at CES 2023 in Las Vegas, Nevada, on Jan. 4, 2023.
David Becker | Getty Images
AMD makes GPUs for gaming and, like Nvidia, is adapting them for AI inside of data centers. Its flagship chip is the Instinct MI300X. Microsoft has already bought AMD processors, offering access to them through its Azure cloud.
At launch, Su highlighted the chip’s excellence at inference, as opposed to competing with Nvidia for training. Last week, Microsoft said it was using AMD Instinct GPUs to serve its Copilot models. Morgan Stanley analysts took the news as a sign that AMD’s AI chip sales could surpass $4 billion this year, the company’s public target.
Intel, which was surpassed by Nvidia last year in terms of revenue, is also trying to establish a presence in AI. The company recently announced the third version of its AI accelerator, Gaudi 3. This time Intel compared it directly to the competition, describing it as a more cost-effective alternative and better than Nvidia’s H100 in terms of running inference, while faster at training models.
Bank of America analysts estimated recently that Intel will have less than 1% of the AI chip market this year. Intel says it has a $2 billion order of backlogs for the chip.
The main roadblock to broader adoption may be software. AMD and Intel are both participating in a big industry group called the UXL foundation, which includes Google, that’s working to create free alternatives to Nvidia’s CUDA for controlling hardware for AI applications.
Nvidia’s top customers
One potential challenge for Nvidia is that it’s competing against some of its biggest customers. Cloud providers including Google, Microsoft and Amazon are all building processors for internal use. The Big Tech three, plus Oracle, make up over 40% of Nvidia’s revenue.
Amazon introduced its own AI-oriented chips in 2018, under the Inferentia brand name. Inferentia is now on its second version. In 2021, Amazon Web Services debuted Tranium targeted to training. Customers can’t buy the chips but they can rent systems through AWS, which markets the chips as more cost efficient than Nvidia’s.
Google is perhaps the cloud provider most committed to its own silicon. The company has been using what it calls Tensor Processing Units (TPUs) since 2015 to train and deploy AI models. In May, Google announced the sixth version of its chip, Trillium, which the company said was used to develop its models, including Gemini and Imagen.
Google also uses Nvidia chips and offers them through its cloud.
Microsoft isn’t as far along. The company said last year that it was building its own AI accelerator and processor, called Maia and Cobalt.
Meta isn’t a cloud provider, but the company needs massive amounts of computing power to run its software and website and to serve ads. While the Facebook parent company is buying billions of dollars worth of Nvidia processors, it said in April that some of its homegrown chips were already in data centers and enabled “greater efficiency” compared to GPUs.
JPMorgan analysts estimated in May that the market for building custom chips for big cloud providers could be worth as much as $30 billion, with potential growth of 20% per year.
Startups
Cerebras’ WSE-3 chip is one example of new silicon from upstarts designed to run and train artificial intelligence.
Cerebras Systems
Venture capitalists see opportunities for emerging companies to jump into the game. They invested $6 billion in AI semiconductor companies in 2023, up slightly from $5.7 billion a year earlier, according to data from PitchBook.
It’s a tough area for startups as semiconductors are expensive to design, develop and manufacture. But there are opportunities for differentiation.
For Cerebras Systems, an AI chipmaker in Silicon Valley, the focus is on basic operations and bottlenecks for AI, versus the more general purpose nature of a GPU. The company was founded in 2015 and was valued at $4 billion during its most recent fundraising, according to Bloomberg.
The Cerebras chip, WSE-2, puts GPU capabilities as well as central processing and additional memory into a single device, which is better for training large models, said CEO Andrew Feldman.
“We use a giant chip, they use a lot of little chips,” Feldman said. “They’ve got challenges of moving data around, we don’t.”
Feldman said his company, which counts Mayo Clinic, GlaxoSmithKline, and the U.S. Military as clients, is winning business for its supercomputing systems even going up against Nvidia.
“There’s ample competition and I think that’s healthy for the ecosystem,” Feldman said.
Sheth from D-Matrix said his company plans to release a card with its chiplet later this year that will allow for more computation in memory, as opposed to on a chip like a GPU. D-Matrix’s product can be slotted into an AI server along existing GPUs, but it takes work off of Nvidia chips, and helps to lower the cost of generative AI.
Customers “are very receptive and very incentivized to enable a new solution to come to market,” Sheth said.
Apple and Qualcomm
Apple iPhone 15 series devices are displayed for sale at The Grove Apple retail store on release day in Los Angeles, California, on September 22, 2023.
Patrick T. Fallon | Afp | Getty Images
The biggest threat to Nvidia’s data center business may be a change in where processing happens.
Developers are increasingly betting that AI work will move from server farms to the laptops, PCs and phones we own.
Big models like the ones developed by OpenAI require massive clusters of powerful GPUs for inference, but companies like Apple and Microsoft are developing “small models” that require less power and data and can run on a battery-powered device. They may not be as skilled as the latest version of ChatGPT, but there are other applications they perform, such as summarizing text or visual search.
Apple and Qualcomm are updating their chips to run AI more efficiently, adding specialized sections for AI models called neural processors, which can have privacy and speed advantages.
Qualcomm recently announced a PC chip that will allow laptops to run Microsoft AI services on the device. The company has also invested in a number of chipmakers making lower-power processors to run AI algorithms outside of a smartphone or laptop.
Apple has been marketing its latest laptops and tablets as optimized for AI because of the neural engine on its chips. At its upcoming developer conference, Apple is planning to show off a slew of new AI features, likely running on the company’s iPhone-powering silicon.
Hidden among the majestic canyons of the Utah desert, about 7 miles from the nearest town, is a small research facility meant to prepare humans for life on Mars.
The Mars Society, a nonprofit organization that runs the Mars Desert Research Station, or MDRS, invited CNBC to shadow one of its analog crews on a recent mission.
“MDRS is the best analog astronaut environment,” said Urban Koi, who served as health and safety officer for Crew 315. “The terrain is extremely similar to the Mars terrain and the protocols, research, science and engineering that occurs here is very similar to what we would do if we were to travel to Mars.”
SpaceX CEO and Mars advocate Elon Musk has said his company can get humans to Mars as early as 2029.
The 5-person Crew 315 spent two weeks living at the research station following the same procedures that they would on Mars.
David Laude, who served as the crew’s commander, described a typical day.
“So we all gather around by 7 a.m. around a common table in the upper deck and we have breakfast,” he said. “Around 8:00 we have our first meeting of the day where we plan out the day. And then in the morning, we usually have an EVA of two or three people and usually another one in the afternoon.”
An EVA refers to extravehicular activity. In NASA speak, EVAs refer to spacewalks, when astronauts leave the pressurized space station and must wear spacesuits to survive in space.
“I think the most challenging thing about these analog missions is just getting into a rhythm. … Although here the risk is lower, on Mars performing those daily tasks are what keeps us alive,” said Michael Andrews, the engineer for Crew 315.
Formula One F1 – United States Grand Prix – Circuit of the Americas, Austin, Texas, U.S. – October 23, 2022 Tim Cook waves the chequered flag to the race winner Red Bull’s Max Verstappen
Mike Segar | Reuters
Apple had two major launches last month. They couldn’t have been more different.
First, Apple revealed some of the artificial intelligence advancements it had been working on in the past year when it released developer versions of its operating systems to muted applause at its annual developer’s conference, WWDC. Then, at the end of the month, Apple hit the red carpet as its first true blockbuster movie, “F1,” debuted to over $155 million — and glowing reviews — in its first weekend.
While “F1” was a victory lap for Apple, highlighting the strength of its long-term outlook, the growth of its services business and its ability to tap into culture, Wall Street’s reaction to the company’s AI announcements at WWDC suggest there’s some trouble underneath the hood.
“F1” showed Apple at its best — in particular, its ability to invest in new, long-term projects. When Apple TV+ launched in 2019, it had only a handful of original shows and one movie, a film festival darling called “Hala” that didn’t even share its box office revenue.
Despite Apple TV+being written off as a costly side-project, Apple stuck with its plan over the years, expanding its staff and operation in Culver City, California. That allowed the company to build up Hollywood connections, especially for TV shows, and build an entertainment track record. Now, an Apple Original can lead the box office on a summer weekend, the prime season for blockbuster films.
The success of “F1” also highlights Apple’s significant marketing machine and ability to get big-name talent to appear with its leadership. Apple pulled out all the stops to market the movie, including using its Wallet app to send a push notification with a discount for tickets to the film. To promote “F1,” Cook appeared with movie star Brad Pitt at an Apple store in New York and posted a video with actual F1 racer Lewis Hamilton, who was one of the film’s producers.
(L-R) Brad Pitt, Lewis Hamilton, Tim Cook, and Damson Idris attend the World Premiere of “F1: The Movie” in Times Square on June 16, 2025 in New York City.
Jamie Mccarthy | Getty Images Entertainment | Getty Images
Although Apple services chief Eddy Cue said in a recent interview that Apple needs the its film business to be profitable to “continue to do great things,” “F1” isn’t just about the bottom line for the company.
Apple’s Hollywood productions are perhaps the most prominent face of the company’s services business, a profit engine that has been an investor favorite since the iPhone maker started highlighting the division in 2016.
Films will only ever be a small fraction of the services unit, which also includes payments, iCloud subscriptions, magazine bundles, Apple Music, game bundles, warranties, fees related to digital payments and ad sales. Plus, even the biggest box office smashes would be small on Apple’s scale — the company does over $1 billion in sales on average every day.
But movies are the only services component that can get celebrities like Pitt or George Clooney to appear next to an Apple logo — and the success of “F1” means that Apple could do more big popcorn films in the future.
“Nothing breeds success or inspires future investment like a current success,” said Comscore senior media analyst Paul Dergarabedian.
But if “F1” is a sign that Apple’s services business is in full throttle, the company’s AI struggles are a “check engine” light that won’t turn off.
Replacing Siri’s engine
At WWDC last month, Wall Street was eager to hear about the company’s plans for Apple Intelligence, its suite of AI features that it first revealed in 2024. Apple Intelligence, which is a key tenet of the company’s hardware products, had a rollout marred by delays and underwhelming features.
Apple spent most of WWDC going over smaller machine learning features, but did not reveal what investors and consumers increasingly want: A sophisticated Siri that can converse fluidly and get stuff done, like making a restaurant reservation. In the age of OpenAI’s ChatGPT, Anthropic’s Claude and Google’s Gemini, the expectation of AI assistants among consumers is growing beyond “Siri, how’s the weather?”
The company had previewed a significantly improved Siri in the summer of 2024, but earlier this year, those features were delayed to sometime in 2026. At WWDC, Apple didn’t offer any updates about the improved Siri beyond that the company was “continuing its work to deliver” the features in the “coming year.” Some observers reduced their expectations for Apple’s AI after the conference.
“Current expectations for Apple Intelligence to kickstart a super upgrade cycle are too high, in our view,” wrote Jefferies analysts this week.
Siri should be an example of how Apple’s ability to improve products and projects over the long-term makes it tough to compete with.
It beat nearly every other voice assistant to market when it first debuted on iPhones in 2011. Fourteen years later, Siri remains essentially the same one-off, rigid, question-and-answer system that struggles with open-ended questions and dates, even after the invention in recent years of sophisticated voice bots based on generative AI technology that can hold a conversation.
Apple’s strongest rivals, including Android parent Google, have done way more to integrate sophisticated AI assistants into their devices than Apple has. And Google doesn’t have the same reflex against collecting data and cloud processing as privacy-obsessed Apple.
Some analysts have said they believe Apple has a few years before the company’s lack of competitive AI features will start to show up in device sales, given the company’s large installed base and high customer loyalty. But Apple can’t get lapped before it re-enters the race, and its former design guru Jony Ive is now working on new hardware with OpenAI, ramping up the pressure in Cupertino.
“The three-year problem, which is within an investment time frame, is that Android is racing ahead,” Needham senior internet analyst Laura Martin said on CNBC this week.
Apple’s services success with projects like “F1” is an example of what the company can do when it sets clear goals in public and then executes them over extended time-frames.
Its AI strategy could use a similar long-term plan, as customers and investors wonder when Apple will fully embrace the technology that has captivated Silicon Valley.
Wall Street’s anxiety over Apple’s AI struggles was evident this week after Bloomberg reported that Apple was considering replacing Siri’s engine with Anthropic or OpenAI’s technology, as opposed to its own foundation models.
The move, if it were to happen, would contradict one of Apple’s most important strategies in the Cook era: Apple wants to own its core technologies, like the touchscreen, processor, modem and maps software, not buy them from suppliers.
Using external technology would be an admission that Apple Foundation Models aren’t good enough yet for what the company wants to do with Siri.
“They’ve fallen farther and farther behind, and they need to supercharge their generative AI efforts” Martin said. “They can’t do that internally.”
Apple might even pay billions for the use of Anthropic’s AI software, according to the Bloombergreport. If Apple were to pay for AI, it would be a reversal from current services deals, like the search deal with Alphabet where the Cupertino company gets paid $20 billion per year to push iPhone traffic to Google Search.
The company didn’t confirm the report and declined comment, but Wall Street welcomed the report and Apple shares rose.
In the world of AI in Silicon Valley, signing bonuses for the kinds of engineers that can develop new models can range up to $100 million, according to OpenAI CEO Sam Altman.
“I can’t see Apple doing that,” Martin said.
Earlier this week, Meta CEO Mark Zuckerberg sent a memo bragging about hiring 11 AI experts from companies such as OpenAI, Anthropic, and Google’s DeepMind. That came after Zuckerberg hired Scale AI CEO Alexandr Wang to lead a new AI division as part of a $14.3 billion deal.
Meta’s not the only company to spend hundreds of millions on AI celebrities to get them in the building. Google spent big to hire away the founders of Character.AI, Microsoft got its AI leader by striking a deal with Inflection and Amazon hired the executive team of Adept to bulk up its AI roster.
Apple, on the other hand, hasn’t announced any big AI hires in recent years. While Cook rubs shoulders with Pitt, the actual race may be passing Apple by.
Tesla CEO Elon Musk speaks alongside U.S. President Donald Trump to reporters in the Oval Office of the White House on May 30, 2025 in Washington, DC.
Kevin Dietsch | Getty Images
Tesla CEO Elon Musk, who bombarded President Donald Trump‘s signature spending bill for weeks, on Friday made his first comments since the legislation passed.
Musk backed a post on X by Sen. Rand Paul, R-Ky., who said the bill’s budget “explodes the deficit” and continues a pattern of “short-term politicking over long-term sustainability.”
The House of Representatives narrowly passed the One Big Beautiful Bill Act on Thursday, sending it to Trump to sign into law.
Paul and Musk have been vocal opponents of Trump’s tax and spending bill, and repeatedly called out the potential for the spending package to increase the national debt.
The independent Congressional Budget Office has said the bill could add $3.4 trillion to the $36.2 trillion of U.S. debt over the next decade. The White House has labeled the agency as “partisan” and continuously refuted the CBO’s estimates.
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The bill includes trillions of dollars in tax cuts, increased spending for immigration enforcement and large cuts to funding for Medicaid and other programs.
It also cuts tax credits and support for solar and wind energy and electric vehicles, a particularly sore spot for Musk, who has several companies that benefit from the programs.
“I took away his EV Mandate that forced everyone to buy Electric Cars that nobody else wanted (that he knew for months I was going to do!), and he just went CRAZY!” Trump wrote in a social media post in early June as the pair traded insults and threats.
Shares of Tesla plummeted as the feud intensified, with the company losing $152 billion in market cap on June 5 and putting the company below $1 trillion in value. The stock has largely rebounded since, but is still below where it was trading before the ruckus with Trump.
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Tesla one-month stock chart.
— CNBC’s Kevin Breuninger and Erin Doherty contributed to this article.