Over the last five years, Nvidia (NVDA +1.30%) has been the quintessential millionaire-maker stock -- returning roughly 950% compared to the S&P 500's relatively modest gain of 74%. The company's powerful graphics processing units (GPUs) are the workhorses of the generative artificial intelligence (AI) industry. And its advantages in scale and technology have helped it stay ahead of the competition.
That said, Nvidia's stock price growth is beginning to stall as investors balk at its huge size and pivot to other sides of the AI infrastructure opportunity. Let's dig deeper to see if the company has what it takes to break out of its slump and continue generating market-beating returns.
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Business is still booming The generative AI megatrend shows no signs of slowing anytime soon. In fact, it may be heating up. Analysts at Evercore and Bank of America expect big tech's AI-related capital spending to exceed $1 trillion in 2027 -- up from around $800 billion to $900 billion this year. Most of this money is going to advanced hardware needed to run massive data centers.
Nvidia's chips remain highly relevant, which is reflected in the company's first-quarter earnings results. Revenue jumped 85% year over year to $81.6 billion, which is an incredible number for a business that is already so large. And as in previous quarters, overall growth was driven by growth in the company's data center segment, which recently announced exciting new offerings such as the Vera Rubin Platform, designed to facilitate the rise of agentic AI by removing processing bottlenecks.
Many industry watchers believe agentic AI represents the next phase of the technology. Unlike earlier AI systems, it is designed to independently plan and make decisions with limited human oversight, making it ideal for helping automate a variety of industries. And if the technology takes off as expected, it could help Nvidia maintain its elevated growth rate.
Management is returning value to shareholders Nvidia's success isn't limited to its top line. The company's technological edge gives it strong pricing power and operating leverage. Net income soared 211% year over year to $58.3 billion, and management is getting increasingly serious about returning much of it directly to shareholders.
As of May, Nvidia has increased its cash dividend from just $0.01 per share to $0.25 per share (a yield of around 0.5%). More importantly, management authorized an additional $80 billion in stock repurchases on top of the $38.5 billion remaining from its previous program.
Image source: Getty Images.
Investors tend to love buybacks because they reduce the number of a company's shares outstanding, giving every investor a higher claim on the company's future earnings and cash flow. They tend to encourage stock price growth and, unlike dividends, they aren't taxed as regular income, which can make a tremendous difference over the long term.
Nvidia's huge push toward buybacks marks a sharp divergence from other technology giants like Amazon, Microsoft, and Micron Technology, which are instead plowing cash back into AI-related capital expenditures like data centers or expanded production capacity. Nvidia's strategy is arguably less risky because it relies on internally generated cash instead of debt or dilution like some of the alternatives in the tech industry.
With a market cap of $4.72 trillion, Nvidia isn't a millionaire-maker stock anymore because, even in the best-case scenario, rapid multibagger growth seems unrealistic from such a high level. The company's sky-high margins will also eventually come down as customers substitute in-house solutions for Nvidia products and rivals catch up technologically.
That said, with a forward price-to-earnings (P/E) multiple of just 22.7, most of these challenges are already priced into Nvidia's valuation. And management's aggressive buyback policy will benefit shareholders over the long haul. Investors should view Nvidia stock as a value-oriented pick in the AI industry instead of a big growth opportunity.
In recent years, Nvidia (NVDA +1.30%) has been the hot growth stock that the market has been rallying around, determining the overall path forward. And as it has done well, so too has the S&P 500. The stock has been a lightning rod for growth investors, attracting plenty of investment dollars.
More recently, however, another big name in tech has been rising prominently, and that's Micron Technology (MU +0.90%). Not only has it been generating Nvidia-like returns of late, but there was also plenty of anticipation around its recent earnings results, as investors looked to the numbers to see whether the stock's impressive rally could continue. Is this a sign that Micron has become the new Nvidia, and that it's the new go-to investment for growth investors?
Image source: Getty Images.
Micron has been the better buy in the past five years You might be surprised to learn that over the past five years, Micron has actually outperformed Nvidia. Its gains over that stretch are up around 1,300%, while Nvidia, which has been slowing down of late, is up by 860%. For a while, however, the gap was significant, with Nvidia's gains far exceeding Micron's. It wasn't until the rapid surge this year, with Micron's stock rising almost in a straight line up, that its gains soared past Nvidia's.
There is clearly more hype around Micron these days, not unlike the hype that was around Nvidia a few years ago, when ChatGPT and generative artificial intelligence were in their early stages. Now, with investors focused on memory products and the shortages in that industry, it's Micron that appears to be in the spotlight.
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Why Nvidia may still be the safer option for investors Although Micron has been delivering impressive results in recent quarters due to strong demand for its memory and storage products, that growth isn't likely to be sustainable over the long haul. Micron's revenue rose by 346% in its most recent quarter (which ended on May 28) to $41.5 billion. It was an impressive result, but it was largely due to significantly higher prices for its products; its margins were around 85% versus 38% a year ago.
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Nvidia's growth rate has slowed from the highs it hit in previous years, but it remains strong at 85%, and it isn't dependent on rapidly rising prices. That's why, from a risk standpoint, it may be a more compelling option, because if there's any hint of demand slowing down or if there's no longer a shortage of memory and storage products, Micron's stock could be due for a steep decline, especially given its rapid run-up in value over the past year.
If you asked me which stock would have a better 2026, Nvidia (NVDA +0.93%) or Advanced Micro Devices (AMD +2.74%), I would have said Nvidia without hesitation. If the only thing you had to look at were business results, you'd likely come to the same conclusion as my projection.
However, the market is in love with AMD's stock, and it has trounced Nvidia's year-to-date performance. Since the start of 2026, AMD's stock has risen a jaw-dropping 144%. Nvidia has barely done anything, rising about 4%. Clearly, the market prefers AMD to Nvidia stock.
But will that continue into the latter half of 2026? Let's take a look.
Image source: Getty Images.
AMD is putting up a fight in the AI computing arena AMD and Nvidia are both deeply involved in the AI computing build-out. Nvidia is more exposed than AMD, but AMD still gets over half its revenue from data center-related products. From the start of the AI race, Nvidia's products were hands down better than AMD's. Additionally, Nvidia had its graphics processing unit (GPU) controlling software, CUDA, that was ages ahead of AMD's offering. This allowed Nvidia to capture a large market share, and it became the go-to computing unit for all AI workloads.
AMD has clawed itself back into the mix and launched several exciting products, like its Instinct MI350 series. This landed AMD several deals, including one with OpenAI. All of this added to the hype around AMD's stock indicating that it could become a legit competitor in the AI data center landscape.
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This caused the stock to surge throughout 2026, as the prevailing sentiment is that AMD has caught up with Nvidia. The problem is that that's just not the case.
Nvidia is crushing AMD in nearly every financial metric The "AMD is back" argument falls apart when you compare its results to Nvidia's. In the first quarter, AMD's data center division grew at a respectable 57% year-over-year pace and a 7% quarter-over-quarter pace. Nvidia nearly doubled those results, with data center revenue rising 92% year over year and 21% quarter over quarter. As for size, Nvidia is nearly 15 times larger, with its data center division generating $75.2 billion in Q1, and AMD's totaling $5.8 billion. In the company-wide view, Nvidia is still winning the race.
NVDA Net Income (TTM) data by YCharts.
So, how is Nvidia's stock underperforming AMD's so badly? In my view, the market has become irrational with AMD's stock. After its major run-up, AMD now trades for a shocking 71 times forward earnings. Nvidia trades at a far cheaper and more reasonable 21.6 times forward earnings. That means AMD's earnings must more than triple after 2026's growth is accounted for, just to trade at the same level that Nvidia does today.
That seems like an absurd mismatch of valuation and expectations, and with Nvidia not shrinking at all, it makes AMD seem like a worse stock pick for the future. I'm not betting against AMD stock in any way, as the market can remain irrational longer than I can stay solvent. Still, after looking at AMD and Nvidia, I have a hard time rationalizing investing in AMD versus Nvidia.
AMD appears to have already taken some of Nvidia's market share, according to the stock's sentiment (it really hasn't), while Nvidia appears to be losing every battle it's getting into (it's not). There is a huge mismatch in expectations, and I think investors would be smart to take advantage of it by selling AMD shares and instead investing that into Nvidia's stock, as it looks like a great value right now.
Just because Nvidia is the biggest company in the world, it doesn't mean it has reached a ceiling. It can go far higher, and if expectations come back to reality for other AI competitors, Nvidia's stock is primed to skyrocket.
I've been bullish on the AI CapEx trade for a while, but this rotation is forcing me to reassess nearly every position I own. The Mag 7 are now a drag on the indices.
It has been a frustrating year for Nvidia (NVDA +0.39%) investors, as the tech giant's shares have barely delivered any gains so far in 2026. The PHLX Semiconductor Sector index, for comparison, has registered remarkable gains of 79% this year.
However, it is difficult to justify Nvidia's underperformance in the first half of 2026. The company is on track to deliver better results this fiscal year, driven by the artificial intelligence (AI)-fueled demand for its chips. So, will the market give Nvidia enough credit for its impressive financial performance and help the stock rally in the second half of 2026?
Let's find out.
Image source: The Motley Fool.
Nvidia's Vera Rubin chips could be a catalyst for the stock Nvidia is all set to begin shipments of its next-generation Vera Rubin processors this fall. The company recently noted that Vera Rubin chip systems are now in full production, and demand for these chips appears to be quite healthy. I say this because Nvidia noted earlier this year that it has a $1 trillion order pipeline for the Blackwell and Vera Rubin chip architectures for 2026 and 2027.
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That's a significant upgrade over the $500 billion worth of orders it was anticipating for 2025 and 2026. A nice chunk of those orders is likely to be for the Rubin processors. That's because Nvidia claims that Vera Rubin will deliver 10 times higher performance per watt over Blackwell systems, as reported by CNBC. So, it is easy to see why companies such as Meta Platforms, Anthropic, OpenAI, Amazon, Microsoft, and Google are poised to deploy these chips to run AI workloads in data centers.
What's more, Nvidia is expected to increase the price of Vera Rubin systems by 25%, according to market research and analysis firm The Futurum Group. So, Nvidia's margin profile could improve, leading to a stronger jump in earnings this year. What's worth noting is that Nvidia's earnings are predicted to increase by 88% in fiscal 2027 (which ends in January 2027) to $8.96 per share.
That would be a significant step-up from the 60% earnings growth Nvidia delivered in fiscal 2026. IDC forecasts that the semiconductor industry's revenue could jump by 53% in 2026 to $1.29 trillion. Nvidia, meanwhile, could witness an 82% jump in revenue this fiscal year to $392 billion. So, there is a likelihood that Nvidia's earnings will grow faster than the overall semiconductor market this year. After all, its top-line growth is poised to outpace the industry, and a potential increase in the price of its Vera Rubin systems could lead to a larger increase in earnings than analysts project.
This is precisely why buying Nvidia could prove a smart move after its poor performance in the first half of 2026.
The stock is too cheap to ignore right now With a price-to-earnings ratio of 29, Nvidia stock is an absolute bargain right now. The iShares Semiconductor ETF, which tracks and invests in semiconductor companies, trades at a much more expensive 75 times earnings. This cheap valuation could pave the way for a strong bull run in Nvidia in the second half of the year.
Assuming it trades at even 40 times earnings by the end of the fiscal year and clocks $8.96 in earnings per share, Nvidia's stock price could jump to $358. That's a potential upside of 85%, which is why it would be a good idea to buy this AI stock before it starts rallying in the second half of 2026.
Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Meta Platforms, Microsoft, Nvidia, and iShares Trust-iShares Semiconductor ETF. The Motley Fool has a disclosure policy.
Insights into the Fund's Strategic Moves in Q2 2026 Harbor Capital Appreciation Fund (Trades, Portfolio) recently submitted its N-PORT filing for the second qu
NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) stock has cooled off this summer, but the 24/7 Wall St. price target says the pullback looks like a setup for further upside. Shares closed at $192.53 on June 26, 2026, down 8.62% on the week, even as Wall Street remains overwhelmingly bullish. Nvidia is the most-owned megacap in the AI build, and our model thinks the recent dip widens the runway for further upside.
Our 24/7 Wall St. price target for NVIDIA is $245.91 over the next 12 months, implying 27.73% upside. The recommendation is buy, with a confidence score of 90%, which we consider high.
24/7 Wall St. Price Target Summary Metric Value Current Price $192.53 24/7 Wall St. Price Target $245.91 Upside 27.73% Recommendation BUY Confidence Level 90% A Summer Wobble Inside a Bigger Uptrend NVIDIA is up 24.36% over the past year and 3.36% year to date, but the last month has been ugly, with shares off 9.34%. The stock sits 27% below its 52-week high of $236.26 and well above the $151.29 low.
Fundamentals have not cracked. Q1 FY2027 revenue hit $81.615 billion, up 85.23% year over year, with non-GAAP EPS of $1.87 beating expectations. Data Center revenue reached $75.246 billion, up 92%, with networking revenue tripling at 199% growth. Q2 guidance came in at $91 billion. NVIDIA also launched the BioNeMo Agent Toolkit for life sciences, extending the platform beyond pure compute.
Why Bulls See a Breakout Toward $300 The bull case rests on Blackwell. CEO Jensen Huang called the AI factory buildout “the largest infrastructure expansion in human history”, and NVIDIA has locked in $119 billion in supply commitments. Multigenerational deals with OpenAI (10GW), Anthropic (1GW), Meta, Microsoft, Google Cloud, and Oracle anchor demand into the Vera Rubin platform.
Of 61 covering analysts, 58 rate NVDA Buy or Strong Buy versus just 1 Sell. The Street consensus target is $298.93. If Blackwell 300 ramps at 75% gross margins and Q2 results come in near guidance, the bull scenario points to $259.20, a 34.63% one-year return.
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The Risks Worth Watching The bear case starts with concentration. The model assumes zero China Data Center compute revenue, and further export tightening hits sentiment more than numbers. Supply-chain reliance on TSMC, a planned cash tax jump in Q2, and gross margin risk during architecture transitions are real. Retail conviction is wobbling, with Reddit traffic this month flagging AI stock losses and Chinese model parity on Huawei silicon.
Insider selling has picked up, with 9 recent transactions net selling. Bulls counter that these are routine 10b5-1 trims against $20 billion in Q1 buybacks and a fresh $80 billion repurchase authorization. The bear scenario still produces $212.99, a 10.62% gain.
NVIDIA Price Prediction 2026-2030 At $192.53, the 24/7 Wall St. price target of $245.91 leans on real earnings power rather than relying on multiple expansion, and even the bear case is positive. Key signals to monitor: whether Q2 prints above the $91 billion guide, whether gross margins hold above 73%, and whether export rules expand beyond H20. The current pullback is worth watching closely.
Looking further out, here is where the 24/7 Wall St. price target model projects NVDA could trade, assuming current growth trajectories hold and the AI capex cycle extends through the Vera Rubin generation.
Year 24/7 Wall St. Price Target 2026 $245.91 2027 $285.00 2028 $320.00 2029 $355.00 2030 $391.74 These projections assume NVIDIA holds platform leadership through Vera Rubin and hyperscaler capex grows in line with current commitments. A China policy reversal would be meaningful upside, while a credible domestic Chinese alternative or hyperscaler in-house silicon shift would compress the trajectory.
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The stock market has become noticeably more unsettled over the past month. The S&P 500 closed on Friday at 7,354, down 3.3% from its June 2 record high of 7,609. Ordinarily, a pullback of that size wouldn’t attract much attention. What makes this one different is the surge in investor anxiety beneath the surface.
Volatility in technology stocks has exploded, sentiment has fallen into “Extreme Fear” territory, and options traders are paying up for downside protection at levels rarely seen outside major market selloffs. On the surface, those signals look alarming. Dig a little deeper, though, and they paint a more balanced picture than the headlines suggest.
Wall Street Is Worried About Tech, Not the Entire Market One of the market’s most unusual signals today is the widening gap between the Nasdaq-100 Volatility Index (VXN) and the CBOE Volatility Index (VIX).
Recently, that spread reached 12 points — the widest margin in at least 23 years. That’s even larger than the peaks recorded during the 2008 financial crisis and the pandemic-driven selloff in 2020.
The move has been driven almost entirely by technology stocks. Since early May, the VXN has climbed roughly 43%, while the VIX has risen just 9%. The spread is important.
The Nasdaq-100 is heavily concentrated in mega-cap technology companies such as Nvidia (NASDAQ:NVDA | NVDA Price Prediction), Microsoft (NASDAQ:MSFT), Apple (NASDAQ:AAPL), and other AI leaders. A soaring VXN relative to the VIX suggests traders expect larger swings in those stocks — not necessarily across the broader market. Investors appear to be reassessing lofty valuations rather than preparing for a full-scale market collapse.
That’s a remarkably pessimistic reading considering the S&P 500 remains only 3.7% below its all-time high. During previous periods when the index fell into single digits, markets were suffering far steeper declines.
Options markets also reflect growing caution. The five-day average put-to-call ratio has climbed to 0.84, its highest level since April and well above the readings that prevailed through much of the past year. Investors are clearly buying more downside protection, but they have not yet reached the panic-driven capitulation that often accompanies major market bottoms.
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Fear Is Rising Faster Than the Damage None of this means investors should dismiss the warning signs. A record VXN-VIX spread underscores just how dependent market leadership has become on a handful of large technology companies. If those stocks continue to weaken, they could weigh on the broader indexes.
At the same time, the underlying market has remained surprisingly resilient. Despite heightened volatility, the S&P 500 is still up roughly 7.4% for the year. Outside of technology, many sectors have held up well, suggesting investors are rotating rather than rushing for the exits.
Historically, periods when investor sentiment deteriorates much faster than stock prices have often created attractive opportunities once emotions cool. That’s not a guarantee this time will follow the same script, but it does suggest today’s fear may be running ahead of the market’s actual fundamentals.
Key Takeaway The market is clearly sending caution signals. Tech volatility has reached levels rarely seen in more than two decades, and investor sentiment has swung decisively toward fear.
Yet the actual market damage remains relatively modest. A 3.7% pullback from record highs hardly resembles the kind of washout typically associated with widespread panic.
For long-term investors, this is a reminder to separate emotion from evidence. Maintain diversified exposure, keep cash available to take advantage of opportunities, and focus on companies with durable earnings, strong free cash flow, and reasonable valuations.
Markets rarely feel comfortable near turning points. Right now, fear is making far more noise than prices are — and history suggests that’s often worth paying attention to.
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SHANGHAI, CHINA - JUNE 24: Nvidia logo is seen during the 2026 Mobile World Congress (MWC) Shanghai on June 24, 2026 in Shanghai, China. Mobile World Congress (MWC) Shanghai, slated for June 24 to 26 this year, is Asia's largest and most influential connectivity ecosystem event, with global leaders and innovators set share their visions for the future of connectivity at this showpiece in east China. (Photo by Long Wei/VCG via Getty Images)
VCG via Getty Images
This article was written by Doug Nathman, with research by his team at Trefis.
Currently priced near $195, NVIDIA (NVDA) is positioned for an approximate 51% upside in the upcoming three years under a conservative assumption. Such a significant shift warrants a closer examination of its origins. Revenue compounding drives the growth, although the multiple plays a notable role along the journey. Below is the operational basis for the calculations:
While the industry focuses on its GPUs, the company is making strides into a completely new sector. Management has introduced Vera, its inaugural CPU specifically designed for agentic AI. This initiative targets a market that NVIDIA has not tapped into before.
This strategic shift underscores why the growth projection hinges on revenue. The current Data Center operation serves as a massive, compounding driver, while the introduction of the Vera CPU line adds a separate, distinctive growth channel.
NVDA Key Metrics
Trefis
How The Calculations Are MadeThree forecasts contribute to the upside figure. Revenue is expected to compound at 30.0% each year over three years, marking a decline from the LTM 70.7% rate, which aligns with the deceleration evidenced in the historical data. Net margin relaxes from 63.0% to 57.6% as the current LTM reverts to the long-term average. Additionally, the multiple has adjustments to undergo that are unfavorable for the company. NVDA’s P/E currently stands at 29.8x, which is less than its 3-year average of 56.0 times. The scenario further reduces it to 22.3 times due to a slower expected growth rate that fails to sustain even the current multiple.
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When these three components are combined, earnings rise from $159.6 billion to approximately $320.5 billion, a 101% increase. Applying the diminished multiple to this figure results in a stock price near $294.80, which is just 51% higher than the present value. The multiple impacts earnings prior to the adjustments reflecting on the share price.
Is NVDA Capable Of Achieving This?The Vera CPU serves as the essential catalyst yet to be accounted for in the current run rate. Management asserts that Vera unveils an entirely new $200 billion market for the company. More specifically, they already anticipate nearly $20 billion in total CPU revenue within this year.
What Could Potentially Undermine It?The main risk lies in the possibility that this new CPU introduction may not progress as swiftly as previous launches. When asked to compare the Vera Rubin launch to past successes, management acknowledged the difficulty in making such an evaluation at this time. They admitted it is somewhat premature to determine how quickly the new architecture will scale.
Considering An Investment In NVDA At Current PricingInvestors are investing in consistent compounding, rather than a revaluation or margin enhancement. The assumption is that revenue continues to grow at an approximately projected rate; if it falls short, the calculations lack alternative directions.
The $20 billion in anticipated Vera revenue is too significant to overlook, rendering the uncertainty around the ramp an understandable concern.
Is It Wise To Invest In NVIDIA?A thorough three-year analysis on an individual stock remains a concentrated investment, as historical volatility during previous market turmoil indicates. Investors who conduct analyses like this for individual holdings often seek a similar methodology across a diversified portfolio, partly for discipline, and partly because even the most straightforward single-stock thesis can unravel due to factors not accounted for in the numbers.
The Trefis High Quality (HQ) Portfolio blends analytical precision with a proactive outlook across 30 stocks, featuring a consistent selection framework along with a sizing and re-balancing strategy designed to achieve growth without the risks associated with the individual stock analysis just discussed.
By selecting 30 stocks with high conviction, the HQ approach has historically outperformed a benchmark composed of the three major indices – the S&P 500, S&P Mid-cap, and Russell 2000.
The explosive growth in artificial intelligence (AI) is triggering a massive data center investment cycle and fundamentally reshaping infrastructure design.
Nvidia (NVDA) anchors this shift, accelerating a transition toward next-gen 800-volt direct current (VDC) data centers slated for commercial rollout in 2027.
This redesign supports ultra-dense 576-GPU architectures, a quantum leap from today’s 72-GPU standard, by relocating power conversion out of the rack and into standalone power centers.
Barclays’ analyst Julian Mitchell flags this structural shift as a powerful catalyst for infrastructure suppliers – and, according to experts, the following three names are particularly well positioned to benefit.
Vertiv’s specialized power management systems secure its position as Nvidia's lead architectural collaborator for the 800VDC transition.
The firm engineers the vital hardware that converts grid alternating current to 800VDC, alongside the DC-to-DC power shelves that high-density racks demand.
Financial momentum is already accelerating; first-quarter sales climbed 30% year-over-year to $2.65 billion, while adjusted operating margins expanded 430 basis points to 20.8%.
Driven by an order backlog of about $13 billion, management lifted full-year guidance, projecting roughly 51% earnings growth.
While chief product officer Scott Armul expects a “steady” commercial ramp through 2027, VRT stock offers high-leverage exposure to the precise capacity and density bottlenecks the impending architectural shift aims to resolve.
While internal rack hardware scales, GE Vernova provides the heavy-duty electrical infrastructure linking power grids directly to data center facilities.
As a premier power equipment specialist, the company bridges the widening gap between utility generation and AI campus consumption.
Recent performance highlights a massive backlog acceleration; Q1 sales rose 16% to $9.3 billion, while organic orders surged 71% to $18.3 billion, pushing total backlog to $163 billion.
With orders running at twice the rate of shipments, management pulled forward the firm’s $200 billion backlog target to 2027.
This unprecedented macro-level demand ensures GE Vernova stock captures the upstream energy investments required to sustain dense 576-GPU facility configurations.
Through disciplined acquisitions and divestitures, nVent Electric has transformed into a pure-play provider of electrical protection and advanced thermal management.
Next-generation 800VDC architectures generate extreme heat profiles that render traditional air cooling obsolete – forcing hyperscalers to adopt liquid-cooling and in-rack power distribution systems.
Financial execution underscores this transition: first-quarter revenue leaped 42% to $1.24 billion, propelled by a 76% surge in its data center-linked Systems Protection segment.
Backlog tripled to a record $2.6 billion in fiscal Q1, prompting management to raise full-year sales growth guidance to 26%-28%.
This rapid scaling, backed by a 40% boost in capital spending for capacity expansion, cements a compelling long-term thesis for the 2028 upgrade cycle.
Wall Street currently rates NVT shares to “Strong Buy” with the mean price target of about $193 indicating significant further upside from here.
Former House Speaker Kevin McCarthy, now chairman of the Alpha Institute, told CNBC on June 29, 2026 that artificial intelligence is on track to become the rare issue both parties run against in the next presidential cycle. That is a strange thing to predict about a technology currently powering the most expensive capital-expenditure boom in American corporate history. But McCarthy thinks the politics have already turned, and that investors with exposure to data centers, chip designers, and the utilities feeding them should pay attention before policy catches up to the mood.
Why McCarthy thinks 2028 becomes an anti-AI election McCarthy told CNBC, “I’ve never seen one issue flip so hard, and I don’t think you’re going to see one party in one way and another party in another. You could have in the year 2028, both nominees running against AI.” The usual pattern in American politics is that technology splits the parties. Crypto, social media moderation, and electric vehicles all produced a pro side and an anti side. AI, in his telling, is collapsing into a single bipartisan villain.
The macro backdrop is not helping the technology’s case. University of Michigan consumer sentiment sat at 44.8 in May 2026, down from 61.8 in July 2025, which is well into what the index treats as recessionary territory. When voters feel that pessimistic, they look for something to blame, and a technology going after white-collar work makes a convenient target.
The myth-versus-data argument on water, energy, and jobs McCarthy’s frustration is that the populist case against AI rests on claims he says the underlying data does not support. “AI has kind of become the boogeyman already, because if you think about it, there’s this myth. People think these data centers, you’re going to take your water, take your energy. When some of this data will show that it lowers your energy price,” he told CNBC.
The picture from government and academic reports is more complicated than either side admits. The Department of Energy projects data centers will account for up to 12% of U.S. electrical demand by 2028, and Colorado utility Xcel Energy has proposed an electric resource plan that could add over 6,000 megawatts of new generation, partly to serve data centers.
McCarthy’s labor point holds up better in the current data. JOLTS job openings hit 7.62 million in April 2026, the high of the past year, with unemployment steady at 4.3%. Electricians and HVAC trades feeding hyperscale construction are part of that demand.
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The policy-lag risk for AI-exposed portfolios “I have a fear that the policy has not kept up… we’re living through an industrial revolution that is much faster and policy is not keeping up with it, and there’s going to be discomfort,” McCarthy told CNBC. His Alpha Institute, he said, is trying to “get the policy right before” populism forces reactive rules.
That regulatory vacuum is what should focus investor minds. Executive Order 14179, Removing Barriers to American Leadership in Artificial Intelligence, currently tilts federal policy toward buildout. State legislatures are moving the other way on water permits, large-load tariffs, and residential rate protection, and that patchwork is where the real friction shows up for hyperscalers and the utilities supplying them.
Why investors should care The trade most exposed to a McCarthy-style backlash runs wider than any single chip designer. It spans data-center developers, grid-interconnection queues, and AI-infrastructure suppliers whose growth assumptions quietly require permissive permitting through 2030.
NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) sits at the top of that stack with capital flooding the buildout.
McCarthy is making a probabilistic claim about 2028. The investing question is whether the political risk on AI infrastructure is currently priced into the names benefiting from it. His answer, fairly clearly, is no.
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A $1,000 investment in NVIDIA Corp. (NASDAQ: NVDA) stock a year ago would be in a double-digit percentage profit as of June 29, 2026, as the company benefited from the AI stock boom.
On June 30, 2025, NVDA stock traded at about $157.99. As of Monday, Nvidia stock hovered around $194.73, up 23.55% over the past 12 months.
As such, an investor who risked $1,000 a year ago would have seen the portfolio grow to approximately $1,235 at press time. Essentially, the investor’s 6.329 NVDA shares would be sitting on unrealized profits of over $230.
NVDA stock 1-year chart. Source: Finbold The $1,000 portfolio peaked at about $1,470, as Nvidia stock hit an all-time high of roughly $236.49 in mid-May 2026. Over the past few weeks, NVDA stock plunged by 17%, reducing unrealized profits by $235.
However, the investor could have benefited from Nvidia’s largest dividend payout, as Finbold noted. Notably, Nvidia paid a dividend of $0.25 per share on June 26, 2026; thus, the $1,000 initial portfolio could have earned $1.58.
Nvidia stock market outlook At press time, Nvidia’s outstanding shares were around 24.2 billion, thus a market capitalization of $4.66 trillion. The company’s stock price has experienced bearish sentiment over the past few weeks amid fears of a potential AI stock bubble burst and technical headwinds, as Finbold highlighted.
Nonetheless, the long-term outlook for Nvidia stock remains bullish, fueled by rising demand for AI products, as Finbold reported. Furthermore, Jensen Huang, founder and CEO of NVIDIA, believes the company’s future is well supported by the notable growth in Agentic AI.
As such, the $1,000 NVDA portfolio could grow further in the near future, amid a potential parabolic rally.
-16 NVIDIA Blackwell B300 AI servers expected to commence operations following expected Q3 2026 delivery, expected to generate approximately US$360,000 in monthly revenue before operating expenses-
-Marks the first milestone in the Company’s previously announced expansion into AI computing and data center services-
SINGAPORE, June 29, 2026 (GLOBE NEWSWIRE) -- Bit Origin Ltd (NASDAQ: BTOG) ("Bit Origin" or the "Company"), an emerging growth company focused on AI computing infrastructure, digital asset innovation and blockchain-based strategies, today announced the acquisition of approximately US$11 million of NVIDIA Blackwell B300 AI infrastructure assets.
The acquired assets consist of sixteen (16) NVIDIA Blackwell B300 AI servers that have already been purchased by the seller and are currently expected to be delivered during the third quarter of 2026. Upon delivery, the servers are expected to be deployed at a data center facility in Malaysia pursuant to previously executed hosting arrangements. The Company has also acquired the benefit of previously executed customer deployment arrangements relating to the infrastructure. Based on these customer agreements, the Company expects the B300 servers, following their expected delivery and deployment, to generate approximately US$360,000 in recurring monthly revenue before operating expenses.
The aggregate purchase price consists of US$1 million in cash and US$10 million in equity, in the form of pre-funded warrants issued by the Company.
The acquisition represents the Company's first transaction involving next-generation NVIDIA Blackwell AI infrastructure and marks another important milestone in the execution of Bit Origin's AI infrastructure strategy announced earlier this year.
Strategic Expansion into AI Infrastructure
In April 2026, Bit Origin announced its strategic expansion beyond digital asset mining into AI computing infrastructure, GPU computing services and related digital infrastructure opportunities.
Unlike development-stage AI infrastructure projects, the acquired assets are supported by previously executed supplier arrangements, customer agreements and data center hosting arrangements. Following the expected delivery during the third quarter of 2026, the Company expects the infrastructure to commence commercial operations in Malaysia and begin generating recurring infrastructure-related revenue.
Management believes demand for high-performance GPU infrastructure continues to be driven by the rapid adoption of artificial intelligence technologies, large language models, enterprise AI applications and next-generation computing workloads. As enterprises increasingly deploy AI-powered products and services, access to reliable, scalable computing infrastructure has become an increasingly critical component of the global digital economy.
The Company believes this acquisition strengthens its position within the evolving AI computing ecosystem while establishing a foundation for continued expansion into high-performance computing infrastructure.
Management Commentary
"This acquisition represents another important milestone in the execution of our AI infrastructure strategy," said Mr. Jinghai Jiang, Chairman and Chief Executive Officer of Bit Origin.
"We are pleased to acquire next-generation NVIDIA Blackwell B300 AI infrastructure together with contracted customer deployment and hosting arrangements. We expect the servers to be delivered during the third quarter of 2026 and, upon deployment in Malaysia, to generate approximately US$360,000 in recurring monthly revenue before operating expenses, providing an initial foundation for our AI infrastructure business."
Mr. Jiang continued, "As demand for AI computing resources continues to accelerate globally, we believe high-performance GPU infrastructure represents an attractive long-term opportunity. This transaction expands our exposure to AI infrastructure through revenue-generating assets while establishing a scalable platform for future growth. We intend to continue evaluating additional opportunities involving AI infrastructure, GPU computing services, data center operations and other high-performance computing assets as part of our broader growth strategy."
About Bit Origin Ltd
Bit Origin Ltd (NASDAQ: BTOG) is an emerging growth company focused on digital asset innovation and blockchain-based strategies, including the development of AI computing infrastructure, digital infrastructure opportunities and digital asset treasury initiatives.
For more information, please visit www.bitorigin.io.
Safe Harbor Statement
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include statements regarding the anticipated closing of the transaction, expected revenue generation, future AI infrastructure opportunities, expansion into AI computing services, and the Company’s long-term strategic initiatives. These forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from those expressed or implied herein. The Company undertakes no obligation to update any forward-looking statements except as required by law.
Company Contact:
Bit Origin Ltd
Mr. Jinghai Jiang
Chairman and Chief Executive Officer
Nvidia (NVDA - Free Report) has been one of the most searched-for stocks on Zacks.com lately. So, you might want to look at some of the facts that could shape the stock's performance in the near term.
Shares of this maker of graphics chips for gaming and artificial intelligence have returned -8.8% over the past month versus the Zacks S&P 500 composite's -2.9% change. The Zacks Semiconductor - General industry, to which Nvidia belongs, has lost 8.9% over this period. Now the key question is: Where could the stock be headed in the near term?
While media releases or rumors about a substantial change in a company's business prospects usually make its stock 'trending' and lead to an immediate price change, there are always some fundamental facts that eventually dominate the buy-and-hold decision-making.
Revisions to Earnings EstimatesRather than focusing on anything else, we at Zacks prioritize evaluating the change in a company's earnings projection. This is because we believe the fair value for its stock is determined by the present value of its future stream of earnings.
Our analysis is essentially based on how sell-side analysts covering the stock are revising their earnings estimates to take the latest business trends into account. When earnings estimates for a company go up, the fair value for its stock goes up as well. And when a stock's fair value is higher than its current market price, investors tend to buy the stock, resulting in its price moving upward. Because of this, empirical studies indicate a strong correlation between trends in earnings estimate revisions and short-term stock price movements.
Nvidia is expected to post earnings of $2.08 per share for the current quarter, representing a year-over-year change of +98.1%. Over the last 30 days, the Zacks Consensus Estimate remained unchanged.
The consensus earnings estimate of $9 for the current fiscal year indicates a year-over-year change of +88.7%. This estimate has changed +3% over the last 30 days.
For the next fiscal year, the consensus earnings estimate of $12.13 indicates a change of +34.9% from what Nvidia is expected to report a year ago. Over the past month, the estimate has changed +0.9%.
Having a strong externally audited track record, our proprietary stock rating tool, the Zacks Rank, offers a more conclusive picture of a stock's price direction in the near term, since it effectively harnesses the power of earnings estimate revisions. Due to the size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, Nvidia is rated Zacks Rank #3 (Hold).
The chart below shows the evolution of the company's forward 12-month consensus EPS estimate:
12 Month EPS
Projected Revenue GrowthWhile earnings growth is arguably the most superior indicator of a company's financial health, nothing happens as such if a business isn't able to grow its revenues. After all, it's nearly impossible for a company to increase its earnings for an extended period without increasing its revenues. So, it's important to know a company's potential revenue growth.
In the case of Nvidia, the consensus sales estimate of $91.58 billion for the current quarter points to a year-over-year change of +95.9%. The $385.37 billion and $521.66 billion estimates for the current and next fiscal years indicate changes of +78.5% and +35.4%, respectively.
Last Reported Results and Surprise HistoryNvidia reported revenues of $81.62 billion in the last reported quarter, representing a year-over-year change of +85.2%. EPS of $1.87 for the same period compares with $0.81 a year ago.
Compared to the Zacks Consensus Estimate of $78.75 billion, the reported revenues represent a surprise of +3.63%. The EPS surprise was +5.65%.
The company beat consensus EPS estimates in each of the trailing four quarters. The company topped consensus revenue estimates each time over this period.
ValuationWithout considering a stock's valuation, no investment decision can be efficient. In predicting a stock's future price performance, it's crucial to determine whether its current price correctly reflects the intrinsic value of the underlying business and the company's growth prospects.
While comparing the current values of a company's valuation multiples, such as price-to-earnings (P/E), price-to-sales (P/S), and price-to-cash flow (P/CF), with its own historical values helps determine whether its stock is fairly valued, overvalued, or undervalued, comparing the company relative to its peers on these parameters gives a good sense of the reasonability of the stock's price.
The Zacks Value Style Score (part of the Zacks Style Scores system), which pays close attention to both traditional and unconventional valuation metrics to grade stocks from A to F (an A is better than a B; a B is better than a C; and so on), is pretty helpful in identifying whether a stock is overvalued, rightly valued, or temporarily undervalued.
Nvidia is graded D on this front, indicating that it is trading at a premium to its peers. Click here to see the values of some of the valuation metrics that have driven this grade.
ConclusionThe facts discussed here and much other information on Zacks.com might help determine whether or not it's worthwhile paying attention to the market buzz about Nvidia. However, its Zacks Rank #3 does suggest that it may perform in line with the broader market in the near term.
In a June 29 X post, Ali Martinez revealed that, after confirming a bearish breakout, Nvidia (NASDAQ: NVDA) stock price target stands at $170.
Specifically, the prominent on-chain analyst revealed that NVDA shares have cleared the ‘neckline’ of a head-and-shoulders pattern, indicating their descent is likely to continue.
Head-and-shoulders is a technical analysis (TA) pattern that occurs during a trend reversal either from bullish to bearish or from bearish to bullish. In the case of Nvidia stock in 2026, the left shoulder began forming during the April rally that ended with a drop in early May and went on to form a head later in the same month.
The right and lower shoulder finally took shape in mid-June with a new climb above $210 before the most recent trading broke the ‘neckline,’ indicating a deeper correction is imminent.
2026 Nvidia stock price performance Notably, the June 29 extended session also featured a slight recovery as NVDA shares rallied 0.90% from their latest – Friday – close to $194.26.
Under the circumstances, the confirmation of the sell signal might only come after the Monday morning bell as volume increases, diminishing the impact of any individual trades.
Should Martinez’s forecast prove correct, it would indicate that, after dropping 14.19% in June, Nvidia stock is set to plunge another 11.70% to $170.
Such a move could also prove significant for the wider market as NVDA shares have served as something of a leader among big tech firms due to their exceptional rally during the artificial intelligence (AI) boom that started with the initial public release of ChatGPT.
So far, despite the technological narrative remaining dominant with most analysts seeing further potential in the greater sector with a particular focus on memory and central processing units (CPUs), investors have apparently turned more cautious.
Indeed, in stark contrast to its performance in recent years, Nvidia stock is underperforming the benchmark indices – for example, NVDA shares are 1.95% up to their latest close at $192.53 year-to-date (YTD), and the S&P 500 is up 7.23% in the same timeframe – with June providing a period of particular volatility amidst a growing debate over AI return on investment (ROI).
Featured image via Shutterstock
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CHARLOTTE, N.C., June 29, 2026 (GLOBE NEWSWIRE) -- NN, Inc. (“NN” or the “Company”) (NASDAQ: NNBR), a global diversified industrial company that engineers and manufactures high-precision components and assemblies with six sigma quality, today provided an update on its rapidly growing Data Center business. NN’s combined Data Center and Electric Grid business is already its 2nd largest business, with a further goal to grow the business into the Company’s largest business by sales. The Data Center & Electric Grid end markets are top targeted growth markets for the Company along with Medical products and Defense and Electronics products.
NN has secured a significant amount of additional 2026 immediate-supply awards for liquid cooling products that go into NVIDIA AI data center racks. The new awards in this announcement are additive to prior communicated awards and greatly increase the size of NN’s liquid cooling product portfolio for AI data center racks.
NN is on its way to having 52 dedicated machines to make liquid cooled products for its data center business. 50 machines will be dedicated production lines and an additional 2 machines will be dedicated to making samples for new business. NN has already pre-sold 100% of the production capacity. NN is continuing to prospect globally and is using its global business development team and global machining footprint to prospect for additional business in this fast-growing area. In 2026, NN has attended Data Center tradeshows in the United States, Europe, and China.
Harold Bevis, President and Chief Executive Officer of NN, Inc. commented, "The liquid-cooled AI data center market is one of our targeted end markets for growth. We announced the successful launch of a new product line in Q1 2026. It is a custom-designed, stainless-steel product line for the liquid-cooled data center market. Since then, we have secured multiple AI data center awards, have invested in an initial complement of 17 next-generation, high-speed, high-precision CNC machines at our Wuxi, China plant, and began production. We have a big set of data center products already but we are just beginning. We make products that go into both the electrical system and cooling system for Data Centers and produce these products in multiple plant locations.
Today, we are pleased to announce that we have tripled the size of the liquid cooling product line that just launched in Q1 2026. Specifically, we have secured another set of multi-year, multi-product awards for stainless-steel cooling products for the NVIDIA supply chain. NN is now underway with procuring an additional 30 new machine centers on top of the 17 new CNC machine centers we previously announced. Additionally, we have successfully repurposed and retooled 5 automotive CNC production centers to become dedicated data center production. We have a strategic goal to rotate out of commodity auto products and this accelerates the achievement of that objective.”
Bevis continued, “We are building a meaningful position in the global supply chain for liquid cooled AI systems. The Wuxi plant had approximately 200 CNC machine centers before successfully entering the data center business. These additional 47 machine centers bring the total in that plant to approximately 250 CNC machine centers when this expansion is complete. We have large aspirations with our global footprint, and the industry needs NN to scale up and supply more. The AI data center liquid cooling industry is scaling very rapidly, and we are participating in the global data center buildout. This is a natural product fit as we are experienced veterans in pressurized fluid management, stainless steel part production, exceptional repetitive quality levels at high volumes, electropolishing, abrasive flow machining, debris-free and leak-free products, and fast innovation.
We have a dedicated company effort to grow Data Center products, and we are happy to have secured our next set of new awards. This expansion and ramp up is underway now during Q2 2026 and will be additive to our 2026 sales. Based on equipment lead times, the 47th new machine will be installed in November 2026. We are underway prospecting for additional awards and developing new products. As mentioned, the 47 new machines in this announcement will go into NN’s Wuxi, China plant and it will be supplying parts into NVIDIA’s Asia supply chain in China, Taiwan, and Vietnam. NN’s Wuxi China plant is a global low-cost plant that is well known in the metal part making industry. It is in an ideal location for supplying the metal parts that go into the global supply chain for AI data center racks. We believe these data center racks which are being produced in Asia are coming back to the US and being installed in data centers being built in the United States AI market.”
Bevis concluded, “As next generation supply chain decisions are being made in the data center industry, NN intends to use its global footprint of machining plants to participate further. This is a multi-billion market that is scaling up right now, and these computing racks are the hardware behind the expanding use of AI and cloud computing. These new awards fit within NN’s previously issued new wins guidance for achieving $80 to $90 million of accretive new business during 2026. We will combine this new information along with other information and adjust 2026 and 2027 sales and EBITDA guidance, if needed, during NN’s next business and guidance update when we release Q2 earnings in early August. We look forward to discussing this big advancement during that time.”
About NN’s Fluid Management Products
NN is a leader in precision fluid management products for over 40 years. The Company makes precision metal fluid management components including valve body, socket body, valve seat, sealing seat, needle, plunger, plug base, socket base, guides, and threaded connector parts. Given its long-term expertise, NN can make these products in a variety of manners across high-mix, medium-speed single spindle machines as well as high-volume, high-speed production with multi-spindle machines and rotary transfer systems. It makes these products in-house in its plants in China, Europe, South America, and North America. NN makes these products today and has for decades under multi-year contracts for many of the top OEMs in the world. The goal is leak-free, debris-free products that never fail during the life of the equipment.
NN's existing liquid management products precisely fit the requirements of data center applications, and the demanding performance and quality requirements of AI data center and cloud customers are a direct use of the Company’s existing capabilities. Furthermore, next generation computing designs require even higher power use and even higher heat generation, which will lead to next-generation liquid-cooled computing systems and components. The Company can already make products that are advanced beyond today’s requirements. NN has delivered six sigma quality, micron-level tolerance parts for combustion engines for decades. The Company’s decades of global experience and footprint are directly applicable to this new area.
About NN
NN, Inc., a global diversified industrial company, combines advanced engineering and production capabilities with in-depth materials science expertise to design and manufacture high-precision components and assemblies for a variety of markets on a global basis. Headquartered in Charlotte, North Carolina, NN has facilities in North America, Europe, South America, and China. For more information about the Company and its products, please visit www.nninc.com.
Forward-Looking Statements
This press release contains express and implied forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including, but not limited to, statements regarding future growth of NN’s liquid-cooled AI data center business, the procurement and timing of additional machines to support the liquid-cooled AI data center business, NN’s aspirations , the size and future outlook of the data center market, NN’s competitive position in the data center market, , expected new business wins for 2026, the Company’s 2026 performance and other statements that are not historical facts.
Forward-looking statements generally will be accompanied by words such as “anticipate,” “believe,” “could,” “estimate,” “expect,” “forecast,” “guidance,” “intend,” “may,” “will,” “possible,” “potential,” “predict,” “project”, “achieve,” “growth,” “enable,” “improve,” or the negative of these terms, and similar words, phrases or expressions that convey uncertainty of future events or outcomes. Forward-looking statements involve a number of risks and uncertainties that are outside of management’s control and that may cause actual results to be materially different from such statements. Such factors include, among others, general economic conditions and economic conditions in the industrial sector; competitive influences; risks that current customers will commence or increase captive production; risks of capacity underutilization; quality issues; inflationary pressures and material changes in the cost or availability of raw materials, supply chain shortages and disruptions, the availability of labor and labor distributions along the supply chain; our dependence on certain major customers, some of whom are not parties to long-term agreements (and/or are terminable on short notice); the impact of acquisitions and divestitures, as well as expansion of end markets and product officers; our ability to hire or retain key personnel; the restrictions contained in our debt agreements; the level of our indebtedness and our ability to obtain financing at favorable rates, if at all, or to refinance existing debt as it matures; our ability to secure, maintain or enforce patents or other appropriate protections for our intellectual property; the impact on climate change on our operations; economic, social and geopolitical instability, military conflict, current fluctuation, and other risks of doing business outside of the United States; and uncertainty of government policies and actions in respect to global trade and tariffs, including the potential impacts of tariffs on the United States economy, the economy of other countries in which we conduct operations and our industry, cyber liability or potential liability for breaches of our or our service providers’ information technology systems or business operations disruptions. The foregoing factors should not be construed as exhaustive and should be read in conjunction with the sections entitled “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations” included in the Company’s filings made with the U.S. Securities and Exchange Commission. Any forward-looking statement speaks only as of the date of this press release, and the Company undertakes no obligation to publicly update or review any forward-looking statement, whether as a result of new information, future developments or otherwise, except as required by law. New risks and uncertainties may emerge from time to time, and it is not possible for the Company to predict their occurrence or how they will affect the Company. The Company qualifies all forward-looking statements by these cautionary statements.
Santa Clara, California-based Nvidia, on June 12, expanded its Washington presence by appointing veteran lobbyist Bruce Andrews to steer its government affairs as U.S.-China tensions over advanced AI chips continue to escalate. Andrews will serve as its Chief External Affairs Officer, reporting to General Counsel Tim Teter.
Don’t forget to check out our premarket coverage here
Lending support to her choice, BTIG analyst Jake Fuller reiterated a Buy rating on Uber Technologies on Friday and maintained a $100 price target.
Jenny Van Leeuwen Harrington, chief executive officer of Gilman Hill Asset Management, LLC, said Enbridge Inc. (NYSE:ENB) has a 5% dividend yield.
On the earnings front, Enbridge, on May 8, reported first-quarter earnings of 98 cents per share. It beat the analyst consensus estimate of 89 cents per share. The company reported quarterly sales of $22.357 billion, which beat the analyst consensus estimate of $17.396 billion.
Stephen Weiss, chief investment officer and managing partner of Short Hills Capital Partners, said Meta Platforms, Inc. (NASDAQ:META) will continue to bounce.
Meta is also partnering with Indian billionaire Mukesh Ambani‘s Reliance Industries to develop its first AI-enabled data center in India. The Facebook parent company is accelerating its global artificial intelligence infrastructure buildout.
Price Action Uber gained 5.5% to close at $76.20 on Friday. Nvidia shares fell 1.6% to settle at $192.53 during the session. Enbridge shares gained 0.1% to close at $56.24 on Friday. Meta shares rose 1.4% to settle at $550.25 during the session. Photo via Shutterstock
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Nvidia CEO Jensen Huang. Bloomberg/Getty Images Nvidia's AI ambitions are officially out of this world this year, and they haven't come back down to Earth.
The AI chip giant is adding to the team behind Space-1, its first computing system designed for space. In recent weeks, the chip giant posted a second job tied to orbital data centers.
The role — for a system software principal architect — will help build software for Space-1, which the chip giant unveiled at its GTC event in March.
Space data centers have emerged as a potential way to get around growing constraints on land, power, and cooling on Earth. Companies like SpaceX are racing to make the idea a reality, while skeptics argue the costs still outweigh the benefits.
During a recent earnings call, Nvidia CEO Jensen Huang said the economics around space computing are poor today but will improve over time.
The principal architect job post follows another role shared earlier this year for an orbital data center system architect. While that position focuses on designing the overall system — from computing hardware to satellites to connectivity systems — the new post focuses on making Space-1's software work in practice.
The person hired will design the software that runs the system so it can withstand radiation and extreme temperature swings and be managed remotely.
Space-1 harnesses Nvidia's latest Vera Rubin AI chip platform and is designed for low-Earth orbit missions.
The system software role requires previous experience building AI infrastructure and systems in space. It offers a base salary of $272,000 to $431,250, which doesn't include Nvidia's coveted equity awards.
While the technology is still in its early stages, Nvidia's latest job postings suggest the chipmaker is moving from conceptual planning to building the systems needed to make it work.
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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.
As Europeans scramble to stay cool amid a record-breaking heatwave, Big Tech faces its own battle to keep the powerful chips in AI data centers running.
Temperatures this week have underscored the impact the weather can have on infrastructure like factories, nuclear power plants and data centers. Extra demand from air conditioning units can overload power grids, causing blackouts that can disrupt infrastructure. And it's not just in Europe.
Over the past three years, severe weather has become the leading cause of loss in Zurich's U.S. data center builders' risk portfolio. It now drives a third of the company's losses, Zurich's Head of International Construction Patrick McBride, told CNBC.
Severe weather is no longer something that can be treated as a background exposure.
Patrick McBride
Head of International Construction at Zurich
Many data centers are moving to suburban or rural areas where land is cheaper and records of extreme weather were often limited because the areas were largely underdeveloped, he said. "Now we have $3 billion worth of assets with over a mile worth of exposure to these events."
Why insurers are watching climate riskA recent study by climate risk analytics firm First Street found that 79% of global data center capacity faces elevated risks from acute climate hazards such as flooding, extreme winds, and wildfires that can disrupt operations, increase downtime and drive insurance and repair costs.
"It's not a matter of 'if' climate risks will impact the digital infrastructure revolution," Joe Macejak, U.S. property digital infrastructure leader at Marsh Risk, told CNBC. "But rather how clients and stakeholders in the digital infrastructure industry identify, quantify, and manage these climate risks within their respective tolerances."
If they don't manage these risks, businesses could face higher costs and operational shortfalls —which "pose a threat to the capital stacks that are fueling the AI-driven data center revolution," Macejak added.
Where new data centers face severe weather risksThis year, 64% of data center capacity under construction is outside traditional hubs such as Northern Virginia and moving into so-called frontier markets, such as West Texas, Tennessee, Wisconsin and Ohio, Zurich's McBride said. He added that facilities in these areas can face heightened risk of "tornadoes, hail and high winds wreaking havoc on vast roofs that have exposed HVAC [heating and cooling systems], cooling towers and energy installations like solar."
McBride gave Brazil as an example of an emerging data center market that might face heat challenges. Meanwhile, in Europe, data centers are migrating to areas like the Iberian Peninsula, where temperatures are also rising.
"Severe weather is no longer something that can be treated as a background exposure," McBride said. "It is one of the first things we and the owners we work with look at."
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It's not just the data center that could be impacted by extreme heat.
"Extreme heat stresses data centers and the grid they rely on at the same time," Mishal Thadani, CEO and co-founder of AI software platform Rhizome, said. The company uses models to help utilities identify vulnerabilities from climate threats.
Cooling makes up around 40% of data centers' energy use even at normal temperature, and this rises in extreme heat, just when air conditioning is driving up demand for the power grid, Thadani said. "Data centers need the most energy exactly when the grid has the least available to give."
He provided the example of the Italian city of Turin that saw highs of around 38 degrees Celsius (100 degrees Fahreheinheit) in May. The heatwave put the city's underground cables under thermal stress, and it caused repeated blackouts, Thadani said.
"Now add facilities that each pull as much power as a hundred thousand homes. The heat and the load hit the same wires at the same time. Data center load can be curtailed during the worst hours, but most planning models still don't account for how much more often extreme heat is coming," Thadani added.
How operators are adapting data center designMicrosoft, one of the hyperscalers leading the data-center buildout, told CNBC that it is preparing for changing conditions.
Microsoft designs its data centers to operate "reliably in a wide range of environmental conditions, with site selection, redundant systems, and real-time monitoring helping manage risks from extreme heat and severe weather," a spokesperson told CNBC on Thursday.
Tech giant Nvidia said last week that its new AI servers can run their cooling liquid at 45 degrees Celsius, up from previously lower temperatures. Raising chiller temperatures by just one degree can cut cooling energy costs by about 4%, Nvidia said.
Read more data center newsAnthropic’s latest hiring spree reveals where it’s building AI data centers nextNo one wants AI data centers on Earth. Do they make sense in space?Why AI demand is pushing data centers to the edge of EuropeDenmark faces data center reckoning as power grid overwhelmed by surging demandMajor data center company pauses investment decisions in Middle East amid Iran war, CEO tells CNBCAnthropic looks to hire six-figure role for negotiating data center deals to fuel Europe AI expansionAI data center boom ‘stress tests’ insurers as private capital floods inData center expansion reaches an ‘inflection point’How the AI debt binge shattered hyperscalers’ ‘unspoken contract’ with investorsPowering AI: Europe switches on its first microgrid-connected data centerHow the red-hot AI data center boom is igniting demand for a new, lucrative career path: Trade workersDust to data centers: The year AI tech giants, and billions in debt, began remaking the American landscapeQuantum’s big leap puts data centers in the spotlightData center deals hit record $61 billion in 2025 amid construction frenzyThese developments are driving technology forward for all participants in the sector, said Aaron Lewis, chief commercial officer of global data center solutions at HVAC company, Johnson Controls. The company already tests data-center cooling equipment to ensure it can withstand various temperatures.
Lewis said that recently, for the first time, he saw a client in Europe add a "climate change factor" in the specification, so their data centers are designed for temperature rises.
Ultimately, the market will end up with a "diverse set of systems and applications, and as the technologies continue to evolve, we're finding ways to transfer the heat more effectively. The pace of innovation driven by the data center boom is going to allow us to operate under some of these conditions far into the future," Lewis told CNBC.
Shortly after the launch of ChatGPT in late November 2022, big tech hyperscalers realized that chipsets known as graphics processing units (GPUs) could be used to develop next-generation applications in artificial intelligence (AI). At the time, Nvidia (NVDA 1.42%) had a first-mover advantage in the GPU landscape. As a result, the company's revenue skyrocketed to record levels seemingly overnight -- as did its valuation.
After rapid and sustained share price appreciation, Nvidia quickly entered the trillion-dollar club. With a market capitalization of $4.7 trillion, Nvidia now sits at the top of this exclusive roster.
While GPUs have ushered in Nvidia's status as the world's most valuable company, I think its next trillion-dollar opportunity lies elsewhere. Luckily, Nvidia CEO Jensen Huang has given us some clues. Let's explore where Nvidia has been investing lately, and assess what these moves could mean for the company's trajectory as the AI infrastructure era takes shape.
Image source: Nvidia.
Understanding the critical role of AI networking AI networking refers to the specialized interconnects that link GPU clusters inside data centers. Without extremely high bandwidth, ultra-low latency, and lossless performance, communication among model training and inference deployments creates congestion that leaves GPUs underutilized.
This results in diminished returns on multi-billion-dollar hardware investments. In this sense, networking can be seen as being as important as raw compute. In other words, the fastest GPUs ultimately deliver little value if data cannot flow efficiently between clusters. As models grow larger and applications become more complex, the underlying network stitching AI development together becomes the limiting factor for overall system performance.
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Does Nvidia even offer AI networking solutions? While its GPU business takes the spotlight, Nvidia has quietly assembled deep expertise across multiple networking technologies tailored for AI.
The company's InfiniBand platform offers ultra-low latency, in-network computing, and high-bandwidth connectivity optimized for high-performance computing (HPC) and AI workloads. Nvidia complements this with its Spectrum family of Ethernet switches -- particularly the AI-optimized Spectrum-X platform, which features adaptive routing, congestion control, and predictable behavior within standard Ethernet environments.
Rounding out the offering are the BlueField data processing units (DPUs), which offload networking, storage, and security tasks from CPUs and GPUs. Taken together, Nvidia's networking suite forms a comprehensive, high-performance foundation capable of powering hyperscale AI deployments.
Nvidia is partnering with several AI networking leaders To accelerate its position and secure additional supply in the networking domain, Nvidia has made several targeted strategic investments.
In March, Nvidia invested $2 billion each in Coherent and Lumentum. The rationale behind these partnerships is to advance Nvidia's position in optical interconnects and silicon photonics, two essential layers for transmitting data at high speeds over long distances with lower power consumption. Nvidia invested another $2 billion in Marvell Technology to deepen its reach in designing custom AI accelerators.
These moves are far from random. Rather, each investment quietly strengthens Nvidia's ability to build end-to-end optical and electrical networking components layered atop its GPU ecosystem.
By combining its GPUs' architectures with an expanding networking portfolio, Nvidia is positioning itself as the key provider of complete AI factories -- integrated systems that capture compute, high-speed interconnects, DPUs, software, and advanced photonics. The goal is to enable customers to deploy turnkey infrastructure capable of training and running the largest AI models at unprecedented scale and efficiency.
From a valuation standpoint, Nvidia currently trades at a forward price-to-earnings (P/E) ratio of roughly 22. As the chart illustrates, this multiple sits well below the elevated levels Nvidia reached during the peak enthusiasm of the AI revolution's initial GPU phase.
NVDA PE Ratio (Forward) data by YCharts.
I don't think the market has fully incorporated Nvidia's expansion into networking. Since all signs point to an acceleration in AI infrastructure spending over the next several years, Nvidia's true earnings power could prove considerably larger than current expectations. Given these dynamics, I see Nvidia as a no-brainer stock to buy and hold, as hyperscalers bolster their capex budgets, allocating more to networking gear to meet their capacity needs.
On June 16, just its third day of trading, Space Exploration Technologies (SPCX +0.13%), also known as SpaceX, was briefly the fourth-largest company by market cap. Its stock has pulled back since then, but it's still in the top 10 as of June 25.
The space company's fast rise drew comparisons to Nvidia (NVDA 1.42%), the chipmaker that's currently the world's most valuable business. Some Wall Street analysts have even predicted that SpaceX's market cap could surpass Nvidia's. Here's a look at the most bullish projections and how these two companies really compare.
Image source: The Motley Fool.
The analysts predicting a big move from SpaceX Nvidia's market cap sits at about $4.7 trillion, and multiple analysts have set targets beyond that for SpaceX. Arete analyst Andrew Beale gave SpaceX a buy rating and a price target of $401 by the end of next year, which would translate to a market cap of about $5.3 trillion -- enough to surpass Nvidia's current market cap, although there's no telling exactly where it will be in the future.
Oppenheimer analyst Tim Horan predicts that SpaceX could be worth $10 trillion within five years. CNBC's Jim Cramer said SpaceX stock could grow very quickly after its IPO due to its small float, and he has made multiple market-cap predictions for it in television appearances, including $5 trillion and $6 trillion.
Cramer's prediction is tied to the hype around SpaceX stock, but Beale and Horan based their forecasts on the strength of the business. They both cited Starlink, SpaceX's satellite internet service, as one of the main drivers of growth. Starlink anchors SpaceX's connectivity segment, which generated $11.4 billion in revenue last year, 61% of its total sales. It's also fast-growing, going from 9 million customers in 2025 to 12 million across more than 160 countries this month.
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Founder and CEO Elon Musk has said that V3 Starlink satellites should launch later this year. These satellites are a significant upgrade over previous versions, with 10x the V2 version's downlink speeds and an even larger jump in uplink capacity.
SpaceX also has its launch business, which accounted for 80% of U.S. commercial launches in 2025, and its AI business. Although its AI segment lost money in 2025, the company has made some smart moves recently. It's leasing computing capacity to AI companies, including Anthropic and Alphabet, and it acquired Cursor, a popular AI coding start-up, in a $60 billion all-stock deal.
Nvidia still has a sizable lead The SpaceX and Nvidia comparison breaks down once you get into their financial results, because that's where the chipmaker is much farther along. SpaceX's revenue grew 33% to $18.7 billion in 2025, which is fine on its own, but a red flag for a company the market is valuing at $2 trillion. Nvidia made $215.9 billion, up 65% year over year, in its fiscal 2026, which ended on Jan. 25, 2026. As for valuations, Nvidia trades at about 18 times annual sales. SpaceX trades at nearly 5 times more: 108 times annual sales.
SpaceX isn't profitable yet, either, reporting a net loss of $4.9 billion last year as it spends heavily on rockets, constellations, and AI. Even after a record-setting $75 billion IPO, SpaceX was back to raising money less than two weeks later with a $25 billion debt sale.
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It's easy to take Nvidia's success for granted now that it's the market leader, but its financial results are spectacular. Revenue growth consistently tops expectations, its gross margin is above 70%, and it reported net income of $120 billion in its fiscal 2026. It's the dominant chipmaker at a time when the four biggest hyperscalers are expected to spend $600 billion to $700 billion on data centers this year.
SpaceX could theoretically be bigger than Nvidia one day, but realistically, Starlink is its only profitable business right now, and the launch business is close to breakeven. The extremely high valuation also means that anything short of perfect execution could trigger a downturn. I expect SpaceX to grow over the next five to 10 years, but not enough to surpass Nvidia.
Nvidia is the most valuable company in the world, with a market cap of more than $4.7 trillion. It has become not just an earnings powerhouse for its investors, but also for its partners.
Last fall, Nokia (NOK 7.26%) inked a $1 billion partnership to develop an AI-enabled cellular phone network, called AI RAN, or radio access network. It will essentially result in the upgrade to 6G communications and AI capabilities for mobile networks, transforming cell towers into data centers and changing mobile communications.
For its part, Nvidia is providing the AI chips and platform on which the AI RAN 6G platform will run.
Image source: Getty Images.
As part of the deal, Nvidia will deploy Nokia's switches, SR Linux software, and optical technologies at its data centers.
At the time the deal with Nokia was announced, Nokia was trading at just $6 per share, and had been in penny stock territory a few weeks prior at $4.90 per share. Since then, Nokia stock has skyrocketed 133% to almost $14 per share, including a 114% gain year to date.
The company is anticipating a major surge in revenue from the partnership, which has created investor excitement and bolstered its stock price.
Should you go all-in on Nokia? Nokia's stock price shot up following its first-quarter earnings release on April 23. The enthusiasm was less about its results, which were solid but not spectacular, and more about its outlook.
Nokia raised its guidance for the fiscal year. It's now calling for network infrastructure sales growth of 12% to 14% this fiscal year, up from 6% to 8% projected growth in January. The jump is based on the assumption that IP and optical networks revenue will grow 18% to 20% in 2026. The previous target was 10% to 12% growth. That increase in the outlook is related largely to the data center partnership with Nvidia.
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The other piece of the deal, the 6G networking, will have a longer runway, with earnings accretion from the partnership likely starting to emerge in 2027 and for several years after as the 6G networks get built.
So, this could be a transformative partnership for the beaten-down telecommunications stock, which has been trading mostly in penny stock range for more than a decade.
The recent surge has increased Nokia's price-to-earnings (P/E) ratio to 86 with a forward P/E of 36, so it's still a bit pricey. Analysts are mixed on the stock, with about half rating it as a buy with a $12 per share median price target.
While the future looks brighter for Nokia, investors may want to be cautious and pick their spots, given the recent rapid surge in Nokia's price and valuation. It does appear to be a long-term grower, but investors may want to find a better entry point.
Artificial intelligence has moved beyond proving it works. The challenge today is producing enough computing power to satisfy demand. Big Tech is spending hundreds of billions of dollars building AI infrastructure, yet companies are still finding themselves short on capacity. That indicates AI adoption is accelerating faster than the industry’s ability to support it.
The latest evidence comes from an unlikely source: Google reportedly had to tell one of the world’s largest technology companies that it simply couldn’t deliver all the AI compute it wanted.
Even Google Has Run Out of Room The Financial Times reports that Google informed Meta Platforms (NASDAQ:META | META Price Prediction) around March that it could not provide all of the Gemini inference capacity Meta wanted to purchase. The shortage reportedly disrupted some of Meta’s internal AI projects and forced the company to prioritize where it used Google’s models.
That isn’t what investors expected to hear from one of the world’s largest cloud providers. Google invested over $90 billion in 2025 and is planning to double that this year expanding its AI infrastructure, including custom Tensor Processing Units (TPUs) and new data centers. Yet demand for Gemini has grown so quickly that capacity has become a scarce resource.
Meta wasn’t the only customer affected, according to the Financial Times, although its enormous demand made it the most visible example. The report says Google continues to limit some customer access as it works to expand capacity.
Training a model happens once. Inference happens millions or even billions of times every day. It shows enterprise AI adoption is accelerating across software development, customer service, advertising, research, and productivity tools. Every new AI-powered application increases demand for inference compute.
According to Alphabet’s (NASDAQ:GOOG) latest quarterly earnings release, Google Cloud ended the quarter with more than $460 billion in remaining performance obligations, a backlog that includes long-term customer contracts. CEO Sundar Pichai also said cloud revenue would have been higher if Google had more available capacity.
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In other words, demand isn’t the problem. Supply is.
Why Investors Should Pay Attention Surprisingly, this shortage is good news for much of the AI supply chain. If Google cannot fully satisfy demand despite operating one of the world’s largest AI infrastructures, it suggests the market remains far from saturated. Companies supplying the hardware behind AI — including GPUs, high-bandwidth memory, networking equipment, optical components, and power systems — still have years of demand ahead of them.
Granted, Google, Microsoft (NASDAQ:MSFT), Amazon (NASDAQ:AMZN), and Meta are investing aggressively to close the gap. Collectively, those companies are expected to spend well over $700 billion on AI infrastructure this year alone.
Regardless, expanding AI capacity takes time. New chips must be manufactured, servers assembled, data centers completed, and networking equipment installed before additional inference capacity becomes available.
And there are numerous chokepoints they are encountering along the way: energy, land, and memory, to name just a few. Nvidia (NASDAQ:NVDA) CEO Jensen Huang says the compute required for agentic AI will rise at least 1,000% compared to generative AI in just two years.
Key Takeaway In short, AI isn’t running into a demand problem. It’s running into a supply problem. The Financial Times’ report that Google couldn’t provide Meta with all the Gemini capacity it requested highlights just how quickly enterprise AI adoption is accelerating. Even companies spending hundreds of billions of dollars on infrastructure can’t build compute fast enough to satisfy customers.
For investors, that’s an encouraging signal. The AI boom is no longer limited by interest in the technology. It’s limited by the industry’s ability to produce enough computing power to meet it. Until that imbalance narrows, companies supplying the AI ecosystem should continue to benefit from one of the strongest infrastructure spending cycles the technology sector has ever experienced.
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The NVIDIA logo in this illustration taken June 11, 2026. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights, opens new tab
SYDNEY, June 29 (Reuters) - Australian AI infrastructure company Firmus Technologies said on Monday it had signed a strategic partnership with Nvidia Corp (NVDA.O), opens new tab to help provide emerging AI firms with more cost-effective access to computing power.
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Firmus said the deal would see it buy Nvidia infrastructure and sell Nvidia‑powered cloud services to "AI Native" customers, among others, in an agreement that would earn the U.S.-listed chip giant product revenue and a share of cloud revenue.
The deal will deliver 170,000 Graphics Processing Units (GPU) from the first quarter of 2027 to the start of 2028, that will be located in Batam, Indonesia.
Firmus said it expected to earn up to $30 billion in revenue during the first six years of the deal, based on customer commitments.
The Australian-founded company said the deal would make it easier for smaller and developing AI firms to access the technology's infrastructure.
"We have worked to figure out how to close the gap between the cost benefits that the large guys have access to, which they do because they have great credit ratings, and the guys that are up and comers," Firmus co-chief executive Tim Rosenfield told Reuters. "This is actually a really material way to level the playing field a little bit to give the next a chance to compete with the big guys."
Nvidia has participated in Firmus' previous capital raisings making it an investor in the Australian firm, according to Firmus.
Firmus said in April it had raised $1.35 billion over the previous six months, giving it a $5.5 billion post-money valuation. It has appointed investment banks to work on a potential initial public offering, according to people familiar with the matter.
Rosenfield declined to comment on Firmus' IPO preparations.
Reporting by Scott Murdoch; Editing by Kate Mayberry
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Scott Murdoch has been a journalist for more than two decades working for Thomson Reuters and News Corp in Australia. He has specialised in financial journalism for most of his career and covers the Australian financial services sector and superannuation. He is based in Sydney.
Back in 2023, investors viewed Microsoft (MSFT +6.03%) as one of the best options to get direct exposure to OpenAI. That's because the tech giant announced a multiyear, multibillion-dollar investment in OpenAI that could reach $10 billion.
It wasn't Microsoft's first investment in the company, and the two of them seemed close. However, the good relationship has turned a bit sour, with Microsoft releasing products that directly compete with ChatGPT.
Microsoft no longer seems like the top stock to buy for direct exposure to OpenAI, but there is still a great option. Nvidia (NVDA 1.42%) appears to be the best choice for investors who want exposure to OpenAI before its IPO.
Image source: Getty Images
OpenAI needs chips OpenAI needs AI infrastructure to run ChatGPT and future services, and that infrastructure is only possible with Nvidia's chips. As OpenAI's revenue continues to scale, the need for more AI chips will grow.
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OpenAI hasn't been shy about saying it will have to spend a lot of money. Investors were recently told that the company may spend $115 billion through 2029. A lot of that money will have to go to AI chips.
Nvidia isn't the only AI chipmaker. Broadcom and Advanced Micro Devices are two other viable options, and OpenAI does business with both of them. However, Nvidia has established itself as the golden standard of GPUs, and it's not even close. Nvidia's net income is higher than the combined revenue of Broadcom and Advanced Micro Devices.
Nvidia supplies chips to every major company The artificial intelligence opportunity encompasses many components. AI data centers, liquid cooling systems, raw materials, optical cables, and other pieces. There are competitors in each of those industries that are vying for market share.
All of this activity revolves around AI chips, and Nvidia is the distinguished leader in the industry. It doesn't rely on OpenAI for revenue and can already deliver superb sales and earnings growth with parabolic demand from hyperscalers, AI start-ups, and other companies.
Nvidia delivered 85% year-over-year revenue growth in its fiscal 2027 first quarter, while more than tripling its net income. Microsoft can't compete with those results, even with its cloud platform.
OpenAI has to compete with companies like Anthropic and xAI. It's also squaring off against hyperscalers with substantial profits, like Microsoft, Meta Platforms, and Amazon. All of these companies want more Nvidia chips. That's OpenAI's problem, and it gives Nvidia the green light to raise AI chip prices and secure higher margins.
Marc Guberti has positions in Broadcom. The Motley Fool has positions in and recommends Advanced Micro Devices, Amazon, Broadcom, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.
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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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).
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
