The efficiency and speed of automating workflows with artificial intelligence (AI) agents have triggered a massive surge in enterprise spending in 2026. Morgan Stanley expects new global data center construction costs to total nearly $3 trillion through 2028.
If the AI data center build-out is still in the early innings, investors could potentially build tremendous wealth with leading AI companies over the next 20 years. Here's why Arm Holdings (ARM 3.87%), IREN (IREN 0.78%), and Nvidia (NVDA 1.42%) are excellent candidates.
Image source: Getty Images.
1. Arm Holdings Arm is one of the leading chip designers. Its architecture is found in virtually every smartphone, and it has a huge opportunity to supply core technology for data centers.
The latest results show why the stock is surging higher in 2026. Revenue hit a record $1.49 billion last quarter, up 20% year over year. An attractive feature of the business is that it earns royalties on every chip shipped using its architecture, making Arm highly profitable.
Demand for Arm's energy-efficient chips should continue to grow as AI models become smarter, requiring more compute capacity, which is already in short supply. Leading tech companies, including some of the "Magnificent Seven," are using Arm-based chips in their AI compute systems.
Management expects Arm to hold the largest share of data center central processing units (CPUs) by the end of the decade, driven by its superior energy efficiency and rising core counts in new CPU designs. That should lift data center royalty revenue, which is on pace to double again over the next year.
Top semiconductor companies already trade at trillion-plus market caps -- but not Arm. It looks expensive on a price-to-earnings basis, but given the growing demand for Arm-based chips, it seems on course to eventually join the trillion-dollar club. Its current $380 billion market cap looks modest compared with what it may be worth in the coming decades, as data centers grow and use more chips to handle future AI workloads.
Today's Change
(
-0.78
%) $
-0.37
Current Price
$
47.37
2. IREN Growing AI adoption is creating a shortage in data center capacity. IREN is emerging as one of the best-in-class data center builders. The stock has soared 385% over the past year, yet it still trades at a relatively low market cap of about $18 billion. For a company with a growing portfolio of 5 gigawatts of grid-connected power, that valuation may undervalue its long-term growth in an AI-driven economy.
IREN has already signed two long-term cloud contracts with Microsoft and Nvidia. It's on track to bring 480 megawatts of new capacity online this year, and management expects to finish 2026 with $4.4 billion in annualized revenue.
It's also planning data centers in Spain and Australia, showing expansion potential beyond North America. The company's market cap seems to fairly value the multibillion-dollar contracts with Microsoft and Nvidia but is placing no value on its future data center pipeline, especially overseas.
In a world short on compute, IREN's power portfolio could become more valuable over time. Management is developing a blueprint for repeatable, fast processes to build new data centers. It does everything in-house, including construction and design. It's expected to have over 1.2 gigawatts of its power portfolio online in 2027, and management anticipates this accelerating over time.
Today's Change
(
-1.42
%) $
-2.77
Current Price
$
192.97
3. Nvidia As investors pursue opportunities in CPUs, XPUs, and memory, Nvidia's valuation has compressed, creating an attractive entry point for a new investment. Its data center revenue nearly doubled last quarter, as shipments of its chip systems remain robust, and the upcoming Vera Rubin platform points to continued momentum.
CEO Jensen Huang is a visionary leader worth backing. Just nine years ago, gaming GPUs drove most of Nvidia's revenue. Huang's ability to identify new markets where GPUs matter is a core reason to buy and hold the stock for the long haul.
Case in point: Nvidia's growing CPU business. The new Vera CPUs are on track to reach $20 billion in revenue this year, more than a third of Intel's revenue. Demand is expected to be robust for Nvidia's next-generation Vera Rubin platform, which uses multiple chip types to power agentic AI workloads. This is a key catalyst for growth heading into next year, with analysts expecting total revenue to rise 81% this year to $391 billion.
The chip industry is fiercely competitive, so Nvidia has to stay on the cutting edge to keep growing. But it has the leadership and significant resources to be a leading AI hardware supplier for the long term, yet the stock trades at just 22 times this year's earnings estimate.
Quantum computing is still in its early innings, but if the technology reaches the potential that some see for it, the industry could mint many millionaires among its investors. Grand View Research projects that the quantum computing market will grow at a 22.3% compound annual rate through 2033, and Infleqtion (INFQ +6.57%) may be one of the best ways to get exposure to this opportunity.
Its partnership with Nvidia shows that Infleqtion is a serious player Like most quantum computing pure plays, Infleqtion doesn't have much revenue to support its multibillion-dollar market cap. The company's top line was only $9.5 million in the first quarter, and it booked more than $30 million in net losses.
Today's Change
(
6.57
%) $
0.84
Current Price
$
13.63
The company is developing quantum computers that should be able to solve highly complex problems that classical computers can't. Infleqtion has partnered with Nvidia (NVDA 1.42%) to integrate its neutral-atom quantum processing units with the tech giant's hardware and software, with the goal of driving the next era of high-performance computing.
That partnership strengthens Infleqtion's reputation while also giving it access to more talent and capital. The combined technology will also be more convenient for AI data center operators to make use of, since it bridges quantum computing technology with the GPUs they already use, and therefore won't require a major overhaul.
In other words, it will be easier to integrate Infleqtion's offerings into established AI infrastructure than the technologies of many of its competitors.
The development of quantum computing is accelerating It's not just tech companies that are spearheading the push to quantum computing with investments and initiatives. The Trump administration recently issued an executive order for the government to develop policies that could accelerate quantum computing development in America.
"The United States must take a cohesive, whole-of-government approach to accelerate deployment and commercialization of quantum computing, sensing, and networking," President Donald Trump wrote.
Infleqtion already has a good relationship with the government. It was recently selected by the U.S. Department of Commerce for $100 million in proposed funding to advance quantum computing. As Washington ramps up its investments in the technology, there is a good chance more of that capital will flow into Infleqtion's coffers. The day after Trump's announcement, French President Emmanuel Macron announced that France would make similar investments in that nation's quantum computing efforts. Clearly, the quantum race is starting to heat up.
"Infleqtion has one of the industry's broadest quantum technology portfolios, spanning quantum computing, advanced sensing, and space-based quantum systems," the company said in a press release that covered the executive order.
Quantum computing will have many applications, and it's even expected to be part of the space economy. Infleqtion is one of the early leaders on that front: It was a key contributor to the launch of America's Quantum Space Initiative. That private sector initiative is designed to "help advance the development and deployment of quantum technologies for future space systems."
Infleqtion may still be burning through cash, but it's in the right business at the right time. Government funding and an Nvidia partnership are just two of the catalysts that could help Infleqtion gain market share rapidly once it can develop its quantum computing technology to the point where it can be commercialized.
Nvidia (NVDA 1.42%) makes the chips behind most of the artificial intelligence (AI) build-out, and the payoff for its shareholders has been enormous. But lately a new worry has surfaced: What if AI spending is near its peak? That question has pushed the stock down about 18% from its mid-May high as of this writing, even as Nvidia's business keeps accelerating.
Given this backdrop, it's a good time to tune out the near-term noise and focus on the long-term. So, where could the stock realistically be in 2030?
Unfortunately, the possible outcomes are wide -- not just because of the unpredictable nature of its business in a fast-changing industry, but also because of its stock's premium valuation. Nvidia could keep executing at full speed and still deliver only ordinary returns to investors from here. Or AI spending could prove more durable than skeptics expect, letting the company grow into and beyond today's price.
Both outcomes are plausible.
Image source: Nvidia.
The bull case: demand is still booming Demand certainly isn't a problem. And this is great news for investors, because the entire bull case rests on it.
Nvidia's most recent quarter showed no sign of a slowdown. In its fiscal first quarter of 2027 (the period ended April 26, 2026), revenue rose 85% year over year to $81.6 billion, and its AI-focused data center segment grew 92% to $75.2 billion.
Additionally, management guided for about $91 billion in revenue for fiscal Q2.
"The buildout of AI factories -- the largest infrastructure expansion in human history -- is accelerating at extraordinary speed," said Nvidia founder and CEO Jensen Huang in the company's fiscal first-quarter earnings release.
The spending behind that demand is staggering. Amazon, Microsoft, Alphabet, and Meta Platforms are together on track to spend about $725 billion on capital projects in 2026 -- up about 77% from last year, with most of it pointed at AI infrastructure.
Of course, not all of those dollars flow to Nvidia. But graphics processing units (GPUs) remain a central piece of the build-out, and Nvidia still supplies the large majority of them.
A fresh product cycle is coming, too. Nvidia's next-generation Vera Rubin platform is due from partners in the second half of 2026. If this build-out turns out to be a multiyear shift rather than a one-time surge, Nvidia can keep growing well into 2030.
Today's Change
(
-1.42
%) $
-2.77
Current Price
$
192.97
The bear case: a peak, and rising competition But here is where the bears have a point worth taking seriously.
That $725 billion is increasingly funded with debt (and, in some cases, equity, which dilutes shareholders), and free cash flow is under pressure and, for some of these customers, may even turn negative as they spend. So, spending at this pace may not keep accelerating, and when it slows, Nvidia's growth would likely slow with it.
The chip business has always moved in cycles, and there's little reason to think this one won't.
Competition is the other pressure point.
Nvidia's biggest customers are also its emerging rivals. Alphabet, Amazon, Microsoft, and Meta are all designing in-house chips to cut their dependence on Nvidia and lower the cost of AI computing -- and Amazon- and Google-built silicon already powers large workloads at AI developers like Anthropic. Advanced Micro Devices is pushing its own accelerators as well.
Of course, Nvidia is still the dominant player. But over several years, credible alternatives could erode its pricing power -- and Nvidia's roughly 75% gross margin sits far above a typical chipmaker's. If that margin narrows while growth cools, Nvidia's financial results could disappoint on two fronts at once.
The one thing working in the stock's favor is that the valuation has already come down. Nvidia trades at about 30 times earnings -- well below the 40-plus multiple it carried for much of the past two years. Clearly, there's some unease about when the cycle may peak already priced into the stock.
So, where does that leave the stock in 2030?
Nvidia is very likely to be a larger and more profitable business by then. But the range of outcomes for the stock is unusually wide. If the build-out keeps running and margins hold, the shares could compound at a high-single-digit to low-double-digit annual rate -- which from about $193 today would put them somewhere in the high-$200s to low-$300s by 2030. If AI spending peaks within a year or two and competition softens pricing, the stock could spend years going nowhere, even as revenue grows.
Given the stock's more reasonable valuation multiple today and the extraordinary underlying business momentum, I'm personally leaning modestly toward the optimistic side of that range.
Nvidia (NASDAQ: NVDA), the biggest beneficiary of the artificial intelligence boom, closed the Friday session with a market capitalization of approximately $4.663 trillion.
As investors speculate about which company could become the first to reach a $10 trillion valuation, Finbold consulted ChatGPT to estimate when Nvidia might achieve the milestone.
Based on its current valuation, the semiconductor giant would need to increase its market capitalization by about 114.5% to reach $10 trillion.
NVDA one-week stock price chart. Source: Finbold After analyzing the company’s revenue growth, Wall Street forecasts, AI infrastructure spending trends, and product roadmap, ChatGPT projected that Nvidia is most likely to hit the $10 trillion mark between 2029 and 2031.
Nvidia stock fundamentals Notably, Nvidia’s growth continues to be fueled by heavy investment in AI infrastructure. The company reported quarterly revenue of $81.6 billion, up roughly 85% year-over-year, with its data center business remaining the main growth driver.
Meanwhile, Microsoft, Amazon, Meta Platforms, and Alphabet continue investing billions in AI infrastructure, sustaining demand for Nvidia’s products.
Analysts increasingly view this spending cycle as a long-term trend, while strong demand for the Blackwell platform and growing interest in the upcoming Vera Rubin architecture provide additional growth catalysts.
According to ChatGPT’s analysis, the most bullish scenario would see Nvidia reach a $10 trillion valuation as early as late 2027 or 2028, supported by sustained growth, successful Blackwell deployment, strong margins, and continued AI-driven demand.
Analyst forecasts project Nvidia’s annual revenue to increase from about $216 billion in its last fiscal year to nearly $392 billion in fiscal 2027 and around $552 billion in fiscal 2028.
Ideal timeline for Nvidia hitting $10 trillion market cap However, ChatGPT considers 2029 to 2031 the most likely timeframe, estimating that reaching a $10 trillion valuation would require annual revenue of $700 billion to $1 trillion alongside continued leadership in AI chips, networking infrastructure, and enterprise AI.
The timeline also depends on valuation growth. At 20% annual market cap growth, Nvidia would reach $10 trillion in about 4.2 years, compared to 3.4 years at 25%, 2.9 years at 30%, and 2.1 years at 40%.
NVDA market cap prediction. Source: ChatGPT. However, ChatGPT noted several risks, including U.S. export restrictions on China, growing competition from AMD and custom AI chips, and the possibility of slowing AI infrastructure spending, all of which could delay Nvidia’s path to $10 trillion.
You've almost certainly heard the term "smart money," usually in reference to Wall Street's most proven investment managers. This label isn't necessarily limited to money managers, though. Any organization that picks stocks can be "smart" for any number of reasons, including its sheer expertise on a particular topic or industry.
Enter Nvidia (NVDA 1.42%). It's clearly a leading expert on artificial intelligence (AI), having manufactured the computing processors at the heart of most AI platforms (not to mention partnering with other technology companies to improve these systems). If this company invests in a particular AI stock, it's a pretty big deal.
With that as the backdrop, know that Nvidia -- through its venture capital arm NVentures -- now owns 833,325 shares of a small biotechnology company called Generate Biomedicines (GENB +0.30%). Here's the deal.
Image source: Getty Images.
What's Generate Biomedicines? With a market cap of only $2 billion and no significant revenue yet, this pre-profit company isn't exactly a household name. You've probably never even heard of it, in fact.
But that's not the point. Neither is the fact that Nvidia's $13 million stake in the up-and-coming company is practically nothing compared to its current $80 billion war chest. The point is, Nvidia has heard of it -- and likes it enough to take a position.
Then again, Nvidia has a (very) in-depth understanding of this company's business.
Generate Biomedicines isn't a biotechnology outfit in the usual sense of the word. It's actually the developer of an AI platform that digitally tests how a prospective drug molecule might perform as a treatment for a particular disease.
Today's Change
(
0.30
%) $
0.05
Current Price
$
16.47
And it's no mere theoretical idea. The platform is up and running, launching the development of real drugs in real clinical trials. As of the latest update, four drug candidates are in Generate Biomedicines' pipeline, with one in phase 3 testing. That's GB-0895, for the treatment of severe asthma.
Of course, there's no limit to the number of such tests the company's technology can perform, whether with a partner or on its own. It and its drugmaking partners just need to come up with worthy ideas to test.
Creating a massive opportunity To be clear, this AI-powered testing isn't a replacement for actual clinical testing; the United States' FDA and other countries' regulatory bodies still require proof that a drug is safe and effective to use in a real-world setting.
Generate Biomedicines' technology addresses two of the pharmaceutical industry's chief challenges, though: wasted time and wasted money.
Only about one in 10 drugs that begin clinical trials are approved. And that still understates the ultimate failure rate. See, even fewer drug hopefuls move past the preclinical development stage when there's little to no evidence of efficacy realized or when safety concerns surface.
All this work still requires significant resources, though, particularly clinical trials. Numbers compiled by Thermo Fisher Scientific's drug-manufacturing division, Patheon Pharma Services, indicate it can take between 10 and 15 years and $2.6 billion to bring one new approved medicine to market. It costs about the same, of course, even if a drug makes it to and through phase 3 trials only to end up not being approved; dial back the figure accordingly for developmental efforts that are abandoned in phase 1 and phase 2 clinical testing stages.
The real travesty? It's arguably the potentially game-changing drugs that never even begin development in the first place, out of fear that precious resources may be wasted on them that could have been devoted to more promising prospects.
Generate Biomedicines' AI-powered platform dramatically reduces this risk by giving pharmaceutical developers a clear, virtual sense of what's likely to happen between a drug and a disease in an actual clinical trial. Although the numbers vary somewhat, studies on this matter generally indicate that AI-discovered drugs are about twice as likely to succeed in phase 1 trials as drugs that begin clinical trials without prior virtual testing. That's huge. Indeed, it's so huge that AI-powered drug development is likely to change how the entire $1.8 trillion pharmaceutical market constantly renews its drug portfolios.
If it's good enough for Nvidia... Generate Biomedicines isn't the only name in this budding business, for the record. It competes with Recursion Pharmaceuticals' (RXRX +5.24%) -- which is partnered with Sanofi and Roche -- Insilico Medicine, and Isomorphic Labs, which is a spinoff from Alphabet's Google's DeepMind that's already working with established pharma names like Eli Lilly and Novartis. Generate Biomedicines will need to fight for its share of the AI drug development market that Precedence Research expects to be worth $160 billion per year by 2035 (versus less than $20 billion last year).
But even a small fraction of this growth would be a windfall for Generate Biomedicines.
Perhaps more important right now, however, among the up-and-coming businesses Nvidia could have selected, it chose Generate Biomedicines, even though it's also collaborating with the aforementioned Recursion, while supplying Insilico with high-performance AI processors. That speaks volumes about what Nvidia sees in this company. Interested investors might want to take the subtle hint if they can stomach the risk and likely volatility.
The beating heart of the artificial intelligence (AI) boom is, without a doubt, Nvidia (NVDA 1.42%). The chipmaker's graphics processing units (GPUs) -- the specialized chips that do the heavy math behind AI -- power the data centers that train and run ChatGPT, Claude, and the vast majority of AI models.
It's no surprise, then, that Nvidia has managed a multiyear win streak nearly unmatched in the modern era. In its fiscal 2022, the company booked $26.9 billion in revenue. Over the last 12 months, it booked nearly 10 times that -- $253.5 billion.
The stock has followed suit, up more than 600% since January 2022.
Today's Change
(
-1.42
%) $
-2.77
Current Price
$
192.97
That kind of run can make an investor nervous. As unstoppable as Nvidia looks, there are real risks here, and most of them have been talked to death -- customer concentration, fierce competition, the physical limits of the AI build-out. But the one I think matters most still flies under the radar.
Nvidia's fortunes depend on big tech's spending spree The AI boom is being fueled, in large part, by the capital expenditures (capex) -- the money a company sinks into long-term assets like buildings and equipment -- of just a handful of firms. Big tech names like Meta, Alphabet, Amazon, Microsoft, and Oracle are spending on a scale we've never seen. Last year alone, these five shelled out a combined $412 billion -- well over twice the total just two years prior.
That capex is the lifeblood of the AI economy. It flows to the construction firms building the data centers, the neoclouds operating them, and, most critically, to chipmakers like Nvidia.
So if that spending slows, Nvidia is in trouble. That much is obvious. What's not obvious is why it might.
Why big tech's profits look better than they really are Investors have stomached the enormous spending these past few years for one simple reason: They've watched big tech's earnings grow right alongside it. You see earnings per share (EPS) -- a company's profit divided across its shares -- jump 100%, and you stop worrying about the bill. Why fret about spending when profits are exploding?
Here's the thing: There's a lag in the system, and that profit growth could soon look a lot smaller than it does today.
When Meta spends $50 billion on Nvidia chips, that doesn't hit the books as an expense all at once. It counts as capex, and Meta can spread the cost over time. Say, $10 billion a year for five years.
That's depreciation: spreading the cost of a big purchase across the years a company expects to use it. There's nothing shady about it. It's the same thing every business with trucks or factories has always done.
What's different is the scale and the timing. A company often doesn't start the depreciation clock until the equipment actually goes into service -- and given how long it takes to build an AI data center, that can be a long wait.
Image source: Nvidia.
The depreciation wall is coming We're in a stretch where revenue is climbing while the true cost of all those chips hasn't fully shown up in earnings yet -- a "golden window where everybody looks good," as one Morgan Stanley analyst put it. That period won't last. A wall of depreciation is coming, and when it lands, it could drag down big tech's reported earnings.
And that's when investors may start to care about the spending. Faced with shrinking earnings, the Metas and Amazons of the world could trim those massive capex plans. Fewer dollars spent means fewer chips ordered, and fewer chips is bad news for anyone holding Nvidia.
Nvidia's stock could fall before its sales do Now, bulls will tell you Nvidia's order book is booked solid -- CEO Jensen Huang says he expects a $1 trillion backlog by the end of the year -- so there's not a real risk to Nvidia's sales coming any time soon.
I don't discount that, but stock prices are based on where investors think things are headed. Which means that Nvidia shares can take a hit well before Nvidia's actual order book does. All that's required is for investors to believe big tech is likely to scale back in the coming years.
What investors should watch for The real questions are when this happens and how big the hit will be -- and, I'll be honest, no one knows. You can see the uncertainty in Wall Street's own forecasts. Analysts' revenue targets for big tech over the next few years are fairly tight. Their depreciation estimates are all over the map.
None of this makes Nvidia a bad company -- it's a great one, selling every chip it can make. But Nvidia relies on capex spending continuing to expand. That could slow once investors start to see the true cost of that spending show up in income statements. For my money, the depreciation wall is a big reason I'd think twice before buying Nvidia shares today.
Is Nvidia's (NVDA 1.42%) incredible run finally over? Since the company released its latest earnings report -- for the first quarter of its fiscal year 2027, ending April 26 -- on May 20, the stock has been trending south. Nvidia's market cap recently dipped below $5 trillion, after peaking at above $5.5 trillion earlier this year. However, despite the market's skepticism, there remain excellent reasons to invest in Nvidia, especially at current levels. Here's why the stock is a no-brainer buy on the dip.
Image source: The Motley Fool.
The bull case remains intact Nvidia's bears will point to increased competition in the GPU (Graphics Processing Unit) market, including from companies such as Cerebras Systems (CBRS +7.76%), which recently went public. Others will highlight that the hyperscalers -- Nvidia's biggest customers -- are increasingly relying on internally developed custom artificial intelligence (AI) chips, which could decrease their exposure to Nvidia's hardware. Some of them are even exploring selling their AI chips to other data centers, a move that will pit them directly against Nvidia.
These are reasonable concerns. However, several factors make Nvidia's prospects attractive despite these potential obstacles. First, Nvidia still reigns supreme in the GPU space, with a 94% market share, according to some estimates. Whatever the exact number, nobody denies that Nvidia has a runaway lead. Competitors aren't just facing a hardware problem when trying to knock Nvidia off its pedestal. The company's wide moat stems from its sticky CUDA ecosystem, which makes it difficult for customers to switch to competitors. Even seasoned semiconductor leaders like Advanced Micro Devices (AMD 1.48%) have made little progress in capturing market share from Nvidia.
Today's Change
(
-1.42
%) $
-2.77
Current Price
$
192.97
Further, the company is launching a new platform, Vera Rubin (Rubin is the GPU, while Vera is a CPU, or Central Processing Unit), that is even better than its previous Blackwell architecture. The Rubin GPU is expected to offer significantly better performance and cost efficiency than Blackwell. That will help Nvidia mitigate the threat from custom AI chips, since one of their appeals is that they offer better price-to-performance for specific workloads than comparable GPUs.
There is plenty of evidence that the hyperscalers will continue buying from Nvidia and will increase AI infrastructure spending in the next few years, at the very least. Amazon's (AMZN +2.44%) CEO, Andy Jassy, has explicitly said the company will remain a customer of Nvidia for the foreseeable future. Alphabet (GOOG 2.15%) (GOOGL 1.73%) plans to significantly increase capex spending next year, and recently put its money where its mouth is with a massive $80 billion equity offering to help fund its AI-related ambitions.
Finally, Nvidia is tapping into a new opportunity with the Vera CPU, as the shift to agentic AI will bring about increasing demand for CPUs. Nvidia thinks this market could be worth $200 billion. Here's the bottom line: Nvidia's AI-related tailwind is far from over. And over the next five years, the company could once again generate above-average returns, especially for investors who buy its shares on the dip.
Prosper Junior Bakiny has positions in Alphabet, Amazon, and Nvidia. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Amazon, and Nvidia. The Motley Fool has a disclosure policy.
Explore how these global equity funds differ in diversification, sector exposure, and portfolio size to help refine your international investing strategy.
On CNBC’s Closing Bell Overtime Thursday, the conversation circled back to the question every AI investor is now asking out loud. When do OpenAI and Anthropic stop pretending they want to stay private?
The reporters laid out a clock that is mostly running on revenue physics. Anthropic’s revenue is up roughly 4x from last year, while OpenAI’s run rate has doubled over the same period.
Per analyst Kate Luria, these growth rates are “the fastest right now that they will ever be.” Polymarket traders agree the window is opening. The crowd assigns a 77% probability to Anthropic going public by December 31, 2026, and a 23.5% probability to OpenAI listing by the same date. Public-market proxies are how most of you will trade this story for now.
Why the growth-rate clock is ticking Luria’s point is the whole game. A company with quadrupling revenue can sell a clean compounding narrative. However, a company growing 60% off a bigger base has to explain decel, and decel is where multiples die.
Anthropic confidentially filed its draft S-1 on June 1, 2026, shortly after a $65 billion funding round that valued it at $965 billion. Then, OpenAI followed with its own confidential S-1 on June 8, with underwriter targets near $1 trillion. Being first also matters in a way that is easy to miss. Whoever lists first sets the GAAP and accounting standards Wall Street analysts will use to evaluate the entire sector. Thus, it means the second mover spends its roadshow defending someone else’s definitions.
Moreover, OpenAI carries the added burden of being the bigger spender. OpenAI is to blame for $3.1 billion in investment losses flowing through Microsoft’s (NASDAQ:MSFT | MSFT Price Prediction) books in Q1 FY2026 alone.
The hyperscaler threat is also the hyperscaler trade PitchBook’s Harrison Rolfe flagged the obvious risk, noting Google (NASDAQ:GOOG), Microsoft, and Amazon (NASDAQ:AMZN) have the ability to “stiffarm and then undercut OpenAI and Anthropic on price.” The same firms are also the cleanest way to own the buildout.
Microsoft owns 27% of OpenAI in a stake valued near $135 billion. Furthermore, OpenAI is contractually on the hook for $250 billion in incremental Azure services. Satya Nadella told investors the AI business surpassed a $37 billion annual revenue run rate, up 123% year-over-year in the most recent 10-Q.
Unfortunately, MSFT the stock is down 22% year to date. Retail traders on Reddit openly debating whether “Satya and Zuckerberg are incinerating [more] capital.”
Amazon booked $16.8 billion in pre-tax gains from its Anthropic stake in Q1 2026 and guided to roughly $200 billion in capex this year. Alphabet co-invests in Anthropic while running Gemini against it. This is a posture that helps explain why Cloud backlog crossed $460 billion. NVIDIA (NASDAQ:NVDA) sells picks and shovels to all of them, with Data Center revenue of $75.25 billion, up 92% year-over-year.
Retail access and the SpaceX warning The host on Thursday’s segment drew a parallel that should make anyone chasing the IPO pop pause. SpaceX’s offering “was super aggressive” on valuation and has “kind of flatlined since.” Both OpenAI and Anthropic are reportedly reserving allocations for retail investors, but replicating “the Musk effect is obviously its own thing” for Sam Altman and Dario Amodei.
That puts Webull (NASDAQ:BULL) and similar retail venues in an interesting spot. Webull launched single-company SPVs through Monark Markets in June for accredited investors who want pre-IPO exposure, and the FINRA pattern-day-trader rule change took effect June 4, 2026. The stock is still down 19% year to date.
The forcing function here is competitive rather than financial. Both companies have the cash they need. What they lack is the willingness to let the other file first. The timing of these filings will set the comparable multiples for every private AI lab still raising at venture rounds.
If Anthropic prices first on a quadrupling revenue narrative, every Series E pitch deck in the Valley resets to that bar. If OpenAI prices first with the larger absolute revenue figure and the heavier capex commitment, the conversation shifts to scale economics and the durability of the Microsoft relationship. Either way, the public comps that matter most are already trading.
Watch the prospectus amendments through the fall, and watch whether Polymarket’s probability of no OpenAI IPO by year-end starts compressing as bankers leak timelines into August earnings calls. Watch the hyperscaler capex commentary on the next round of prints, because any softening in Microsoft’s or Amazon’s 2027 capex framing would give the IPO bears their first real data point.
Nvidia has dominated the AI chip market for years, but the era of total dependence might be ending.
OpenAI just shared its plans to spice things up with Jalapeño, its custom inference chip built with Broadcom, joining Google, Apple, and SpaceX in a growing list of companies building their way out of single-supplier risk. The goal is less of a clean break and more of a hedge. Custom silicon means more control, hardware tuned to specific needs, and the kind of performance gains Apple unlocked when it ditched Intel.
On this episode of TechCrunch’s Equity podcast, hosts Kirsten Korosec, Anthony Ha, and Sean O’Kane dig into what the custom chip trend means for the industry and a few deals of the week worth watching.
Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod.
Topics
a24, agility, AI, AI, AI chips, AI loops, Anthropic, custom silicon, Equity Video, groq, humanoid robots, nvidia, OpenAI, SPAC
Theresa Loconsolo is an audio producer at TechCrunch focusing on Equity, the network’s flagship podcast. Before joining TechCrunch in 2022, she was one of 2 producers at a four-station conglomerate where she wrote, recorded, voiced and edited content, and engineered live performances and interviews from guests like lovelytheband. Theresa is based in New Jersey and holds a bachelors degree in Communication from Monmouth University.
You can contact or verify outreach from Theresa by emailing [email protected].
With the latest dip in the tech sector, several top growth stocks have fallen back to lows from two months ago. With nothing fundamentally changing with their long-term stories, this could be a great buying opportunity.
Let's look at three top growth stocks to buy while they are at multi-month lows.
1. Nvidia Even the king of AI infrastructure, Nvidia (NVDA 0.61%), has been caught up in the most recent tech pullback. This recent dip has left it at a very attractive valuation with a forward price-to-earnings ratio (P/E) of below 16 times fiscal 2028 (ending January 2028) analyst estimates. That's for a stock that just grew its revenue 85% last quarter and continues to have strong prospects.
Nvidia and its graphics processing units (GPUs) continue to dominate the market for AI model training, and given its wide CUDA software moat, which is where most initial foundational AI code was written, this is unlikely to change anytime soon. However, what is most exciting is how the company is positioned for the future, basically transforming itself from a simple GPU maker to a complete AI infrastructure player.
Today's Change
(
-0.61
%) $
-1.19
Current Price
$
194.55
Its networking segment has been its fastest growing, while it has also designed its own ARM-based central processing units (CPUs). Its "acquisition" of Groq has allowed it to incorporate its inference chips into its CUDA software. This now allows it to offer complete solutions not only for AI training, but also for emerging areas like inference and agentic AI.
The Nvidia growth story is far from over, making this dip a great buying opportunity.
2. Alphabet Alphabet (GOOGL 0.62%) (GOOG 0.58%) is another top tech stock trading near two-month lows. It recently was under some pressure after losing some AI talent, but this doesn't change the company's long-term story. Alphabet remains the company with the most complete AI stack, having both a world-class foundational AI model in Gemini and top-notch AI chips with its tensor processor units (TPUs).
Today's Change
(
-0.62
%) $
-2.13
Current Price
$
341.58
The company's cloud computing segment, Google Cloud, has been growing rapidly, with revenue surging 63% in Q1 2026. Simultaneously, its core search business has also seen accelerating growth, with revenue in this segment up 19% -- incorporating AI within Google Search has helped drive queries and strong growth.
The company's TPUs help give it a big cost advantage both in training its models and in running inference. It can also help provide higher margins within Google Cloud. And with Anthropic looking to buy some of its TPUs for use outside of Google Cloud, it also gives it another high-margin revenue stream.
With the stock trading at a forward P/E of around 24, now is a great time to buy.
Image source: Getty Images.
3. Amazon Another tech heavyweight that is trading below where it was two months ago is Amazon (AMZN +2.18%). The recent dip has left it with a forward P/E of just 27 times this year's analyst estimates and below 24 times next year's consensus. That is both historically cheap and also significantly below the valuations of its brick-and-mortar peers Costco and Walmart.
Despite the recent dip in its stock price, Amazon has been firing on all cylinders. It's seeing tremendous operating leverage in its e-commerce business as its investments in robotics and AI drive efficiency and cost savings. This led to a 43% increase in operating profit in its North American segment last quarter on a 12% rise in sales. The company's leadership in robotics, where it is the world's largest manufacturer and operator, is an often overlooked part of the company's story.
At the same time, the company has been seeing accelerating revenue growth in its AWS cloud unit, which is its largest segment by profitability. The company's chip business also helps give it a cost advantage, and partnerships with Anthropic and OpenAI should help continue to fuel growth well into the future. That makes this a stock to buy for the long term while it's currently down.
Geoffrey Seiler has positions in Alphabet and Amazon. The Motley Fool has positions in and recommends Alphabet, Amazon, Arm Holdings, Costco Wholesale, Nvidia, and Walmart. The Motley Fool has a disclosure policy.
AI stocks led by Nvidia (NVDA) are facing a sharper bubble warning after Chinese fund managers said the era of âbrainless buyingâ may be close to breaking,
Amazon (AMZN) is raising prices for GPU rental capacity on AWS, a sign that demand for AI computing power remains tight across key cloud regions, according to S
Finding core tech stocks to build a portfolio around can be a smart idea for investors. This sector has created the majority of value in the market for the past decade, and that will likely continue for the next decade as artificial intelligence (AI) innovations and breakthroughs occur.
Three that I think qualify for this segment are Alphabet (GOOG 0.70%) (GOOGL 0.64%), Microsoft (MSFT +4.77%), and Nvidia (NVDA 0.78%). Each of these looks like an excellent building block for a portfolio, and I think all will be a smart pick over the next decade.
Image source: Getty Images.
1. Alphabet Alphabet is first on my list for a good reason: It's the most solid of the three. Alphabet has a multi-pronged approach to AI, and its strategy so far has proven fairly solid.
First, it's integrating AI into its core Google Search product. This has made Google the go-to for quick AI-generated information on a topic, and it's a feature loved by the billions who use the product. Alphabet uses its own AI model to do this, leading to the second prong. Thanks to a strong generative AI model in Gemini, it can control its destiny with AI and its business.
Lastly, Alphabet has a thriving cloud computing wing, with Google Cloud growing faster than any of the major cloud providers in Q1. Google Cloud gives AI developers and companies a place to run AI workflows, so even if Alphabet's model doesn't come out on top, Google Cloud won't be a flop, either.
Today's Change
(
-0.64
%) $
-2.19
Current Price
$
341.52
This multifaceted approach has so far proven successful for Alphabet, and its stock has doubled over the past year. Still, there is more upside ahead for Alphabet if it can maintain its current growth pace, and I think it will be an AI force to be reckoned with for years to come.
2. Microsoft Microsoft's AI approach is very similar to Alphabet's, except that it isn't developing its own AI model. Instead, it has chosen to partner with OpenAI, the makers of ChatGPT. Microsoft owns about 27% of OpenAI, so it has a vested interest in its success. Microsoft's Azure cloud computing platform remains neutral and offers developers countless large language models to deploy and use. However, Microsoft has integrated OpenAI's products into all of its existing business productivity software via Copilot.
Today's Change
(
4.77
%) $
16.83
Current Price
$
369.66
This has been a successful approach so far, but the stock hasn't responded to Microsoft's results as it has with Alphabet's. Microsoft is down over 30% from its all-time high, and it looks like a screaming deal as the future is bright.
3. Nvidia Last is Nvidia, which may seem like an odd choice. Current market sentiment is that Nvidia's stock will decline once the AI build-out is wrapped up.
While that's a fair take, it ignores the fact that computing units in data centers have relatively short lifespans and need to be replaced every couple of years. Furthermore, Nvidia will likely keep innovating and developing new computing units with enhanced capabilities that can cut costs and improve performance, which could justify upgrading old systems.
Nvidia is interwoven into nearly every AI product, and it will remain a vital company in the industry long after the initial build-out is complete. However, the market isn't pricing any of that into Nvidia's stock.
NVDA PE Ratio (Forward) data by YCharts
The stock trades for a mere 22.3 times forward earnings, and less than 16 times next year's earnings. That's a major bargain that doesn't come around very often. With Nvidia being a core part of the AI build-out still expected to last for multiple years, the stock is a great buy now and a solid one to build a portfolio upon.
Nvidia stock NVDA fell again on Friday as a broader technology-sector selloff continued to pressure artificial intelligence stocks, leaving the chipmaker on track for its worst weekly performance in more than a year.
The stock declined about 1.5% to $192.35 in early trading. If losses hold through the close, Nvidia would finish the week down more than 9%, marking its steepest weekly decline since April 2025.
The latest pullback extends a difficult stretch for the company, which slipped below the psychologically important $200 level after recovering from an earlier decline in March 2026.
That support level broke earlier this week as concerns surrounding artificial intelligence spending and rising competition weighed on investor sentiment.
The broader market was mixed on Friday as investors assessed ongoing weakness across technology stocks.
The S&P 500 traded around the flatline, while the Nasdaq Composite fell 0.3%. The Dow Jones Industrial Average was little changed.
Semiconductor stocks remained under pressure as investors continued reassessing valuations across the AI sector after several years of extraordinary gains.
The selloff comes amid growing debate over whether the pace of AI infrastructure spending can be sustained and whether the massive investments being made by technology companies will ultimately generate sufficient returns.
Investor sentiment was also affected by a New York Times report that OpenAI is considering delaying its initial public offering until next year.
According to the report, concerns about volatility in AI-related stocks and the recent performance of newly listed SpaceX are among the factors being evaluated.
The report contributed to weakness across AI-linked companies as investors reassessed enthusiasm surrounding some of the market's most popular growth themes.
Competition concerns remain in focusAt the same time, Nvidia continues to face increasing scrutiny over its long-term competitive position.
While the company remains the dominant supplier of AI accelerators, investors have become increasingly focused on efforts by major technology firms to develop alternatives to Nvidia hardware.
Earlier this week, OpenAI and Broadcom unveiled a custom artificial intelligence chip called Jalapeño.
The processor represents OpenAI's first internally developed AI chip and is intended primarily for inference workloads, which involve serving AI models to users through products such as ChatGPT.
OpenAI President Greg Brockman said the chip was developed with assistance from the company's own AI models.
"The degree to which our models have been able to accelerate it was very surprising to us," Brockman said during an interview with CNBC's David Faber.
According to Brockman, the chip was designed from end to end in approximately nine months.
The announcement highlighted a broader industry trend as hyperscalers, AI laboratories, and major technology companies seek greater control over their computing infrastructure through custom silicon.
Despite growing competition, Nvidia remains at the center of the AI infrastructure market.
Its graphics processing units continue to power many of the world's largest AI systems, and customers have already committed to deploying the company's next-generation platforms.
However, investors are increasingly focused on whether Nvidia can maintain its dominant market share as custom chips gain traction and large customers diversify their hardware strategies.
For now, there is little evidence that Nvidia's business has been materially affected.
Nevertheless, the combination of elevated valuations, questions around AI spending, and growing competition has made investors more cautious.
That caution has left Nvidia searching for support after slipping below the $200 level, with the stock now facing one of its most challenging weeks since the AI-driven rally began.
Microsoft (MSFT), Nvidia (NVDA), Meta Platforms (META), and other major technology stocks have come under pressure in recent weeks as investors weigh the costs
Pension funds run on rules, not vibes. Every quarter, especially at half-year close, big institutional allocators check their books and realize the math has drifted. Stocks went up. Bonds did not. That mismatch forces a mechanical trade unrelated to whether the market is cheap, expensive, or about to discover artificial general intelligence in a garage.
The funds sell what got too big and buy what got too small. The Markets segment S&P to 8,000 This Year? flagged this dynamic for the back half of next week, putting a dollar figure on the flow and a date on the calendar. The host’s view is that forced selling creates a buying window. Understanding why that math exists, what the actual numbers look like heading into the rebalance, and how a patient investor might think about it matters.
Why $30 billion has to move The host put it directly. “There’s actually $30 billion of US stocks for sale attached to this pension rebalance,” with the selling concentrated on June 29th and June 30th, the final two trading days of the first half.
Pension funds operate under target allocations, often something like a 60/40 split between equities and fixed income, set by investment policy statements that boards take seriously. When stocks rip and bonds shuffle, the equity sleeve balloons past its target weight.
To get back to policy, the fund sells stocks and buys bonds. There is no discretion involved. A trustee who lets the portfolio drift gets sued. So at quarter-end, and with more force at half-year close, rebalancing trades fire automatically. The bigger the gap between stock and bond returns, the bigger the trade size.
The performance gap driving the trade This half, the gap is wide. The SPDR S&P 500 ETF Trust (NYSEARCA:SPY) is up 7.4% year to date through June 25, and 20% over the past twelve months. Bonds have barely moved. The Vanguard Total Bond Market ETF (NASDAQ:BND) is up 1.01% YTD. The intermediate Treasury bellwether, the iShares 7-10 Year Treasury Bond ETF (NASDAQ:IEF), has returned 0.18% YTD.
A fund that started the year at policy weight is now meaningfully overweight equities and underweight fixed income. Multiply that drift across every major US public pension, corporate defined benefit plan, and target date fund family running quarter-end rebalancing programs, and you reach a flow estimate in the tens of billions.
The host’s $30 billion sits in the range of what street desks have circulated, and it is a seller of US equities into a market that has already wobbled. SPY is down 1.9% on the week and 2.2% on the month going into the rebalance window.
Why the host calls it a buying opportunity The case for fading the flow rests on a simple observation. Forced selling is mechanical, untethered from any view on fundamentals. A pension trimming equities on June 30 tells you nothing about Nvidia’s (NASDAQ:NVDA | NVDA Price Prediction) next quarter or the path of the fed funds rate. The trade is mechanical, the price impact is temporary, and once the rebalance clears, the marginal supply disappears. Historically, month-end and quarter-end pressure has tended to reverse within days as discretionary buyers step back in.
The host framed it that way. “I would not be surprised to see some early market weakness next week. That again could present a solid buying opportunity.”
Volume into the cash close on Monday and Tuesday is where the rebalance prints, and the size will show up in the closing imbalances reported by the exchanges. If stocks hold in the morning sessions and the selling lands cleanly into the auctions, the dip stays shallow. If macro headlines pile on top of the mechanical flow, the weakness lasts longer than the rebalance itself. The investment policy documents that drive all of this are public for most large public pensions and can be reviewed through their own disclosures and, where applicable, SEC filings for the asset managers running the mandates. The trade is boring on purpose. That is the entire point.
Investors are now fully aware of just how successful Nvidia (NVDA 1.30%) has become. What was once an enterprise focused on PC gaming has become a dominant artificial intelligence (AI) business with a market capitalization of $4.8 trillion. This is the most valuable company on the face of the planet.
Despite trading 15.6% off their peak (as of June 23), Nvidia shares are up 6.7% so far in 2026 and have skyrocketed 944% over the past five years.
You haven't missed the boat. Here's one reason to buy this leading AI stock right now.
Image source: The Motley Fool.
Listen to what management is saying There might be no single leadership team on the planet facing a brighter spotlight than Nvidia's management group. It's led by Jensen Huang, who has held the top job at Nvidia since founding the business in 1993. The market listens closely to these executives to understand how the AI landscape will evolve, which makes sense given that they have front-row seats in the industry.
Chief Financial Officer Colette Kress recently gave investors one phenomenal projection that can turn the skeptics into believers. "AI infrastructure spending is on track to reach $3 trillion to $4 trillion annually by the end of this decade," she said on Nvidia's first-quarter fiscal 2027 earnings call. It's worth reiterating that this forecast is on a yearly basis, not in total.
This calendar year, spending is expected to be $765 billion, based on research from Goldman Sachs. To reach the midpoint of Kress's prediction of $3.5 trillion in spending in 2029 implies a monster 358% rate of growth in three years.
Nvidia has a virtual monopoly position in the market for data center graphics processing units (GPUs). It is literally at the epicenter of the AI infrastructure boom, selling the necessary hardware and software that powers training and inference. The company's Blackwell architecture is seeing robust demand, and its newest Vera Rubin platform, built for agentic AI, will start shipments in the third quarter.
Today's Change
(
-1.30
%) $
-2.54
Current Price
$
193.20
Higher demand can lead to a higher stock price Investors are smart to question Kress's outlook. She's incentivized to provide bullish commentary, as it can support Nvidia's share price. It's difficult to argue with the massive spending that's happening, though.
Assuming Kress's forecast is correct, Nvidia will continue to see tremendous demand. That's why investors should consider buying the stock right now, while it's at a compelling forward price-to-earnings ratio of 23.8. The business is best positioned to capitalize on the AI spending bonanza.
Sell-side analysts see Nvidia's revenue rising at a compound annual rate of 45.6% between fiscal 2026 and fiscal 2029. The consensus view is that adjusted diluted earnings per share will increase at a yearly clip of 48.8% during the same time. Fundamental gains like this can propel the stock.
Neil Patel has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Goldman Sachs Group and Nvidia. The Motley Fool has a disclosure policy.
A woman takes a picture at the NVIDIA booth during the China International Supply Chain Expo (CISCE) in Beijing on June 25, 2026. (Photo by Pedro PARDO / AFP via Getty Images)
AFP via Getty Images
This article was written by Doug Nathman, with research by his team at Trefis.
While investors concentrate on NVIDIA's staggering growth rate, an even more revealing figure resides in its supply commitments, illustrating a calculated strategy to satisfy demand that skeptics argue may not be viable.
Following a remarkable ascent, NVIDIA (NVDA) shares have cooled. The stock price has dipped below recent peaks, and discussions have transitioned from celebration to doubt. Is it possible for any corporation, even one at the forefront of the AI surge, to sustain this growth rate? While many analysts are examining the latest earnings figures or its trailing multiple, a crucial piece of information for an optimistic perspective is not found on the income statement at all.
The figure is $145 billion. This amount signifies NVIDIA’s overall supply, comprising existing inventory and, more critically, its future purchase commitments.
What Does $145 Billion In Commitments Represent?This amount signifies much more than merely a stockpile of chips stored away; it embodies a substantial, strategic commitment to future production. These pledges secure the necessary manufacturing capacity and raw materials required to create its upcoming generation of processors. Management has affirmed that this is a calculated initiative, reflecting the enhanced demand visibility we possess and a choice to secure capacity farther in advance than is normally standard. In a sector where a single shortage of components can disrupt production, NVIDIA is investing now to ensure it can manufacture the products it anticipates selling over the next several quarters, and even extending into the year 2027.
How This Assures Future RevenueThe underlying principle is straightforward: one cannot sell what cannot be produced. The primary physical limitation on NVIDIA's expansion is not demand, but rather the intricate supply chain necessary for its AI accelerators. By securing $145 billion worth of supply, the company is establishing the groundwork for its forecasts. This strategy is proactive, acting as the concrete basis for management's proclaimed confidence in achieving $1 trillion in Blackwell and Rubin revenue through 2027. That projection appears abstract until one observes the nine-figure commitments being undertaken to ensure the components needed for chip production.
MORE FOR YOU
The Resolution To The Major Concern?The foremost risk looming over the stock is its sustainability. The stock is currently facing pressure precisely because the market is questioning the duration of this level of growth. The company’s price-to-earnings multiple of 30.3, although high in relative terms, lies toward the lower end of its own 10-year spectrum of 19.6 to 143.1, indicating that investors are reluctant to factor in future growth at a rate comparable to the past. These purchase commitments represent a direct and significant response to that apprehension. A corporation that fears an approaching cyclical peak would not engage in long-term supply agreements of this magnitude. This indicates that management perceives a demand trajectory that justifies the undertaking of risk to secure capacity well in advance.
Of course, a commitment does not equate to a sale. The ultimate benchmark is converting that secured supply into revenue. However, for investors attempting to evaluate the resilience of NVIDIA’s market position, this $145 billion figure offers a concrete, forward-looking metric that the headline growth rates do not convey.
Typically, one figure does not drive a decision independently, but recognizing which number is crucial and the rationale behind it constitutes a significant portion of the challenge. Arriving at the aforementioned figure required looking beyond the surface level of fear to what was genuinely occurring beneath—an analysis that is difficult to perform once and exceedingly challenging to replicate consistently.
The Trefis High Quality (HQ) Portfolio is constructed on executing precisely that, continuously, across 30 quality enterprises, and then maintaining them with rule-based discipline so that no single entity dominates your outcome. You acquire a selection of well-researched advantages rather than a sole all-or-nothing gamble, with a proven record of surpassing a benchmark that aggregates the three major indices – the S&P 500, S&P Mid-cap, and Russell 2000. If a figure like this one merits action, that form of disciplined quality deserves serious consideration.
NVIDIA (NASDAQ: NVDA | NVDA Price Prediction) and Cerebras Systems (NASDAQ: CBRS) just delivered earnings that frame the same question from opposite ends. Nvidia posted another blowout quarter built on its CUDA software stack. Cerebras, fresh off its May IPO, showed jaw-dropping inference speed yet guided full-year operating margins negative. The moat is developer gravity.
One Sells Platforms. The Other Sells Speed. Nvidia’s Q1 FY27 hit $81.61 billion in revenue, up 85.2% YoY, with Data Center alone reaching $75.25 billion on 92% growth. Networking soared 199% as InfiniBand, NVLink and Spectrum-X locked customers deeper into the stack. Jensen Huang told investors NVIDIA is “the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced”, and the numbers back the claim.
Cerebras’ first report as a public company landed differently. Q1 GAAP revenue reached $193.4 million, up 94% YoY, with cloud services growing 178%. A multi-year, $20 billion-plus OpenAI inference deal covering 750 megawatts anchors near-term growth. Yet management guided full-year operating margins to negative 28% to negative 32%. Speed sells. Scaling it economically is harder.
Software Gravity Beats Wafer-Scale Throughput Independent benchmarks show Cerebras’ wafer-scale design delivering a 21x speed advantage over Nvidia hardware for latency-sensitive, low-batch inference. The catch is that every major LLM framework and enterprise developer stack is natively optimized for Nvidia architecture out of the box, while Cerebras requires specialized compilation and custom engineering support for anything off the well-trodden path.
Lens NVIDIA Cerebras Core Bet CUDA full-stack platform Wafer-scale inference speed Q1 Gross Margin 75.0% non-GAAP 44.6% GAAP Anchor Customers Meta, OpenAI, Anthropic, Google OpenAI, AWS, G42 Biggest Vulnerability OpenAI’s Jalapeño custom chip Negative operating margins Nvidia’s $119 billion in supply commitments and $80 billion added to its buyback authorization signal management is doubling down on the platform. Cerebras raised $5.6 billion at IPO and is funneling it into data center capacity for OpenAI’s decode workloads while AWS Trainium 3 handles prefill. That is a focused inference bet riding on one customer’s roadmap.
The Next Test Is Whether Developers Defect Two catalysts matter into the back half of 2026. For Nvidia, the OpenAI Jalapeño chip, built with Broadcom, is the most credible threat to CUDA stickiness. NVDA shares are already down 8.79% over the past month, even with the stock up 27.01% YoY. For Cerebras, the bar is executing the OpenAI ramp without further margin slippage. Q2 core gross margin guidance of 36% to 38% telegraphs how steep the infrastructure build will be.
Why The Setup Still Favors Nvidia For AI infrastructure exposure with a self-funding moat, Nvidia remains the cleaner expression of the thesis. The 75% gross margin, $48.55 billion in quarterly free cash flow, and the developer install base are tough to dislodge in a single product cycle. Cerebras has the faster chip and a marquee anchor customer. A forward P/E of 23 on NVDA already prices in some software erosion. If CUDA defections spread beyond OpenAI, my view changes.
Since Nvidia (NVDA 1.86%) started its monster rise at the beginning of 2023, there have been countless investors who proclaimed the stock to be in a bubble. Time and time again, those investors were proven wrong.
There may be a handful of people who are still saying Nvidia is in a bubble right now, although I'd argue that the opposite is true: I think it's undervalued.
I think investors are underestimating the potential of the Rubin upgrade cycle that's coming later this year, and it could easily send Nvidia stock to new heights that no stock has ever reached before.
Image source: Getty Images.
Even more growth is headed Nvidia's way Later this year, Nvidia's newest architecture launches. The Rubin chip architectures build upon an already impressive Blackwell architecture, and offer a 10 times reduction in artificial intelligence (AI) inference costs and a four times reduction in training costs. That sounds impressive from a cost-savings standpoint, but what the AI hyperscalers actually hear is that they can achieve a major performance increase at the same cost by running the same number of GPUs.
Regardless of how these units are used, these improvements aren't coming for free. Rubin chips cost about 25% more than Blackwell, which will result in a revenue increase just from switching to a new chip generation. That will help boost Nvidia's revenue and profits over the next year, but there are other factors at play.
Today's Change
(
-1.86
%) $
-3.71
Current Price
$
195.29
All of the major AI hyperscalers announced a combined $650 billion in data center capital expenditures for 2026. While this cohort hasn't unveiled 2027 projections, Nvidia believes the spending will be more than $1 trillion. That's a huge rise, and will likely be leveraged more heavily toward computing equipment as the physical data center buildings near completion.
An upgrade cycle combined with an expanding market could lead to massive growth for Nvidia, and Wall Street analysts back up that projection. For the rest of the current fiscal year (FY) 2027 (ending in January 2027), they estimate 81% revenue growth. For FY 2028, that figure is 41%. While that's not as fast as FY 2027's, it's still a strong growth rate for a company as large as Nvidia. Furthermore, analysts have historically underpredicted Nvidia's growth rate, so don't be surprised if it's much faster than this.
Despite an obviously strong year upcoming, Nvidia's stock has priced in very little future growth beyond this fiscal year.
NVDA PE Ratio (Forward 1y) data by YCharts
That makes Nvidia stock a no-brainer buy now, as it's actually quite cheap and completely dispels the notion that Nvidia is in a bubble.
Semiconductor chip export restrictions to China have cost Nvidia (NVDA 1.86%) billions in revenue. In a recent interview, CEO Jensen Huang admitted that Nvidia's chip market share in China has been wiped out. Speaking about Nvidia's share of the artificial intelligence (AI) chip market, Huang said, "Nvidia had ... 90-some-odd percent of the world's market share. Today in China, we have now dropped to zero."
China is a large and important market for Nvidia, but in the near term, the company hasn't missed a beat. Its new Vera central processing unit (CPU) is opening up a $200 billion addressable market that completely dwarfs its previous chip revenue in China.
Image source: The Motley Fool.
Vera CPU revenue expected to hit nearly $20 billion Last year, the company earned nearly $20 billion in revenue from China (9% of its total revenue), but that revenue fell by roughly half year over year in the fiscal first quarter to approximately $4.5 billion. Huang's comment suggests revenue has continued to collapse since the end of the quarter. While the U.S. has approved some licenses for the H200 chip in China, Nvidia has yet to earn any revenue from it and has not included any China data center sales in its forward guidance.
However, Nvidia is never sitting still. Its steady cadence of product releases is one of its competitive strengths. The GPU leader is now a leader in CPUs as well. During the last earnings call in May, management noted that it expects nearly $20 billion in CPU revenue this year. This completely replaces last year's revenue from China.
Today's Change
(
-1.86
%) $
-3.71
Current Price
$
195.29
Nvidia is set for another record year By expanding into the CPU market, Nvidia is entering a space that Intel and Advanced Micro Devices have dominated for decades. AI demand has made the semiconductor competitive landscape more crowded, but Nvidia is differentiating itself by integrating Vera CPUs into a computing system that includes networking, accelerated-computing racks, and GPUs. This kind of innovation is a big reason Nvidia's data center business nearly doubled again in the first quarter, with segment revenue reaching $75 billion.
The Vera Rubin computing platform is designed for advanced reasoning and multiple-step problem-solving to power agentic AI. It features seven purpose-built chips to deliver up to 35x higher inference throughput. It should drive significant revenue when it starts shipping later this year.
Analysts currently expect Nvidia's full-year revenue to increase 81% from last year to $391 billion. That should translate to $8.96 in earnings per share based on the consensus estimate.
Given the uncertainty around government regulations in chip exports, it's unclear when Nvidia will recover its business in China. But for now, the growth opportunity from Vera CPUs is not priced into the stock's valuation, which is 22 times this year's earnings estimate. That looks very cheap relative to Wall Street's earnings growth estimates for the next few years, which currently sit around 45% annualized.
John Ballard has positions in Nvidia. The Motley Fool has positions in and recommends Advanced Micro Devices, Intel, and Nvidia. The Motley Fool has a disclosure policy.
Nvidia (NVDA 1.86%) had a market capitalization of $360 billion at the beginning of 2023, which was right before the artificial intelligence (AI) boom started gathering momentum. The company has since sold millions of its graphics processing units (GPUs) for data centers, which are the primary chips used in AI training and inference workloads, propelling its market cap to $4.8 trillion.
But despite a 13-fold increase in value over the last three years, Nvidia stock is still cheap by one of Wall Street's most widely used valuation metrics. In fact, here's why the stock could more than double from here.
Image source: Nvidia.
Nvidia is about to launch its most powerful chips yet Nvidia's dominance in the market for AI data center chips started in 2022 with its H100 GPU, which was built on its Hopper architecture. The company has since launched Blackwell and Blackwell Ultra GPUs, the latter of which can deliver up to 50 times more performance than the H100 in certain configurations.
Blackwell Ultra GPUs are currently the most sought-after AI chips in the industry, but Nvidia is about to extend its advantage with its new Vera Rubin system, which will ship in the second half of this year. It includes the Rubin GPU, the Vera central processing unit (CPU), and a series of updated networking components. Nvidia says the platform is so powerful that developers can train AI models using 75% fewer GPUs compared to Blackwell.
Vera Rubin can also reduce inference token costs by up to 90% (inference tokens include the text, images, and symbols generated by an AI model in response to a query). In other words, Nvidia's new system will make AI substantially cheaper to use, which could make providers like OpenAI and Anthropic more profitable, driving more demand for chips as a result.
During a conference call with investors on May 20, Nvidia CEO Jensen Huang said every frontier AI company intends to adopt Vera Rubin at launch, which wasn't true for the Blackwell platform. Therefore, he expects it to be far more successful than its predecessor.
Today's Change
(
-1.86
%) $
-3.71
Current Price
$
195.29
Nvidia's revenue and earnings continue to soar Nvidia generated $215.9 billion in total revenue during its fiscal year 2026 (ended Jan. 26), which was up 65% from the prior year. Its data center business accounted for $193.7 billion of that revenue, and it grew by 68%.
Both of those growth rates accelerated in the first quarter of fiscal 2027 (ended April 26). The company generated $81.6 billion in total revenue and $75.2 billion in data center revenue, which represented year-over-year increases of 85% and 92%, respectively, highlighting the sheer momentum in AI-related hardware sales.
Since demand currently exceeds supply for GPUs, Nvidia is able to dictate prices, which is significantly boosting its profit margins. As a result, Wall Street expects the company's generally accepted accounting principles (GAAP) earnings to soar by 91% to $9.36 per share during fiscal 2027 (according to Yahoo! Finance), which could have very positive implications for its stock price.
The price-to-earnings (P/E) ratio is one of the most widely used valuation metrics on Wall Street. If a stock has a P/E ratio of 10, investors are effectively paying $10 for every $1 of the company's earnings. Faster-growing companies tend to attract higher P/E ratios; investors are willing to pay more for their earnings because those companies will, in theory, earn their money back more quickly.
That's why the Nasdaq-100 index, which is full of high-growth technology companies, trades at a P/E ratio of 34.4, whereas the more diversified S&P 500 trades at a P/E ratio of 25.2.
Nvidia's P/E ratio recently fell to 30.09, which was the lowest level since 2019. Moreover, it was a substantial discount to its average P/E of 71.2 over that seven-year period.
NVDA PE Ratio data by YCharts
In other words, Nvidia stock would have to more than double just to trade in line with its long-term average P/E ratio. I'm not suggesting that will happen immediately, but based on the company's projected earnings for fiscal 2027 (which I highlighted earlier), its stock trades at a forward P/E ratio of just 21.5. That means even if its stock doubles over the next six or seven months, its P/E would rise to just 43, which would still be far below its long-term average.
No matter which way you slice it, Nvidia stock looks extremely cheap right now, especially ahead of what could be the biggest product launch in its history. As a result, it could be a great buy right now.
Banks have spent decades building fraud systems that see one transaction at a time. A charge either looks suspicious or it doesn’t. Fraud rings built their business model around that gap, spreading activity across thousands of payments using stolen cards, mule accounts, shared devices and synthetic identities so no single transaction trips a filter.
The Nilson Report projects that global card fraud losses will reach $403 billion over the next decade, with the U.S. accounting for roughly 42% of those losses despite representing just 26% of total card volume worldwide, according to a press release.
Nvidia’s AI blueprint for financial fraud detection is built around a different idea. Rather than asking whether a single transaction looks suspicious, the system asks whether the people, devices and accounts involved in a transaction are connected to suspicious activity elsewhere. A $47 purchase at a gas station may look completely normal on its own. It looks different if the phone used to approve it also shows up in 60 other disputed charges across three states that week. Or the same card was opened using an address tied to a known mule account.
That is the blind spot fraud rings count on. PYMNTS Intelligence found that unauthorized-party fraud — driven by credential theft and account takeovers — now makes up 71% of all fraud incidents and dollar losses at U.S. financial institutions, up from 48% in 2024. Organized rings move fast precisely because they know the window before detection closes.
Why Transaction-Level Scoring Fails Against Organized Rings Most bank fraud systems today use a technique called gradient-boosted modeling, a scoring engine that looks at a transaction’s characteristics and decides whether it resembles past fraud. Did the purchase happen in an unusual location? Was the amount out of range for this customer? Did the card get used twice in five minutes in different cities? Those are useful signals for catching individual bad actors.
They are much less useful against a coordinated ring. A ring using 500 stolen card numbers can keep each card’s activity well within normal-looking ranges, making individual transactions appear routine. The Nilson Report found that card-not-present transactions represent the highest-risk category in every world region, precisely because they are easiest to execute at scale with stolen credentials, according to the release.
Nvidia’s blueprint addresses that gap by adding a layer that maps relationships across the data. The technique, graph neural networks, works by building a picture of how transactions, accounts and devices connect to each other, then looking for clusters that share suspicious links. It feeds those relationship signals into the existing scoring model as additional context, so a transaction that scores low on its own can still be flagged if it sits inside a connected cluster of high-risk activity.
PYMNTS reported that Block Chief Risk Officer Brian Boates has pushed banks to move away from reviewing fraud after the fact toward stopping it in the moment. “It’s one thing to find the bad actors after the fact,” Boates said. “But what’s much more effective is investing in more real-time technology.” PYMNTS Intelligence found that 68% of financial institutions have increased fraud detection spending year over year as the problem outpaces older systems.
Real-Time Decisions Inside Live Payment Flows The challenge with relationship-based analysis is speed. Mapping connections across millions of accounts and transactions takes significant computing power. Doing it fast enough to stop a payment before it clears, typically within a few hundred milliseconds, requires infrastructure most banks have not yet built.
The Nilson Report noted that worldwide card fraud losses totaled $33.41 billion in 2024, and that AI tools have helped the industry build its best fraud-fighting models to date, even as organized crime continues to adapt.
Nvidia’s blueprint uses its Dynamo-Triton inference server to run those relationship checks at payment speed. The system produces a fraud score for each transaction alongside an explanation of which signals drove it, so a fraud investigator can see not just that a transaction was flagged, but that it was flagged because the device matched three others in an active dispute cluster, or because the billing address had been used to open four accounts in the past week. The blueprint runs on Amazon Web Services and Hewlett Packard Enterprise, with Dell Technologies support planned, Nvidia said.
For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.
For much of the AI boom, Nvidia (NVDA 1.86%) has been the stock market darling.
The stock started soaring shortly after the release of ChatGPT in Nov. 2022 as it was primed to benefit from demand for its GPUs, which are used for AI training.
Since then, the stock has gained more than 1,000%, and Nvidia has become the most valuable company in the world, with a market cap of nearly $5 trillion.
However, in 2026, chip stock investors seemed to have moved on from the industry leader, piling into the new chip sector bottlenecks, including memory chip stocks like Micron and Sandisk, which are experiencing a shortage, and CPU stocks like Intel, AMD, and Arm Holdings, which are expected to benefit from increasing demand for AI inference.
As a result, Nvidia's performance has been downright pedestrian this year. At nearly the halfway point of 2026, Nvidia stock is up just 4%, compared to an 8% gain in the S&P 500, and a 9% increase in the Nasdaq Composite. The iShares Semiconductor ETF, which tracks the sector, has more than doubled this year due to breakout gains from Intel, Micron, and other stocks, rather than Nvidia.
Today's Change
(
-1.86
%) $
-3.71
Current Price
$
195.29
While Nvidia stock is slumping, down 17% from its peak in May, the business performance remains excellent. Revenue jumped 85% in the first quarter to $81.6 billion, and adjusted net income rose 139% $45.5 billion. Nvidia's net income is on track to top $200 billion this year, easily making it the most profitable company in the world. To put that number into perspective, only a few dozen companies make that much in annual revenue. $200 billion is similar to the GDP of countries like Ukraine and Qatar.
Based on its trailing adjusted earnings per share of $5.84, the stock now has a price-to-earnings ratio of 33, which is modestly more expensive than the S&P 500, at 26.
Image source: Nvidia.
Where Nvidia starts to look like a bargain The trailing valuation isn't the best way to look at Nvidia. After all, this is a company that just grew revenue by 85% and more than doubled its net income. You have to factor in its growth and its direction.
Below is the consensus EPS forecast for Nvidia for the next three years.
Fiscal year endingEPS consensusJan. 2027$8.69Jan. 2028$11.67Jan. 2029$15.76 Source: Nasdaq.com
Nvidia reported $4.77 in adjusted EPS last year, so analysts expect EPS to nearly double this year and to more than triple over the next three years.
Based on fiscal 2029 estimates, the stock looks ridiculously cheap, trading at just 12 times expected earnings. That's a valuation normally reserved for no-growth or slow-growth stocks in sleepy industries like banking and manufacturing.
Nvidia, on the other hand, has been one of the most disruptive companies of the decade and is still growing like wildfire.
Is Wall Street right? It's worth remembering that the numbers in the chart above are just forecasts, and the further out they go, the more inaccurate they become. A lot could change between now and Jan. 2029.
However, investors should also be aware that analysts have significantly underestimated the sustainability of the AI boom and Nvidia's growth.
The chart below shows how Wall Street's estimates for Nvidia's next fiscal-year revenue have changed.
NVDA Revenue Estimates for Next Fiscal Year data by YCharts
Through much of 2025, Wall Street thought Nvidia would bring in around $250 billion in revenue for the current fiscal year (fiscal 2027). Instead, Nvidia is on track for close to $400 billion in revenue this year. That's a huge miss; Wall Street simply did not expect the company's growth rate to reaccelerate, which it has in recent quarters.
Why Nvidia looks so undervalued The best explanation for why the stock is trading at just 12 times fiscal 2029 earnings is that investors don't believe these profits are sustainable over the long term. According to that argument, semiconductors are historically cyclical, and when the massive AI capex build-out slows down, so will demand for Nvidia chips.
The debate over whether there's an AI bubble has been brewing for nearly a year now, and there's no clear answer. Last night's earnings report from Micron showed that there's still a huge shortage in memory chips, which seems bullish for companies like Nvidia. While Nvidia is a customer of Micron, the memory shortage means that demand for AI chips like Nvidia's would be even higher if there were sufficient memory supply. In other words, Nvidia's revenue could be even higher than what it is now. Nonetheless, Nvidia stock fell on the news.
At some point, there will likely be a peak in the AI chip cycle, and depending on valuations, there will be a pullback in some stocks. If that happens, some observers will surely say the AI bubble has burst.
However, that risk seems more than priced into Nvidia stock at this point, and Wall Street has thus far been too conservative, underestimating its growth. While the fiscal 2029 EPS forecast is probably wrong, there's a good chance that it's wrong because it's too low, rather than too high.
Congresswoman and former Speaker of the House Nancy Pelosi (D-Calif.) is one of the most followed members of Congress when it comes to her disclosed stock and options trades. Here’s a look at the trades disclosed by Pelosi since the start of 2025 and the names added to her portfolio.
• NVIDIA stock is trading in a tight range. What’s the outlook for NVDA shares?
Nancy Pelosi’s New Stock PicksSince the start of 2025, here are the stocks that Pelosi has disclosed buying shares or options, including the most recently disclosed options purchased this month.
Pelosi’s trading activity can be tracked on the Benzinga Government Trades page.
The three Magnificent Seven stocks are Amazon, Nvidia and Alphabet.
Pelosi’s Trading ActivityPelosi’s spouse, venture capitalist Paul Pelosi, is likely the one overseeing the investment decisions.
Pelosi’s husband has a history of buying call options that are in the money and have expiration dates of a year from the purchase date. He later exercises the options into common stock.
Investments are often made in the technology sector, favoring large-cap names.
Pelosi’s investments are made on a large scale. Transactions are often in the hundreds of thousands of dollars and sometimes in the millions.
The stocks above represent a portion of the current investment portfolio and the stocks held by the Pelosis, with a focus on the most recent investments.
Pelosi has made total stock and options transactions of $8.88 million in 2026, which is down from $48.6 million in transactions in 2025 and $39.2 million in 2024, according to data from Quiver Quantitative.
So far, 2026 includes nearly all buying of options and stocks. The past two years have seen more sales than buys by dollar volume.
Pelosi is not running for re-election in the 2026 election. That means she will no longer have to disclose her stock and options transactions starting in January 2027. This means this could be one of the last disclosures from Pelosi.
Photo Courtesy: ToninT on Shutterstock.com
Market News and Data brought to you by Benzinga APIs
Two of the biggest stock winners of the past decade are Nvidia (NVDA 1.86%) and Advanced Micro Devices (AMD +2.18%), which are up over 16,320% and 9,770%, respectively. The two chip rivals have been major beneficiaries of the artificial intelligence (AI) infrastructure boom, and both remain well-positioned for the long term.
However, the question is which AI stock looks like the smarter long-term buy right now. Let's dig in to find out.
Image source: The Motley Fool.
Nvidia: The king of AI Nvidia was the biggest winner in the initial phase of AI, as its graphics processing units (GPUs) became the primary chips for training large language models (LLMs). The company's advantage in this area stemmed from its CUDA software platform, which it developed to expand the use of its chips beyond their initial purpose of accelerating graphics rendering in video games.
While it took time to unfold, Nvidia smartly seeded CUDA into universities and research labs that were doing early work on AI. As a result, developers learned to program GPUs using CUDA, and most foundational AI code was written on its software platform and optimized for its chips.
Today's Change
(
-1.86
%) $
-3.71
Current Price
$
195.29
This dynamic continues to give Nvidia a sizable moat with AI model training today. In the interim, the company also built out a powerful data center networking business through its 2020 acquisition of Mellanox, and more recently, it "acquired" Groq and its language processing unit (LPU) technology for inference. It has also developed its own ARM-based central processing units (CPUs). This has helped transform Nvidia from a maker of GPUs into a complete AI infrastructure company.
Nvidia offers its customers end-to-end AI server solutions configured for specific AI tasks, such as training, inference, and agentic AI. Nvidia's revenue growth has already been eye-popping, with 85% growth in Q1, and these offerings position the company for strong future growth.
Despite its growth and strong positioning, Nvidia's stock remains attractively priced, trading at a forward price-to-earnings (P/E) ratio of under 16 times fiscal 2028 (ending January 2028) analyst estimates.
AMD: Riding two powerful trends AMD has largely been in the shadow of Nvidia during the training phase of AI, as it was unable to overcome its larger rival's CUDA advantage. However, it has greatly improved its ROCm software platform over the past few years, and it is much better positioned for inference, which is much less technically demanding than AI model training. Inference also tends to be less about raw compute power and often more about fast access to memory.
AMD's chiplet design allows for a larger KV (Key-Value) cache and for more memory to be packaged with its GPUs than those from Nvidia. Meanwhile, the company just announced it was acquiring memory optimization company MEXT, which uses AI-driven software to increase memory capacity while lowering costs without impacting performance. Its technology moves infrequently accessed data from high-cost DRAM (dynamic random-access memory) to unused flash memory, and then uses AI to predict when that data will be needed and transfers it back before it is even requested. Together with its prior acquisition of ZT Systems, this will allow AMD to offer end-to-end servers for inference at an attractive cost.
Today's Change
(
2.18
%) $
11.35
Current Price
$
531.09
The company already has two $100 billion GPU inference deals in place, and it looks poised to become a major player in this arena. That's good news, as the inference market is expected to eventually grow larger than the training market.
In addition to its inference opportunities, AMD also has a major opportunity in agentic AI. The company is a leader in data center CPUs, and this market is set to explode, as CPUs are needed to provide the sequential logic needed to manage AI agents. The GPU-to-CPU ratio is expected to go from 8:1 for training to 1:1 for agentic AI, and AMD sees this as a $120 billion addressable market.
The verdict With a 39.5x one-year forward P/E, AMD is much more expensive than Nvidia, but with a market cap of less than $900 billion, it is a much smaller company than its $5 trillion rival. With two huge opportunities ahead of it, it has significant upside, while Nvidia could eventually run into the law of large numbers in terms of revenue growth.
I really like both stocks, but I think AMD could have more upside over the next decade, given its smaller size and its positioning with two big emerging trends.
In the artificial intelligence (AI) investing sector, several stocks look like great buys right now. There is still massive demand for AI computing power, and companies are racing to build infrastructure and take market share in hopes of creating viable, long-term revenue streams.
Despite many companies offering nearly the same product, there can be large pricing disparities within the same industry, meaning you can find major deals. I think I've discovered three of them, and if you've got $3,000 to deploy, you should consider buying this trio.
Image source: Getty Images.
1. Microsoft Microsoft (MSFT 3.48%) may be one of the most mispriced stocks in the entire stock market right now. It has a strong AI business, integrating Copilot into its business productivity software, and a dominant cloud computing business in Azure. Both of these two are growing rapidly, with their AI business growing at a 123% year over year pace and cloud computing rising at a 40% clip. As more businesses integrate AI and more computing capacity becomes available, these numbers will continue to rise, leading to solid, sustainable revenue streams for Microsoft.
Today's Change
(
-3.48
%) $
-12.70
Current Price
$
352.76
Despite these strengths, the stock is down around 30% from its all-time high, and it looks like an absolute bargain. Microsoft's fiscal year (FY) ends in June, so it's best to use FY 2027 projections to value the stock. From this perspective, Microsoft trades for 19 times forward earnings -- far less than the S&P 500 at 22 times forward earnings.
Microsoft is a dominant and rapidly growing company for its size, and this pricing mismatch doesn't make a ton of sense. As a result, Microsoft is a solid stock to buy now.
2. Nvidia Nvidia (NVDA 2.55%) may seem like an odd recommendation because it's the world's largest company, but the reality is it has a ton of growth left in the tank. The AI hyperscalers' data center expenditures are expected to reach a record $650 billion in 2026, but Nvidia projects they will reach $1 trillion in 2027. If that's true, then Nvidia has major upside ahead.
Right now, the stock trades for just 23 times forward earnings, barely more expensive than the S&P 500 at 22. However, if you use next year's earnings projections, the stock really starts to look cheap.
NVDA PE Ratio (Forward) data by YCharts
At 16 times next year's earnings, it's clear that none of next year's growth has been priced into the stock. It won't stay that way forever, and by buying the stock now, you can get in on those gains before everyone else, making Nvidia an excellent stock to buy now.
Today's Change
(
-2.55
%) $
-5.08
Current Price
$
193.92
3. Nebius If you're looking for outright growth, then Nebius (NBIS 2.12%) is your stock. It's a neocloud company and offers a cloud computing platform specifically catered to AI. Nebius also has a deal with Nvidia to get cutting-edge hardware first, making it an incredibly popular platform for running AI workflows. Nebius has huge expansion plans and believes it can grow its annual recurring revenue from $1.25 billion at the end of 2025 to $7 billion to $9 billion by the end of 2026.
Early results confirm this trajectory, as Nebius's revenue rose 684% in Q1. Wall Street is equally bullish on Nebius's stock, expecting 550% revenue growth this year and 225% next year. So, despite the stock more than tripling already this year, if the stock price follows revenue growth, Nebius still has far more upside ahead.
Today's Change
(
-2.12
%) $
-5.51
Current Price
$
254.15
I think Nebius is a great stock to sprinkle in with solid, established companies like Microsoft and Nvidia. It's far riskier, but it could yield far greater returns if Nebius can build an AI computing empire over the next few years.
NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) and Advanced Micro Devices (NASDAQ:AMD) both posted earnings confirming AI infrastructure dominates semis. NVIDIA reported a $75.246 billion Data Center quarter. AMD reported $5.775 billion. The scale gap is one part of the picture. The software lock-in is the more durable factor.
CUDA Carries NVIDIA. MI450 Carries AMD’s Hopes. NVIDIA’s Q1 FY2027 revenue hit $81.615 billion, up 85.2% year over year, with non-GAAP EPS of $1.87. Networking alone grew 199% to $14.8 billion, because customers buying Blackwell also buy NVLink, Spectrum-X, and InfiniBand. That bundling is the moat. Jensen Huang framed it bluntly, calling NVIDIA “the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced”.
AMD’s quarter was strong on its own terms. Revenue rose 37.9% to $10.253 billion, with Data Center up 57% and free cash flow surging 252.96%. Lisa Su pointed to “a growing pipeline of large-scale deployments” for MI450 and Helios, anchored by Meta’s 6 gigawatts commitment. They still arrive at roughly a fourteenth of NVIDIA’s Data Center scale.
Closed Stack vs. Open Stack NVIDIA sells a closed, vertically integrated stack where CUDA-X, Dynamo, and Omniverse keep developers tethered long after hardware ships. AMD counters with ROCm, an open-source alternative, plus a wider product surface across EPYC, Ryzen, Radeon, and Xilinx. That diversification is real, but AMD competes on multiple fronts without owning any of them.
Lens NVIDIA AMD Core moat CUDA software ecosystem Open ROCm, broad portfolio Gross margin 75.0% 55% Key vulnerability China export restrictions Catching CUDA before MI450 ramps NVIDIA’s $4.84 trillion market cap trades at a forward P/E near 23. AMD trades at a richer multiple after a 275.45% one-year run, while NVIDIA shares are up 34.73% over the same window. The market is paying up for AMD’s catch-up story rather than its current cash flow.
The Next Test Is Developer Mindshare I will be watching whether MI450 Helios deployments pull engineering teams off CUDA, or whether they sit alongside it as a hedge. NVIDIA’s $119.0 billion in supply commitments and $91.0 billion Q2 guide suggest hyperscalers are not slowing orders. The SpaceX-Reflection compute deal circulating on Reddit hints at alternatives, but rewriting a decade of CUDA-native code is the real friction AMD has to overcome.
Why I Lean NVIDIA for the Moat, AMD for the Trade For investors prioritizing durable, predictable cash flow priced reasonably against earnings power, NVIDIA screens better. The CUDA lock-in produces 63% profit margins that hardware cycles alone cannot explain. For investors seeking higher-variance upside who believe ROCm gains traction in 2027, AMD offers a cleaner expression of that thesis, though Lisa Su’s sustained selling of over 200,000 shares across May and June gives me pause. The toll-road economics of CUDA contrast with AMD’s position as a challenger building a parallel highway.
Nvidia (NVDA 2.55%) and AMD (AMD +0.78%) are the two largest producers of discrete GPUs. They both produce data center GPUs for the booming AI market.
However, Nvidia often attracts more attention than AMD because it controls more than 90% of the discrete GPU market. AMD, which tries to compete against Nvidia with its cheaper chips, only holds a single-digit share. Nvidia also generates most of its revenue from its data center GPUs, but AMD still sells x86 CPUs for the slower-growth PC market.
Image source: Getty Images.
Nvidia's stock has rallied more than 930% over the past five years, while AMD's stock has risen nearly 520%. Yet Nvidia still trades at just 21 times its projected EPS for fiscal 2027 (which started in January 2026), while AMD trades at 97 times its projected EPS for 2026.
Therefore, it certainly seems like Nvidia, with a market cap of $4.71 trillion, is still fundamentally cheaper than AMD, which is only worth $854 billion. So are analysts setting the bar too high for AMD, and too low for Nvidia? Let's dig deeper to find out.
Wall Street has consistently underestimated Nvidia From fiscal 2021 to fiscal 2026, Nvidia's revenue and net income grew at CAGRs of 69% and 94%, respectively. That explosive growth, driven by surging sales of data center GPUs to hyperscalers and AI companies, repeatedly crushed Wall Street's estimates.
Today's Change
(
-2.55
%) $
-5.08
Current Price
$
193.92
Even after the AI boom lit a blazing fire under Nvidia's business, its analysts still underestimated its growth potential. In the first quarter of fiscal 2027, its revenue surged 85% year over year to $81.6 billion, beating analysts' expectations by a whopping $2.5 billion.
From fiscal 2026 to fiscal 2029, analysts expect Nvidia's revenue and EPS to each grow at CAGRs of 46%. That growth should be driven by its new Vera Rubin platform, which merges its Vera CPUs and next-gen Rubin GPUs; the growth of the agentic AI market, increased government spending on AI solutions, and the expansion of its sticky software ecosystem. The auto sector will also likely install more of its chips in autonomous vehicles.
But if you expect Nvidia to consistently beat analysts' estimates over the next three years as those catalysts kick in, then it's likely even cheaper than 21 times this year's earnings.
AMD has also stayed ahead of Wall Street's expectations From 2020 to 2025, AMD's revenue and net income rose at CAGRs of 29% and 12%, respectively. Its sales of Instinct data center GPUs accelerated during that period, but those cheaper chips didn't gain much ground against Nvidia's industry-standard GPUs.
Its sales of Epyc CPUs for data centers also rose, but they still control a tiny sliver of the market compared to Intel's (INTC 0.89%) market-leading Xeon CPUs. In other words, AMD is growing -- but it remains an underdog in the GPU and CPU markets.
Today's Change
(
0.78
%) $
4.07
Current Price
$
523.81
From 2025 to 2028, analysts expect AMD's revenue and EPS to grow at CAGRs of 44% and 82%, respectively. That acceleration should be driven by its new Instinct MI400 and MI500 AI chips, which could pull more cost-conscious hyperscalers away from Nvidia. Its upcoming Zen 6 server chips could also boost its share of the data center market, and it will expand its ROCm software ecosystem to challenge Nvidia's proprietary CUDA software.
However, AMD has only stayed slightly ahead of Wall Street's expectations. In the first quarter of 2026, its revenue rose 38% year over year to $10.25 billion, beating the consensus forecast by $336 million but falling short of Nvidia's explosive growth.
At 97 times forward earnings, a lot of AMD's future growth is already baked into its stock. But those projections are pinned to the expectations that it will gain more momentum against Nvidia and Intel -- and that might not be as simple as Wall Street's estimates suggest.
What's Wall Street wrong about? I believe analysts are still underestimating Nvidia while overestimating AMD's growth potential. Both stocks could still be great long-term AI plays, but Wall Street's poor track record with Nvidia suggests its stock is even cheaper than its forward multiple indicates.
Space Exploration Technologies, better known as SpaceX, may have captured the attention of many investors, but I think several stocks are far better investments today. One of the best may be sitting right under investors' noses.
Although it's the largest company in the world, I think Nvidia (NVDA 2.22%) is a far better buy, especially if 2027's artificial intelligence (AI) spending dwarfs 2026's figures. Investors are already seeing signs of this happening.
Image source: The Motley Fool.
2027 is shaping up to be another banner year for Nvidia Nvidia has risen to become the world's largest company thanks to its dominance in the AI computing space. Its graphics processing units (GPUs) are widely considered the best computing units available and are utilized by nearly every major AI company.
Later this year, Nvidia's next generation of chips launches, which will drive even more growth. The Rubin chip architecture promises huge improvements, with an estimated 10 times cheaper cost to run AI inference and 4 times cheaper cost to train AI models. Those gains will drive some companies to upgrade the existing technology, and should also lead to huge improvements in future AI models. The new architecture will also bring a price hike, which will boost Nvidia's revenue, leading to more growth.
Today's Change
(
-2.22
%) $
-4.41
Current Price
$
194.59
However, there's another source of growth available as well: increased spending. The more AI companies spend on computing infrastructure, the better an investment Nvidia will be. Next year, Nvidia believes that the AI hyperscalers will spend around $1 trillion on data center capital expenditures. That's up from $650 billion this year, and that increased spending will be exactly what the stock needs to reach new heights.
But don't just take Nvidia's word for it. One of the AI hyperscalers, Alphabet, told investors they should expect "significantly" higher capital expenditures in 2027 versus 2026. For reference, Alphabet plans to spend between $180 billion and $190 billion on data centers this year. That should lead to more gains for Nvidia's stock, as none of the growth looks priced into its stock right now.
NVDA PE Ratio (Forward) data by YCharts
Nvidia's shares trade for about 23 times forward earnings, just barely more expensive than the S&P 500 at 22. If next year's earnings projections are used, this metric tumbles to a mere 16 times forward earnings.
That's a low price to pay, and Nvidia's stock stands to rise throughout the remainder of 2026 and into 2027 to normal levels. That will lead to strong gains, making Nvidia a great stock to buy now and a far better investment than SpaceX.
NVIDIA’s (NASDAQ:NVDA | NVDA Price Prediction) setup heading into the back half of 2026 mirrors what drove the stock higher in 2025: revenue accelerating, margins holding, and hyperscaler demand outrunning supply. The pullback has reset expectations, and our model suggests the market is underpricing the next 12 months.
Our 24/7 Wall St. price target for Nvidia is $251.55, implying meaningful upside from current levels. Confidence is high, and we rate the stock a buy.
24/7 Wall St. Price Target Summary Metric Value Current Price $199.00 24/7 Wall St. Price Target $251.55 Upside 26.41% Recommendation BUY Confidence Level 90% The 24/7 Wall St. price target reflects forward earnings power, analyst consensus, and proprietary 247Factor adjustments. With 58 buy ratings against just two holds and one sell, Wall Street consensus is one of the most one-sided we track. Our target sits below the Street’s $298.93 average because we apply a more disciplined multiple to forward earnings.
The Pullback That Reset the Setup NVIDIA shares are down 2.76% over the past week and 7.48% over the past month, yet still hold a 6.83% gain year to date and a 34.73% return over the past year. The stock trades roughly 27% below its 52-week high of $236.26, with a 52-week low of $151.29.
Fundamentals tell a stronger story than the chart. Q1 FY2027 revenue reached $81.615 billion, growing 85.23% year over year and beating the $79.116 billion estimate. Non-GAAP EPS of $1.87 topped consensus by 5.42%, the fourth consecutive beat.
Data Center revenue hit $75.246 billion, with Networking up 199% YoY. Management guided Q2 to $91 billion, a sharp acceleration from current levels.
The Case for Higher Upside The bull case rests on the AI capex cycle running hotter and longer than current models assume. Jensen Huang called “The buildout of AI factories, the largest infrastructure expansion in human history,” a phrase backed by $119 billion in supply commitments.
New Vera Rubin scientific computing platforms, an OpenAI partnership covering 10 gigawatts of systems, a multiyear Meta agreement, and CoreWeave’s expansion to 5+ gigawatts by 2030 sit outside near-term consensus.
Wall Street’s $298.93 average target and our internal bull scenario of $261.50 within 12 months reflect this. If forward EPS settles closer to $10 and the multiple holds at 30x, the stock can clear $300.
The Risks Worth Watching The bear case centers on custom silicon competition and capex digestion. OpenAI’s Jalapeño chip with Broadcom, Qualcomm’s expanded data-center portfolio, and AMD’s Rackspace deal point to hyperscaler diversification.
Reddit sentiment briefly fell to 22 (bearish) in late June around losses in AI names, and composite sentiment has declined 9.88 points over seven days. Insider activity has shown net selling across nine recent transactions.
While competitive pressure is real, NVIDIA’s 75% non-GAAP gross margin and PEG of 0.616 suggest the stock is far from priced for perfection. Our bear scenario lands at $216.93, still above current levels.
NVIDIA Price Prediction 2026-2030 The 24/7 Wall St. price target of $251.55 reflects high conviction, with a buy recommendation at 90% confidence. The factor tipping the scale is the magnitude of the Q2 guide. A $91 billion quarter validates the multiyear thesis even with China data-center compute excluded.
The setup looks constructive for investors comfortable with a 2.2 beta and the China headline overhang. The thesis weakens if hyperscaler custom silicon meaningfully reduces NVIDIA’s revenue share inside two years, an outcome the current numbers do not yet support.
Here is where our model projects NVIDIA could trade, assuming current growth and margin trajectories hold.
Year 24/7 Wall St. Price Target 2026 $251.55 2027 $285 2028 $320 2029 $360 2030 $394.73 These projections assume NVIDIA continues executing on Blackwell, Vera Rubin, and platform expansion into robotics and sovereign AI. Significant upside could come from agentic AI monetization across hyperscalers. Significant downside could come from a sustained capex pause or a structural shift toward custom inference silicon.
Nvidia NVDA stock fell on Thursday, giving up premarket gains as investors weighed growing competition in the artificial intelligence chip market despite another wave of enthusiasm across the broader AI sector.
The stock was down 1.3% at $196.76 in early trading after closing 0.5% lower in the previous session.
The decline came even as memory-chip stocks advanced following stronger-than-expected results from Micron Technology, which helped lift sentiment across parts of the semiconductor industry.
Several of Nvidia's major peers also traded lower. Shares of Advanced Micro Devices and Intel were in the red alongside the AI chip leader.
While Nvidia continues to dominate the market for artificial intelligence accelerators, investors are increasingly paying attention to efforts by major technology companies to reduce their dependence on the company's hardware.
The latest development came on Wednesday when OpenAI and Broadcom unveiled a custom artificial intelligence chip called Jalapeño.
The processor marks OpenAI's first entry into AI silicon development and will be used primarily for inference workloads, the computational process of delivering AI responses to users through ChatGPT and other applications.
According to OpenAI President Greg Brockman, the chip was developed rapidly with assistance from the company's own AI systems.
"The degree to which our models have been able to accelerate it was very surprising to us," Brockman said during an interview with CNBC.
Brockman said the chip was designed from end to end in approximately nine months.
The project highlights a broader trend across the artificial intelligence industry as leading technology companies and AI developers seek greater control over their computing infrastructure.
The OpenAI partnership further strengthens Broadcom's position in the growing market for custom AI chips.
Broadcom has emerged as one of the major beneficiaries of the generative AI boom by helping hyperscalers and frontier AI laboratories develop application-specific processors tailored to their own workloads.
Shares of Broadcom have risen about 10% this year and have increased nearly sevenfold since the end of 2022 as demand for AI infrastructure has surged.
The company has become a key partner for organizations looking to supplement or partially replace standard AI hardware deployments with custom-designed silicon.
Meanwhile, Qualcomm recently announced supply agreements involving Microsoft and Meta Platforms, adding to investor concerns that large technology companies are diversifying their AI hardware strategies.
Nvidia remains the industry leaderDespite the growing number of competitors, there is little evidence that Nvidia has lost meaningful business.
The company's graphics processing units remain the preferred option for many artificial intelligence training workloads, and major technology companies continue to commit substantial spending toward Nvidia-based infrastructure.
Many hyperscalers and AI developers have already announced plans to deploy Nvidia's next-generation Vera Rubin platform, which is expected to play a central role in future AI data center buildouts.
Nevertheless, investors appear increasingly focused on the long-term implications of custom chip development.
Humanoid robots are getting smarter and moving closer to the real world. But before they can work alongside humans, Nvidia says they need something even more important: the ability to recognize danger and react in an instant.
The SpaceX IPO and its ripple effects across the ETF landscape were front and center on this week’s ETF Prime. Host Nate Geraci welcomed Zeno Mercer, head of robotics and AI research at VettaFi, and Paul Baiocchi, head of fund sales and strategy at SS&C ALPS Advisors.
Key Takeaways: SpaceX IPO’d at $135, surged 50%, and now trades near $155 at a roughly $2 trillion valuation. Mercer warned that MANGOS ETFs exclude key players like Amazon and carry concentrated valuation risk. Baiocchi flagged S&P 500 concentration risk and spotlighted EQL as a defensive counterweight. SpaceX IPO’d at $135 per share, popped roughly 50%, and now trades near $155 at a $2 trillion valuation. Mercer noted that Musk’s target of $1 trillion in annual SpaceX revenue by 2030 represents a 53-fold jump in five years and faces real competition, including a satellite venture between Delta and Amazon.
See more: SpaceX Takes Center Stage in HALX June Rebalance
On the wave of newly filed MANGOS ETFs, covering Meta, Anthropic, Nvidia, Google, OpenAI, and SpaceX, Mercer said that the basket captures much of the AI value chain but omits key players and carries concentrated valuation risk.
He also argued that the physical AI opportunity is underappreciated, pointing to mobile warehouse robots, drones, and global system integrators as overlooked beneficiaries. On the other side of that trade, he noted that the iShares Expanded Tech Software Sector ETF (IGV) is down 17% this year as AI advancement pressures legacy software as a service platforms.
Concentration Risk and Real-Asset Beneficiaries Baiocchi said the SpaceX IPO frenzy mirrors the dot-com era, noting an unprecedented wave of client calls requesting SpaceX allocations. He also flagged index concentration risk, with three tech-heavy sectors now accounting for more than 50% of the S&P 500.
To address that imbalance, he spotlighted the ALPS Equal Sector Weight ETF (EQL), which equally weights the S&P 500’s 11 Global Industry Classification Standard sectors and recently converted from a fund-of-funds to direct stock replication, lowering costs.
He also highlighted the ALPS Electrification Infrastructure ETF (ELFY) as a play on AI’s power demand, pointing to a Microsoft and Chevron data center power deal as recent evidence of the theme.
The Iran conflict, he added, has spotlighted North American midstream infrastructure, benefiting both the Alerian MLP ETF (AMLP) and the Alerian Energy Infrastructure ETF (ENFR).
For more ETF Prime podcast episodes, visit our ETF Prime Content Hub.
VettaFi LLC (“VettaFi”) is the index provider for AMLP, EQL, ELFY and ENFR, for which it receives an index licensing fee. However, AMLP, EQL, ELFY and ENFR are not issued, sponsored, endorsed, or sold by VettaFi, and VettaFi has no obligation or liability in connection with the issuance, administration, marketing, or trading of AMLP, EQL, ELFY and ENFR.
Mid-year is when serious investors stop trading the headlines and start thinking about the next decade. June 2026 has handed long-term buyers a useful gift: meaningful pullbacks in some of the most important AI platforms despite fundamentals that keep getting stronger. Three names stand out as platform-scale businesses already monetizing AI at scale, with runways that extend well beyond this quarter or even this year.
The setup matters. Goldman Sachs Asset Management’s 2026 outlook frames the central question this way: growth based on long-term transformative investments may be masking the true nature of the underlying real economy, and getting the AI capex call right is the key factor for 2026. The three picks below are levered to that capex cycle from three different angles: the chip layer, the cloud layer, and the application/ad layer.
NVIDIA (NVDA) NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) trades at $199.45, roughly 27% below its 52-week high of $236.26. That is a meaningful entry discount on a business that just printed Q1 FY27 revenue of $81.61 billion, up 85% year over year, with Data Center revenue of $75.25 billion and networking up 199%.
The bull case is straightforward. Hyperscaler AI capex is locked in, and NVIDIA is the toll booth. CEO Jensen Huang called it “the largest infrastructure expansion in human history”, and the numbers back him: $119.0 billion in total supply-related commitments, 75% non-GAAP gross margins, and a board that just authorized an additional $80 billion buyback and raised the dividend from $0.01 to $0.25 per share quarterly. Analyst consensus is 95% bullish with a $298.93 target price.
The risk: Q2 FY27 guidance of $91.0 billion ± 2% excludes China data center compute entirely, and export restrictions remain the single largest swing factor on the outlook. Buyers here are paying for the rest-of-world AI build, not Beijing.
Amazon (AMZN) Amazon (NASDAQ:AMZN) sits at $237.27, 12% below its $278.56 52-week high. The AWS reacceleration story is finally showing up in the numbers: Q1 2026 AWS revenue of $37.59 billion grew 28%, the fastest pace in 15 quarters, at a 38% operating margin.
The platform story has three legs now. AWS is reaccelerating with landmark compute commitments from OpenAI, Anthropic, and Meta. The custom silicon business (Graviton, Trainium, Nitro) crossed a $20 billion annual revenue run rate, growing triple digits year over year. And advertising hit $17.24 billion in Q1, up 24%, on a trailing-twelve-month base above $70 billion. CEO Andy Jassy framed the moment: “We’re in the middle of some of the biggest inflections of our lifetime.” Analyst sentiment is 94% bullish with a $312.99 consensus target.
The risk is the capex bill. Amazon is guiding to roughly $200 billion in 2026 capex, which has already compressed TTM free cash flow to $1.2 billion, down 95% year over year. Long-term debt has climbed to $119.1 billion. Investors buying today are funding an infrastructure cycle whose returns won’t be obvious for years.
Meta Platforms (META) Meta Platforms (NASDAQ:META) is the most contrarian pick of the three. Shares trade at $560.74, down 15% year to date and 19% over the past twelve months. That weakness has happened alongside Q1 2026 revenue growth of 33% and ad revenue of $55.02 billion growing 33%, with ad impressions up 19% and price per ad up 12%.
The bull case rests on three pillars. First, the engagement base: 3.56 billion Family of Apps daily active people, with Morningstar pegging the network at close to 4 billion monthly active users. Second, profitability: operating income of $22.87 billion grew 30%, and the company expects full-year 2026 operating income to exceed 2025 levels. Third, valuation: Morningstar rates Meta 31% undervalued against an $850 fair value estimate as of June 8, 2026, and analyst consensus sits at 89% bullish with an $827.32 target price. CEO Mark Zuckerberg framed the strategy bluntly: “We’re on track to deliver personal superintelligence to billions of people.”
The risk is the spend behind that ambition. 2026 capex guidance was raised to $125-145 billion, Reality Labs lost $4.03 billion in Q1 alone, and EU/US regulatory and youth-litigation overhangs have not gone away. Sentiment trackers register the chill: Meta’s composite prediction score sits at 43.84, neutral with a 7-day change of -15.42.
What to Watch From Here The thread connecting these three is platform durability. NVIDIA owns the silicon, Amazon owns the cloud rails plus a fast-growing chip line, and Meta owns the largest attention surface on the planet. Each is plowing record capital into AI. The earnings prints over the next two quarters, capex absorption, AWS growth rate sustainability, and Meta’s ad pricing trajectory, will tell investors whether the spend is producing the durable economic moats the bull case requires.
Tel Aviv, Israel--(Newsfile Corp. - June 25, 2026) - Eco Wave Power Global AB is pleased to share that NVIDIA has published a corporate blog featuring the Company titled "Eco Wave Power Turns Waves Into Watts With NVIDIA AI Infrastructure and Digital Twins."
Read the full article:
https://blogs.nvidia.com/blog/eco-wave-power-ai-digital-twins/
For convenience, the full text of the NVIDIA article is reproduced below:
Eco Wave Power Turns Waves Into Watts With NVIDIA AI Infrastructure and Digital Twins
June 22, 2026 by Tenika Versey Walker
The next era of AI will not be defined by compute alone. Its growth will be determined by energy.
As accelerated computing scales across AI factories, agentic AI, industrial AI, edge computing and physical AI - including robotics and autonomous systems - global electricity demand is rising at unprecedented speed.
In many regions, expanding grid infrastructure to meet that need requires years of permitting, transmission upgrades, land acquisition and capital investment.
This challenge is reshaping how the world thinks about energy infrastructure for AI.
Eco Wave Power, a member of the NVIDIA Inception startup program's Sustainable Futures initiative, is developing technology - powered by NVIDIA AI infrastructure and digital twins - that converts energy from ocean waves into clean electricity using existing marine infrastructure. By using already-built coastal structures, wave energy generation can be deployed closer to areas with growing power demand - including ports, industrial zones and future AI infrastructure hubs.
"Wave energy is one of the largest renewable energy sources that exists," said Inna Braverman, cofounder and CEO of Eco Wave Power. "Everybody wants it, but nobody can do it, so I looked at the current problems with harnessing wave power and I asked: How do we simplify it?"
Turning the Sea Into a Power Source
Harnessing Earth's natural cycles for power generation isn't a new concept. Wind and solar energy have been well established industries for decades.
Waves are on the way to completing this trifecta of power-producing elements.
In the U.S. alone, wave energy could produce over 60% of annual energy consumption, according to the Energy Information Administration.
It all starts with floaters - noninvasive floating infrastructure attached to breakwaters or sea walls to capture the power generated by waves breaking against the shoreline.
The density of seawater is roughly 800x the density of air, allowing larger amounts of energy to be generated using much smaller devices than wind turbines.
The next step is managing and distributing that power. While previous companies faced a bottleneck at this stage - due to having their computer hardware in the floater, leading to potential damages during rough currents - Eco Wave Power puts its computers, sensors, hydraulic conversion and electric parts on land at centers, keeping expensive hardware dry and safe from storms.
"Wave energy is the least intermittent source of renewable energy," Braverman said. "Solar energy - for example - is great, but you have night, winter, cloud coverage and pollution that all impact production. With wave energy, you can generate around the clock."
AI Wave Energy Layer Using NVIDIA Omniverse Libraries and Accelerated Compute
As AI infrastructure expands, energy systems themselves are becoming increasingly intelligent.
Digital twins of wave patterns and floating infrastructure - built with NVIDIA Omniverse libraries - can simulate wave conditions, structural behavior, deployment configurations and operational scenarios before physical installation begins. These virtual environments can help optimize engineering decisions, reduce deployment risk and accelerate infrastructure planning.
See the Video Player embedded within the NVIDIA corporate blog.
At the operational layer, NVIDIA accelerated computing and AI technologies enable real-time optimization of wave energy systems through predictive analytics, anomaly detection, environmental forecasting and predictive maintenance. AI models can continuously analyze ocean conditions, equipment performance and energy generation patterns to improve efficiency and operational resilience.
AI can also orchestrate energy-aware computing infrastructure by aligning energy-intensive workloads with periods of stronger renewable generation and dynamically optimizing power utilization across distributed systems.
Ocean Powered Data Centers on the Horizon
Eco Wave Power operates projects in Jaffa Port, Israel, created in collaboration with EDF Power Solutions and the Israeli Energy Ministry, and in the Port of Los Angeles, developed in collaboration with AltaSea and Shell. Eco Wave Power is also developing new projects in Portugal at the Port of Leixões, Suao Port in Taiwan, and Mumbai, India, with Bharat Petroleum.
Wave power has already demonstrated its ability to handle consumer energy needs - and is now showing potential to support data centers.
"We have a possibility to link AI factories directly to wave energy, because a lot of data centers are moving toward the coast," Braverman said. "They need cooling and water, so they're now located in ports."
Pilots are already underway at the port of Los Angeles to showcase how wave energy can be the sole power source for a data center without tapping into the existing grid energy.
AI software serves as the control layer for this data center pilot, planning compute tasks based on the available power supply. For example, the software can monitor and predict when waves will be stronger throughout the week based on weather patterns - and accordingly allocate more intensive compute tasks for these periods.
"We exist, we work, we're grid connected and we have so much of this resource," Braverman said. "The energy is needed now, so I think we're in the right place at the right time and we're innovative, but we're not futuristic, and that's what sets us apart."
Explore how NVIDIA is driving the future of energy.
About Eco Wave Power Global AB (publ)
Eco Wave Power Global is a pioneering onshore wave energy company that converts ocean and sea waves into clean, reliable, and cost-efficient electricity using its patented technology. By generating renewable power directly from existing coastal infrastructure such as breakwaters, jetties, and piers, Eco Wave Power enables sustainable electricity production in close proximity to coastal cities, ports, and energy-intensive infrastructure.
As global electricity demand continues to rise, driven in part by the rapid growth of artificial intelligence, data centers, and digital infrastructure, Eco Wave Power is positioning its technology as a scalable, nearshore renewable energy solution capable of supporting next-generation power needs.
With a mission to accelerate the global transition to renewable energy while supporting the next generation of digital and industrial infrastructure, Eco Wave Power developed and operates Israel's first grid-connected wave energy power station, recognized as a "Pioneering Technology" by the Israeli Ministry of Energy and co-funded by EDF Power Solutions. In the United States, the Company recently launched the first-ever onshore wave energy pilot station at the Port of Los Angeles, in collaboration with Shell Marine Renewable Energy.
Eco Wave Power (NASDAQ: WAVE) is expanding globally with projects planned in Portugal, Taiwan, and India, representing a project pipeline of 404.7 MW. The Company has received international recognition and support from organizations including the European Union Regional Development Fund, Innovate UK, and the EU Horizon 2020 program, and was honored with the United Nations Global Climate Action Award.
Eco Wave Power's American Depositary Shares (ADSs) are traded on the Nasdaq Capital Market under the ticker symbol "WAVE."
Note: Information available on or through the websites mentioned herein does not form part of this press release.
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the "safe harbor" provisions of the U.S. Private Securities Litigation Reform Act of 1995 and other Federal securities laws. For example, Eco Wave Power (NASDAQ: WAVE) is using forward-looking statements in this press release when it discusses the possibility the Company can link wave energy directly to AI factories and data centers, its development of new projects in Portugal, Taiwan, and India, and the possibility of wave energy to serve as a sole power source for data centers without tapping into the existing grid. Forward-looking statements can be identified by words such as: "anticipate," "intend," "plan," "goal," "seek," "believe," "project," "estimate," "expect," "strategy," "future," "likely," "may," "should," "will", or variations of such words, and similar references to future periods. These forward-looking statements and their implications are neither historical facts nor assurances of future performance and are based on the current expectations of the management of Eco Wave Power and are subject to a number of factors, uncertainties and changes in circumstances that are difficult to predict and may be outside of Eco Wave Power's control that could cause actual results to differ materially from those described in the forward-looking statements. Therefore, you should not rely on any of these forward-looking statements. Except as otherwise required by law, Eco Wave Power undertakes no obligation to publicly release any revisions to these forward-looking statements to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events. More detailed information about the risks and uncertainties affecting Eco Wave Power is contained under the heading "Risk Factors" in Eco Wave Power's Annual Report on Form 20-F for the fiscal year ended December 31, 2025 filed with the SEC on March 12, 2026, which is available on the SEC's website, www.sec.gov, and other documents filed or furnished to the SEC. Any forward-looking statement made in this press release speaks only as of the date hereof. References and links to websites have been provided as a convenience and the information contained on such websites is not incorporated by reference into this press release.
To view the source version of this press release, please visit https://www.newsfilecorp.com/release/302852
Source: Eco Wave Power Global AB (publ)
Ready to Announce with Confidence? Send us a message and a member of our TMX Newsfile team will contact you to discuss your needs.
NEW YORK--(BUSINESS WIRE)--Amid evolving labor shortages and supply chain dynamics, manufacturers are focused on delivering more uptime with fewer resources — while many of the systems guiding critical maintenance decisions remain largely manual and fragmented. Dataiku, The Platform for AI Success, today announced a new Manufacturing AI Blueprint, Maintenance Scheduling Assistant, built with NVIDIA AI to help industrial organizations modernize how maintenance decisions are made.Designed for glob.
Nvidia (NASDAQ: NVDA) is paying its first boosted dividend tomorrow, June 26, 2026, marking the commencement of its new share buyback strategy announced in March.
As part of the new program, the chipmaker plans to deploy 50% of its free cash flow toward stock buybacks and dividends this year as it restarts manufacturing tied to the new orders.
Prior to the hike, 100 shares earned only a symbolic sum – $1 per quarter at the old $0.01 rate, to be precise. Now, the same investment nets $25 per quarter, or $100 annually if the new payout is maintained.
As such, tomorrow’s Nvidia stock dividend represents an increase of no less than 2,400% from the previous one issued in April, according to DivvyDiary data.
Nvidia dividends calendar. Source: DivvyDiary A new milestone in Nvidia dividend history For context, with 24.22 billion Nvidia shares outstanding as of press time, more or less $6.055 billion will be distributed to shareholders.
These new initiatives put Nvidia more in line with the broader industry, as, for example, Meta (NASDAQ: META) is reportedly planning between $115 billion and $135 billion in capital expenditures as well.
The last time management increased the payout was in June 2024, when they lifted it from $0.004 to $0.01. Currently, the chipmaker offers an annual payout of $0.28 per share, which is a dividend yield of 0.14% (verseus the industry average of 1.37%).
One day, before the historic Nvidia dividend payout date, the shares are up 1.2% in-premarket, the optimism generated by both tomorrow’s shareholder reward and a broader rally in global chip shares following Micron’s (NASDAQ:MU) strongest quarter on record.
Featured image via Shutterstock
Best Crypto Exchange for Intermediate Traders and Investors
Invest in cryptocurrencies and 3,000+ other assets including stocks and precious metals.
0% commission on stocks - buy in bulk or just a fraction from as little as $10. Other fees apply. For more information, visit etoro.com/trading/fees.
Copy top-performing traders in real time, automatically.
eToro USA is registered with FINRA for securities trading.
30+ million Users worldwide
eToro is a multi-asset investment platform. The value of your investments may go up or down. Your capital is at risk. Don’t invest unless you’re prepared to lose all the money you invest. This is a high-risk investment and you should not expect to be protected if something goes wrong. Take 2 mins to learn more.
Join Finbold's newsroom, become a Sales Executive today! Apply now to join Finbold as a crypto/finance news writer!
NVIDIA's 2,400% dividend increase makes it the second-largest dividend payer in the U.S., highlighting how technology companies are reshaping the dividend growth landscape. The WisdomTree U.S. Quality Dividend Growth Fund (DGRW) benefits from exposure to dividend initiators like NVIDIA, Alphabet, and Meta that many backward-looking dividend growth screens still miss. By emphasizing quality and future growth potential over dividend history, DGRW aims to capture tomorrow's dividend leaders before they become widely recognized.
After an exceptional Q1 FY27 results, NVIDIA looks favorably positioned to maintain its topline momentum further, driven by robust demand for Blackwell architecture across hyperscalers and enterprises. NVDA's industry-leading margins are also expected to remain resilient, supported by strong pricing power and a favorable mix of high-value AI systems, despite continued elevated R&D spending. Following recent underperformance and multiple compression, NVDA trades at a compelling 22.3x forward P/E, well below its five-year average and close peers valuation.
Nvidia (NVDA 0.93%) finds itself in an enviable but challenging position. Due to its $4.9 trillion market cap, growth investors seeking gains of tenfold or more are now more likely to seek smaller companies that could increase by such multiples without reaching record sizes.
Fortunately, that high market cap, along with Nvidia's growth and valuation, could attract a new group of investors who want growth without sacrificing safety. This arguably means that a certain type of person should buy this semiconductor stock at current levels.
Image source: The Motley Fool.
The right person for Nvidia stock Thanks to a variety of factors, younger, risk-averse investors should consider Nvidia. Many of these potential buyers see that Nvidia grew revenue by 85% in the first quarter of fiscal 2027 (ended April 26) and assume that the stock is better suited for growth investors.
However, a look at other metrics tells a different story. Thanks in part to its huge size (and some of the hesitation surrounding that), the price-to-earnings ratio (P/E) is 32, modest considering its growth. Moreover, its forward P/E of 23 indicates the financials are on track to continue improving, making the stock more attractive.
And investors who worry about Nvidia's stability should look no further than its $80 billion in liquidity. That alone gives it one of the safest balance sheets among public companies and should ease worries about the company if it faces unexpected challenges.
Today's Change
(
-0.93
%) $
-1.85
Current Price
$
198.19
Furthermore, while those factors bolster the bull case for investors, one might wonder why they should be younger? Someone can profit from Nvidia stock at nearly any age.
The answer comes down to investment priorities, as older shareholders often depend on dividend income from stocks. At a dividend yield of just under 0.5%, Nvidia is well below the S&P 500 average of 1.1%. That is less of a concern for younger persons trying to build retirement nest eggs.
Still, more investors should watch Nvidia's dividend. It recently increased its annual payout from $0.04 per share to $1 per share, a 2,400% increase. That heightened focus on the payout may eventually make it more attractive to income investors over time.
Moving forward with Nvidia stock Now that the law of large numbers could slow Nvidia's growth, the stock's evolving nature has made it ideal for younger investors trying to minimize risk.
Its current rate of revenue increases makes it look like a riskier growth stock. However, characteristics like a falling P/E ratio and a huge liquidity position remain attractive to more conservative investors. Moreover, the lower-than-average dividend yield is less of a deterrent for younger traders who are less likely to need income from that source.
Ultimately, by buying Nvidia stock, conservative investors can benefit from rapid growth without taking on the risks that usually accompany such stocks.
The primary distinction between Vanguard S&P 500 ETF (VOO 0.21%) and State Street SPDR S&P 500 ETF (SPY 0.19%) centers on cost and asset scale, as both provide nearly identical exposure to large-cap U.S. equities.
These two heavyweights represent the most popular vehicles for owning the S&P 500 Index. While SPY is a historical pioneer favored by institutional traders for its deep liquidity, VOO has become a cornerstone for long-term individual investors seeking to minimize management costs while capturing broad market growth.
Snapshot (cost & size)MetricSPYVOOIssuerSPDRVanguardExpense ratio0.09%0.03%1-yr return (as of June 24, 2026)21.7%21.7%Dividend yield1%1%Beta1.001.00AUM$769 billion$1.7 trillionBeta measures price volatility relative to the S&P 500; beta is calculated from five-year monthly returns. The 1-yr return represents total return over the trailing 12 months. Dividend yield is the trailing-12-month distribution yield.
The Vanguard fund is the more affordable choice with an expense ratio of 0.03%, which is one-third the cost of the SPDR ETF. Opinions may vary on how meaningful that cost differential is.
Performance & risk comparisonMetricSPYVOOMax drawdown (5 yr)(24.5%)(24.5%)Growth of $1,000 over 5 years (total return)$1,926$1,930What's insideThe Vanguard ETF holds 505 stocks and seeks to replicate the returns of the S&P 500 Index. Its largest positions include Nvidia (NVDA 0.93%) at 7.9%, Apple (AAPL 0.43%) at 7.05%, and Microsoft (MSFT 2.37%) at 5.15%. This fund, launched in 2010, concentrates its assets in technology (39%), financial services (11%), and communication services (10%). It has paid $7.13 per share in dividends over the trailing 12 months and maintained a 52-week trading range between $545.75 and $699.15.
The SPDR fund manages a portfolio of 504 holdings. Top holdings include Nvidia at 7.8%, Apple at 6.82%, and Microsoft at 4.41%. Launched in 1993, the ETF has a similar sector distribution across technology (39%), financial services (11%), and communication services (11%). It has a trailing-12-month dividend payout of $9.29 per share and a 52-week trading range between $591.89 and $760.40.
For more guidance on ETF investing, check out the full guide at this link.
What this means for investorsWith apologies to the Bard:
"Two fund giants, both alike in dignity,
On fair Wall Street, where we lay our scene."
Given these two ETFs both track the S&P 500, there's no real difference in performance or dividend yield. The three primary distinctions between SPY and VOO are cost, AUM, and average trading volume.
Cost: VOO has a rock-bottom 0.03% expense ratio. SPY charges 0.09%. So $10,000 invested in VOO would cost you $3 annnually. For SPY, it would be $9. I personally don't think saving $6 on a $10,000 investment is going to make a massive difference in your long-term returns, but you might disagree.
AUM: VOO is a giant, with $1.7 trillion in AUM. SPY is not even half as large.
Average trading volume: SPY is much smaller than VOO in terms of AUM, but it has nearly seven times as much average trading volume. So if liquidity is important to you, SPY would probably be a more attractive investment.
Erin Kennedy has positions in Apple and Vanguard S&P 500 ETF. The Motley Fool has positions in and recommends Apple, Microsoft, Nvidia, and Vanguard S&P 500 ETF. The Motley Fool has a disclosure policy.
Nvidia CEO Jensen Huang Chris Jung/NurPhoto via Getty Images Nvidia's dominance in AI is moving beyond chips.
For the first time, the company became the top vendor by revenue in data center Ethernet switches — the networking gear that helps connect AI chips inside data centers, according to market research firm IDC.
This market is growing fast because cloud giants and other large businesses are pouring hundreds of billions into building out AI data centers. IDC research vice president Paul Nicholson called Nvidia's ascension "one of the most significant vendor landscape shifts IDC has tracked in enterprise networking."
In the first quarter of 2026, Nvidia generated $2.1 billion in data center Ethernet switch revenue — a 21.5% share of the market. That's up from 4% in the first quarter of 2024, said IDC senior research manager Brandon Butler.
Nvidia has pushed ahead of rivals like Arista Networks, which held a 20.7% share of the data center Ethernet switch market in the first quarter of this year. Other major players include Cisco, Huawei, and HPE.
The data center Ethernet switch market totaled $10 billion in the first quarter, according to IDC, growing 61% from a year earlier.
IDC attributed Nvidia's growth in networking revenue to its Spectrum-X product, "a tightly integrated system" that's designed to work closely with its AI chips, Butler said.
Butler said Nvidia's approach appeals to cloud giants looking to build quickly and avoid piecing together parts from multiple vendors. The trend also reflects a broader shift of companies buying networking and computing products together, IDC said.
The chip giant has increasingly highlighted networking as a major growth driver. At a shareholder meeting on Wednesday, Nvidia CEO Jensen Huang said Spectrum-X is "now larger than all other Ethernet networking peers combined."
The comments echoed Nvidia's most recent earnings call in May, when chief financial officer Colette Kress said the company's broader data center networking revenue had tripled to $15 billion from the previous year.
Nvidia's networking business traces back to its 2019 acquisition of Mellanox, which gave the company a foothold in data center networking before the AI boom took off.
Nvidia's lead isn't guaranteed. Cloud giants are increasingly looking to diversify their supplier base, Butler said, while businesses may lean on existing relationships with networking providers as they ramp up their infrastructure.
Have a tip? Contact this reporter via email at [email protected] or Signal at @geoffweiss.25. Use a personal email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing information securely.
Read next
Geoff Weiss You're currently following this author! Want to unfollow? Unsubscribe via the link in your email.
Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.
Nvidia (NVDA 0.93%) has built an artificial intelligence (AI) empire, offering graphics processing units (GPUs) that power essential tasks like the training of AI models and providing a wide range of related products and services. All of this has sent earnings soaring in recent years -- and the stock price has followed.
Customers flock to Nvidia for these top AI products, and the company has consistently remained No. 1 in the AI chip market. In recent times, Nvidia says it also aims to lead in central processing units (CPUs), a market that's been dominated by Intel and Advanced Micro Devices. This represents a $200 billion opportunity, and Nvidia has said it's on track to accomplish this goal thanks to its first stand-alone CPU, launching later this year.
All of this sounds fantastic, but it's important to remember that Nvidia faces increasing competition from a variety of companies. Will this leader continue to dominate in AI? One number offers a strikingly clear answer.
Image source: Getty Images.
A history of GPU expertise First, let's start with a quick summary of the Nvidia story so far. The company has a long history of GPU expertise, with this chip first serving the gaming market. Nvidia still makes GPUs for gaming, but it has progressively expanded the uses of these high-powered chips over the years. Through the CUDA parallel computing platform, GPUs may be programmed for other needs, and the area of AI has proven to be particularly valuable.
Today, sales of GPUs to data center customers generate the lion's share of Nvidia's revenue. And this doesn't include chips only, but related products such as networking tools, so that Nvidia offers complete AI systems. The company has also designed offerings specifically suited to various industries -- for example, AI platforms that assist healthcare companies with drug discovery.
All of this has helped Nvidia's revenue climb in the double and triple digits in recent years, and it reached a new record of more than $215 billion in the latest fiscal year. In the first quarter of this year, earnings continued to climb, with revenue rising 85% to $81 billion, and net income advancing more than 200% to $58 billion.
So it's not surprising that Nvidia's stock price has also skyrocketed, climbing 900% over five years.
Today's Change
(
-0.93
%) $
-1.85
Current Price
$
198.19
Nvidia faces competition These points all offer us reason for optimism about the future, but we shouldn't ignore the fact that Nvidia faces growing competition. Fellow chip designers, such as AMD, or new-to-the-market players like Cerebras Systems, aim to take market share. And even some of Nvidia's customers might represent a threat as they're designing their own chips. Amazon is a good example. The company has seen such demand for its own chips that it may even consider creating a separate chip business.
Now, let's consider our question: Will Nvidia continue to dominate in AI as the competition mounts and customers are served with more and more options?
One particular number offers a strikingly clear answer. Almost nine of every 10 systems new to the world's fastest supercomputer list are built on Nvidia, according to the latest rankings. This clearly shows that customers continue to turn to Nvidia -- so even though there is plenty of business for rivals to succeed too, so far this hasn't come even close to threatening Nvidia's leadership position.
The data revealed that Nvidia powers 81% -- or more than 400 -- of the world's top 500 fastest supercomputers. This is an increase of 17 systems from the last report, according to Nvidia. The list is updated twice a year.
Moving forward, Nvidia's new presence in CPUs may help it gain even more ground, as it now offers another key element, particularly in the phase of agentic AI. CPUs are the main chips that help guide AI agents as they take action to handle a problem on behalf of humans.
All of this means that, though Nvidia faces competition, customers still see the value of choosing this leader -- and the company's focus on innovation should keep this going. And that's excellent news for investors who've chosen to buy and hold Nvidia for the long term.
Nvidia (NVDA 0.93%) is the most valuable company in the world, and the only one with a market cap of more than $5 trillion. If you had invested $25,000 in it 10 years ago and held on through the ups and downs that followed, you'd have a stake worth more than $4 million today.
However, the stock has been growing at a more modest pace recently. It's up just 7% this year -- almost precisely as much as the broad market S&P 500 index. So is there still a chance that a $25,000 investment in Nvidia made today could make you into a millionaire?
Nvidia is still at the top of its game Nvidia's story is unusual, and its rise to megacap status was unexpected. There were plenty of investors who recognized it as a great company even before the artificial intelligence (AI) trend sent its revenues skyrocketing a few years ago, but at that time, its graphics processing units (GPUs), the basis of generative AI today, were more widely used to power video games, edit video, and mine cryptocurrency.
The stampede of business that came from the AI revolution sent its sales, profits, and stock price into the stratosphere, and the good news is, the revolution is far from over. The company has been reporting accelerating growth, and it's launching new products and architectures at a dizzying pace in its bid to stay ahead of competitors.
Image source: Nvidia.
For instance, it's now rolling out its latest chip architecture, the Vera Rubin line.
That integrated stack, which combines the Rubin GPU with its new Vera CPU (central processing unit), will deliver 35 times higher inference power than the previous architecture, Blackwell. Moreover, even with the new processors set to start shipping in the second half of this year, its Blackwell processors continue to sell at a high rate; Amazon Web Services (AWS) alone is ordering 1 million Blackwell and Vera Rubin chips in its efforts to build capacity for its cloud clients.
It's noteworthy that Nvidia has decided to pursue a new opportunity in CPUs, which will become increasingly more important in data centers geared toward powering agentic AI. CEO Jensen Huang has said that he sees a $200 billion addressable market for the company in CPUs, and that he anticipates $1 trillion in sales of Blackwell and Rubin GPUs alone across 2026 and 2027.
Can it grow fast enough? This is all exciting, but from an investing standpoint, will it be enough to significantly grow your money? As Nvidia's revenue base further expands from its already enormous level, can its growth continue to accelerate?
Nvidia's revenue increased 85% year over year in its fiscal 2027 first quarter (which ended April 26), which is an impressive result. But let's assume that slows down over the next five years. Assuming a compound annual growth rate (CAGR) of 50%, in five years, its revenue would be almost $2 trillion. I would suggest that's unlikely at this stage. Assuming a 30% CAGR, its annual revenue would be $943 billion, which would be more than any other company brings in today.
Today's Change
(
-0.93
%) $
-1.85
Current Price
$
198.19
To me, that sounds like investors should expect a major slowdown in growth soon, and a stock performance that will reflect that. Moreover, even if it does grow that fast, the stock's price-to-sales ratio would almost certainly fall to a much lower level than today's 20. Theorizing a P/S ratio of 10, Nvidia's market cap would be $9.4 trillion in five years, or almost double its size today, and your $25,000 would be worth about $48,460. You'd have to wait a long time to see that stake grow into $1 million, if it could happen at all.
SummaryNVIDIA is a Buy as its base case no longer depends on Chinese data center compute revenue.NVDA’s data center, AI, networking, and platform businesses are compounding strongly ex-China, with Q1 revenue up 85% and robust $91B guidance.China now represents high-value optional upside, not a key valuation pillar; partial reopening or compliant chip sales would further boost upside.Downside risk is limited, with base and bull cases supporting 43–70% upside; key risks are AI buildout slowdown and Rubin ramp delays. Robert Way/iStock Editorial via Getty Images
I am not buying NVIDIA (NVDA) because I hope China will reopen someday. In fact, my argument is almost the opposite: I am buying NVDA because it no longer needs Chinese data center compute revenue
97 Followers
Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.
