OpenAI CEO Sam Altman is aiming for a $1 trillion valuation for the initial public offering (“IPO”) of the artificial-intelligence (“AI”) model company. But the increasingly poor economics of AI and the company’s terrible financials mean that even an already delayed IPO may never arrive.

OpenAI is facing white-hot competition, with the company now severely marking down the price of high-end AI models created just weeks before. Altman and his public relations team tried to balance that news with the fact that OpenAI’s customers now comprise more than 1 billion users and more than two million businesses. Instead, investors need to pay attention to OpenAI’s lack of pricing power.

In late July, Altman announced the following price cuts on two recently adopted models and an upgrade on a third model.

As part of the announcement, OpenAI explained that GPT-5.6 had become more efficient to run, so the company said: “We’re passing those gains on to customers with lower prices…”

It’s a sales pitch that feels a lot like a seedy car salesman trying to “get you in a new car today.” But businesses aren’t usually trying to lower prices – their profit driver – unless they need to. And that’s even more true for a company’s latest and greatest models, as is the case at OpenAI.

That’s the tough situation OpenAI finds itself in today, as Chinese AI rivals such as Kimi K3 and DeepSeek models make heavy incursions into OpenAI’s user base. They’re releasing high-power AI models that do most of what OpenAI’s (and Anthropic’s) models do, but they charge a fraction of the price, sometimes just a few percentage points of what higher-end models charge.

It’s a price war that OpenAI simply can’t afford, one way or the other. OpenAI is already burning cash furiously and must be propped up by its customers. At the same time, it needs revenue to make good on an estimated $1.4 trillion in spending commitments in the coming years.

Either way, the company may well go broke. Many firms that are counting on it for revenue – Oracle (ORCL), Cerebras Systems (CBRS), and CoreWeave (CRWV) – may be badly hurt.

So, OpenAI must raise money to continue operating, but investors need to see a credible path to profitability before Altman’s IPO goal of $1 trillion can ever come to fruition. This impasse means that OpenAI has tentatively delayed its IPO until 2027, but it may be “delayed” permanently.

OpenAI’s Cash Burn Is Probably Getting Worse

The unprecedented scale of OpenAI’s ability to lose money is something to behold. OpenAI reported an operating loss of $20.9 billion in 2025 and estimates for the first quarter of 2026 peg its operating loss at a further $7 billion. At this rate, OpenAI could easily lose $30 billion in 2026 and possibly even $35 billion to $37 billion. We’ll have to wait for leaked financials for a better idea.

But a price war won’t likely improve profitability, even if it does increase sales for the moment.

In fact, we’re seeing OpenAI’s sales continue to soar, though the company’s executives provided only very high-level financials. CFO Sarah Friar told employees that OpenAI’s July annualized recurring revenue had exceeded the company’s total for the second quarter, according to CNBC.

While that feat may actually be less impressive than it sounds at first, it does indicate a ramp in sales at the end of the quarter. But it may well be one that the company can’t afford.

The interesting detail here is what leaders attributed the growth to: the company’s enterprise agent ChatGPT Work, its AI coding tool Codex, and its GPT-5.6 series of models.

That is, the same GPT model that OpenAI put on sale at a severe discount at the end of July.

For normal companies, sales growth translates into scaling profitability. In OpenAI’s case, higher sales translate into even greater losses, and we have plenty of signs that OpenAI is burning more cash than ever, as it’s forced to lower prices to keep getting business.

So, higher sales are not good news when you’re losing more money in absolute terms.

The inability to price AI models so that they’re profitable shows that AI models are mostly fungible. Businesses are shifting to the lowest-cost model to carry out their work, and some are reserving the high-cost models for their best and highest uses. But Chinese AI models have been showing that they, too, can move upmarket, leaving less room for OpenAI here, too.

For example, among AI startups using open-source software, about 80% are using Chinese AI models, according to Andreessen Horowitz.

While OpenAI struggles to get itself in shape for an IPO, China’s DeepSeek is planning its own public offering by the end of 2026 or early next year.

OpenAI’s Next Funding Round

All this means that OpenAI is likely to be burning even more cash at an even faster clip than before. The upshot then is that it will need to raise another funding round sooner than some may have thought. OpenAI last raised $122 billion in March, valuing the company at $852 billion.

OpenAI is under significant constraints, however. Venture-stage companies do not like to raise money at a lower valuation than the prior funding round. It indicates that something’s not right and dings the company’s reputation. That reputational worry is even greater in the field of AI, which is being hyped as much as any technology ever has been. If OpenAI can’t raise its valuation in the next funding round, it will look like there’s something wrong. (And there is…)

OpenAI needs to raise money at ever-higher valuations to keep the market’s confidence up and so that it can retain the potential to raise even more money in the future.

Of course, Altman wants to line up funding before he needs it, too. Increasingly larger losses in future quarters will hurt investors’ confidence to put up more cash. At the same time, ready cash that can subsidize its ongoing losses means OpenAI is not immediately subject to the market’s whims, giving Altman some maneuvering room if funding conditions tighten for a while.

Like the last funding round in March, OpenAI’s next round is likely to be funded by mega-cap companies that need the AI party to continue. Last time out, Amazon (AMZN), Nvidia (NVDA), and SoftBank (SFTBY) put up $110 billion of the $122 billion raised by OpenAI. Investors may need to raise cash from the debt markets themselves to plow into the money-losing OpenAI.

OpenAI is a linchpin in the AI economy, since it’s promised to spend literally more than $1 trillion across some of the biggest AI-related firms. If it’s unable to meet these commitments – and it must raise the cash to do so – the dominoes will begin to fall across the entire AI sector.

Confidence is key in these situations, and investors are already feeling skittish after a poor debut from SpaceX (SPCX) and massive declines in memory stocks such as Micron Technology (MU). The inability of OpenAI to raise at a higher valuation could be a sign that the Teflon stock market for AI stocks may be about to turn. So, keep a close eye on OpenAI’s ability to raise funding.

Regards,

James Royal, PhD

Editor’s Note: One company quietly beat Apple, Amazon, and the S&P 500 — combined. Over the long run it has returned more than 8,300%… enough to turn $10,000 into $830,000. Yet most investors have never heard of it. Former fund manager Whitney Tilson says right now it’s trading at a rare discount — and he’s revealing the name and ticker, free of charge. Click here for the details…

OpenAI IPO Delay FAQ

Why is OpenAI’s IPO delayed?

OpenAI has tentatively delayed its IPO until 2027. Sam Altman is holding out for a $1 trillion valuation, but investors need to see a credible path to profitability before that can happen, and OpenAI hasn’t demonstrated one.

When will OpenAI’s IPO happen?

OpenAI has tentatively set 2027 as its new timeline, after already delaying the offering once before. Given OpenAI’s mounting losses and the pricing pressure it’s facing from competitors, that date isn’t set in stone.

Could OpenAI’s IPO never happen at all?

It’s possible. OpenAI’s already-delayed IPO may never arrive at all, given the increasingly poor economics of AI and the company’s own terrible financials. What looks like a delay to 2027 could turn out to be permanent.

Why is OpenAI cutting the price of its AI models?

In late July, OpenAI cut prices on GPT-5.6 Luna by 80% and Terra by 20%, just weeks after launching them. OpenAI said it was passing along efficiency gains, but the cuts come as Chinese AI rivals like DeepSeek and Kimi K3 offer similar models for a fraction of the cost.

How much money is OpenAI losing?

OpenAI reported a $20.9 billion operating loss in 2025, with estimates putting its first-quarter 2026 loss at another $7 billion. At that pace, OpenAI could lose $30 billion to $37 billion in 2026.

How much has OpenAI raised in funding, and at what valuation?

OpenAI raised $122 billion in March at an $852 billion valuation, with Amazon, Nvidia, and SoftBank contributing $110 billion of that total. OpenAI will likely need to raise again soon, and doing so at a lower valuation than its last round would signal to the market that something is wrong.

Which stocks could be hurt if OpenAI’s IPO stalls or fails?

Companies that depend on OpenAI for revenue, including Oracle, Cerebras Systems, and CoreWeave, could be badly hurt. OpenAI has promised more than $1 trillion in spending commitments across the AI industry, and if it can’t raise the cash to meet them, the dominoes could begin to fall across the entire AI sector.

The post OpenAI IPO Delay: Just the Start? Price Cuts Hint It May Not Happen at All appeared first on MarketWise.

Since the artificial-intelligence (“AI”) boom began, the industry has faced its share of bottlenecks. Power continues to be a major choke point, as America’s grids can no longer accommodate the immense energy needs of AI data centers. Thermal management has also been a significant issue, with data-center servers and equipment requiring proper cooling to prevent overheating.

But perhaps the biggest AI bottleneck to date has been memory. And that shortage has been building for months.

During Micron Technology’s (MU) first-quarter earnings call on December 17, CEO Sanjay Mehrotra stated:

Over the last few months, our customers’ AI data center build-out plans have driven a sharp increase in demand forecasts for memory and storage. We believe that the aggregate industry supply will remain substantially short of the demand for the foreseeable future…

Micron is working hard to support our customers’ demand during this time, and we expect to grow our [dynamic random-access memory (“DRAM”)] and NAND bit shipments approximately 20% in calendar [year] 2026. Despite significant efforts, we are disappointed to be unable to meet demand from our customers, across all market segments.

After Micron’s second-quarter earnings were released on March 18, Mehrotra told CNBC:

We are only able to supply, for our key customers in the midterm, about 50% to two-thirds of their requirements.

We’re now into August, and the supply of memory hasn’t improved. The world’s leading memory manufacturers – Micron, SK Hynix (SKHY), and Samsung Electronics (005930.KS) – have sold out their entire DRAM and high-bandwidth memory (“HBM”) not just through the rest of this year… but through all of 2027.

That should be good news for these companies, right? Sellouts mean that all of your product has been purchased, with backlogs promising millions or billions in future revenue. So, why has Micron stock sunk from its all-time closing high of $1,213.56 on June 25 to its August 3 closing price of $829.50? That’s a nearly 32% drop. In the same time frame, Samsung, which trades on the Korea Exchange, has fallen roughly 33%. And since SK Hynix went public on the Nasdaq on July 10, its price is down 15% through August 3.

What should investors make of this broad decline in the top memory stocks?

Why the 2027 Memory Sellout Matters

As bad as 2026 has been for memory shortages, 2027 will likely be much worse, at least according to SK Hynix CEO Kwak Noh-jung, who told Reuters that 2027 will likely be “the worst year in the industry’s history from the supply perspective.” He also projected that customer demand will exceed supply capacity “even beyond 2030.”

Here’s why: Memory manufacturers have been encouraging customers to sign long-term (three-to-five-year) contracts, “using an advance payment deposit model where customers essentially pre-pay for some of the memory capacity,” according to TechPowerUp.

With all of 2027’s memory allocation already being sold out, the only customers who will receive any memory supply are those who signed these agreements. Everyone else looks to be out of luck. There literally isn’t enough DRAM available. Those businesses that didn’t sign contracts with the memory manufacturers will be without the memory they need in 2027 and forced to wait until the 2028 supply is made available to order.

Even for those customers that did sign contracts, they’re still not guaranteed the memory supply in 2027. That’s because most of the memory supply will go to AI data centers, hyperscalers, and cloud-service providers. For example, Samsung has five-year agreements in place to supply the world’s five largest data-center operators with the memory they need… and that amounts to between 60% and 70% of Samsung’s memory production capacity.

It’s undoubtedly a smart business move by Samsung because it locks in steady revenue for the next five years. But who suffers the most from these deals? Everyday consumers.

With up to 70% of all memory production going everywhere but into consumer-electronics items, simple math tells us that only 30% of the memory supply remains for everyday products like phones, computers, tablets, and gaming consoles, to name a few.

And when supply is that limited, Economics 101 informs us prices rise. In fact, if you’ve shopped recently for some of these products, you’re already seeing the ripple effect.

So far, this year:

• Steam PC prices have increased between $240 and $300.

• Xbox and PlayStation game console prices have jumped between $100 and $150.

• Apple (AAPL) iPads are between $150 and $200 more expensive, and MacBook prices have soared by $100 to $300.

• Computer and server makers Dell Technologies (DELL), HP (HPQ), Acer, Asus, and Lenovo have also raised prices between 15% and 20%.

On top of the price hikes, global smartphone shipments are projected by IDC’s Worldwide Quarterly Mobile Phone Tracker to finish 2026 down nearly 14% from last year. That would represent the largest annual decline in the history of smartphones. IDC also projects a 1.1% decline in 2027.

All of this trickles down to other types of memory as well. With DRAM silicon wafers in such short supply, electronics manufacturers are turning toward alternative memory options, like NAND flash and solid-state drives (“SSDs”). And that higher demand is pushing those prices up.

With all that in mind, it’s fair to ask why memory manufacturers’ stocks continue to fall.

Why Memory Stock Prices Are Falling Despite Record Sales

There isn’t one clear answer as to why memory stocks have been sinking even as memory manufacturers have completely sold out their supply through next year. Multiple factors are contributing to the stocks’ declines.

For one, as the market looks ahead, there are serious concerns about how sustainable this nonstop AI spending is, even if most of the companies spending are flush with cash. Investors cast a wary eye on hyperscalers and other tech companies and wonder whether this head-spinning spending will slow.

Second, the valuation of stocks like Micron and SK Hynix has been bolstered by huge price surges. While those increases may have been warranted based on the seemingly endless demand for their products as well as the subsequent sold-out inventory, the massive growth may already be baked into their stock prices. That leaves Micron and SK Hynix stocks with a paper-thin margin for error if demand for memory wanes even slightly.

Finally, this is just how the market works. Before the recent memory-stock dip, Micron, for example, experienced a huge move higher. For example, investors could have bought Micron shares for $367.85 on April 1. By June 25, the stock’s price rose to $1,213.56. That’s an increase of 230%… in less than three months. After an otherworldly surge like that, Micron was bound to fall back to Earth – which it has done since, falling roughly 27% (as of August 6) since its late-June high.

That’s simply a product of investors selling high and taking their profit, which brings the stock price back down. The market also tends to correct itself when stocks get ahead of themselves (see SpaceX). This volatility is likely the new norm for memory stocks, which will probably continue to see periods of big gains followed by pullbacks. This isn’t a reflection on the products or the demand, however. That remains real.

How New High-Bandwidth Flash Memory Impacts the AI Build-Out

A brand-new technology has entered the mix. On August 3, flash memory giant Sandisk (SNDK) announced that it, along with SK Hynix, had released the High-Bandwidth Flash (“HBF”) technical specification through the Open Compute Project.

Sandisk and SK Hynix were joined in this venture by Google and AI startup Tenstorrent to create this specification, which, according to Sandisk’s press release, “provides companies and developers designing AI inference systems and accelerators with a common technical framework for incorporating HBF technology where larger, near-compute memory capacity and higher bandwidth are needed to improve power and performance metrics and help reduce total cost of ownership.”

Near-compute memory capacity is essentially HBM placed close to computing cores, which is what AI inference systems need to process today’s AI workloads. The new HBF technology accomplishes this by merging high bandwidth with high capacity.

HBF basically bridges the gap between fast HBM and slow SSDs by stacking NAND flash memory, which provides high storage capacities at speeds that rival HBM. This technology has the potential to loosen AI inference bottlenecks and reduce costs, as HBF is substantially cheaper than HBM because it removes expensive DRAM from the equation.

Plus, HBF could potentially alleviate the AI data-center power problem. Most data centers today use HBM built with DRAM, which consumes power while constantly refreshing itself. HBF, using NAND flash memory, doesn’t require those refresh cycles. That means less power is used during AI inference, which could help lower costs.

Keep in mind, however, that HBF is just in its blueprint stage. It’s not a buyable product yet. Sandisk and SK Hynix expect HBF memory samples later this year, with actual AI-inference products possibly available in early 2027. This is a development worth watching, as it could play a large role later next year if it’s deployed at a commercial scale.

What to Watch for Going Into 2027

We know that all of Micron’s, SK Hynix’s, and Samsung’s memory inventory is sold out through 2027. So, what should investors watch for in the memory industry and its stocks going into next year?

We’ve alluded to some of these already, but they all bear repeating.

• The influx of HBM and DRAM memory alternatives: If data-center operators and consumer-electronics companies want memory, they don’t have any other choice but to look for alternatives to HBM and DRAM since there isn’t any available. Keep a close eye on different types of memory, such as NAND flash memory, high-speed graphics memory (GDDR6 / GDDR7), enterprise SSDs, and the emerging HBF memory.

• The companies making those memory alternatives: SK Hynix is still one to watch, as it manufactures high-speed graphics memory, enterprise-grade NAND flash, and data-center SSDs, as well as the sold-out HBM and DRAM. The South Korean company, as mentioned earlier, was also instrumental in the development of HBF. Samsung also produces the same memory types as SK Hynix and is now developing its own HBF solutions. And Micron is one of the world’s leading makers of high-speed graphics memory, NAND flash wafers, and enterprise SSDs.

Besides those “Big Three,” however, there are other major memory players. The largest being Sandisk, the longtime leader in advanced flash memory that partnered with SK Hynix in the development of HBF technology. In fact, Sandisk’s stock has seen some of the biggest growth in the history of the American stock market. A year ago, Sandisk was trading for roughly $42 per share. As of August 6? $1,258.58 per share. That’s a mind-boggling 2,890% increase in one year.

And that’s actually down from its June 25 closing high of $2,335 (which means, at that point, Sandisk was up 4,841% year over year). This backs up my earlier point regarding the volatility of the memory sector. After its absolutely massive surge, the market pulled back as investors sold off.

While NAND flash memory is a strong alternative, it’s also important to keep in mind that Sandisk, Micron, and Samsung have also sold out their full-year 2026 NAND flash capacity, and SK Hynix expects its inventory to sell out by the end of this month.

• The memory-making wild cards: You may not know much about Asian memory manufacturers Kioxia or CXMT. But they’re worth monitoring.

Kioxia, which trades on the Tokyo Stock Exchange, is actually a spinoff from Toshiba, the Japanese electronics giant that invented NAND flash memory. So, it’s no surprise that Kioxia is a global leader in the manufacturing of NAND flash memory as well as SSDs.

ChangXin Memory Technologies (“CXMT”) is a Chinese manufacturer of DRAM chips for smartphones, computers, servers, and other consumer-electronics products.

This isn’t a recommendation to invest in Kioxia or CXMT. Rather, it’s an alert to watch these Asian tech giants because they could very well eat into the profits of Micron, SK Hynix, and Samsung.

CXMT, for example, is quickly ramping up its DRAM production. In fact, it currently holds a significant 8% of the global DRAM market. And CXMT’s late-July IPO on Shanghai’s STAR Market closed around 466% above its offer price, ensuring it has plenty of financial heft (roughly $8.6 billion) behind it to keep expanding its production.

How Risky Are Memory Stocks?

The massive gains have certainly been enticing. Anyone who bought Micron or Sandisk stock at this time last year must like what they see in their portfolios right now. However, as lucrative as the memory industry has been, some risks come with investing in it.

As I mentioned, the memory industry is volatile. Since late 2022 and the start of the AI data-center boom, it has been riding a massive growth wave that hasn’t fully crashed down yet. One only needs to look at the recent stock growth of all the companies discussed in this article.

Until recently, that is. Consider this recent downturn part of the boom-and-bust cycle.

Back in May, William de Gale, a portfolio manager at BlueBox Asset Management, told CNBC that the industry typically experiences “enormous ups and downs” and that, “in the long run, it’s a pretty dreadful industry.”

While de Gale’s view is pretty grim, his point is valid. Investors in the memory industry better buckle their seat belts, because they’re in for a wild ride.

Consider the five-year betas, which measure stock volatility compared with the overall market, for Micron (2.21), SK Hynix (2.41), and  Samsung (1.56), all of which are roughly 1.5 to 2.4 times more volatile than the market.

Investing in memory stocks through 2027 may produce big gains simply because of supply and demand. But what happens in 2028, when more memory is expected to be available? Again, supply and demand come into play. As more product becomes available, prices should drop, which would result in tighter profit margins… and more than likely lead to a pullback in memory stocks.

Is that a guarantee? Of course not. Nothing investment-related ever is. And who knows what may unfold between now and 2028? But simple economics has stood the test of time for a reason. So there’s a strong chance memory stocks suffer as more capacity is manufactured.

Similarly, what happens if hyperscalers and AI companies tighten the reins on their spending? If you’re considering investing in memory stocks, pay close attention to what Amazon (AMZN), Alphabet (GOOGL), Meta Platforms (META), and Microsoft (MSFT) are spending on AI infrastructure over the next year or so. If there’s a downturn in spending, you can bet memory stocks and their investors will feel the consequences.

And don’t forget about companies like CXMT and Kioxia as they expand production and threaten to take a larger bite out of the global memory pie.

The bottom line? Memory stocks are a fascinating play. Despite this recent downturn, which we can likely attribute to simple valuation and market correction driven by selldowns, the industry is as strong as it’s ever been. And with AI’s demand for memory not expected to die down anytime soon, its stocks could bounce back soon.

Regards,

David Engle

Editor’s Note: What ever happened to the AI stock boom? Even AI darlings like Nvidia have essentially gone nowhere since summer 2025. Our friend and colleague at InvestorPlace, Louis Navellier, may have the answer. According to Louis, the AI industry is quietly “staging” ahead of the next great AI breakthrough… a new class of AI he calls “Superintelligence… but better.” How will it trigger a $100 trillion reset of the AI markets. How will the launch of this tech send some stocks to zero, and others soaring? And why does Louis say: Don’t buy or sell an AI stock in 2026 until you see what’s coming next? Go here for the full story (and Louis’ #1 pick).  

The post Memory Capacity Is Sold Out Through 2027. Why Have Micron, SK Hynix, and Samsung Shares Tumbled? appeared first on MarketWise.

Major technology sectors – semiconductors, software, and artificial intelligence (“AI”) – are some of the stock market’s hottest investments right now. With major tech companies investing in AI at record levels, many related stocks have surged to all-time highs over the past year.

For investors looking to ride this investment wave, it can be challenging to pick individual tech stocks. An easier way to get diversified exposure to these companies and find winners is to invest in some of the best tech exchange-traded funds (“ETFs”), often for a low cost.

The best tech ETFs in chips, software, and AI have returned 30%, 40%, and even 50% annually over the past three years – without investors needing to analyze and trade stocks.

While tech darlings such as Nvidia (NVDA) and Broadcom (AVGO) have raced higher for years, the big winners aren’t all trillion-dollar mega-cap stocks. In fact, even smaller chip companies and lesser-known software and AI companies can offer huge returns in the investment boom.

So, the best tech ETFs offer an accessible way for investors of all skill levels to invest in a portfolio of winning stocks across the semiconductor, software, space, and AI sectors.

Top Tech ETFs to Invest in for 2026

How MarketWise Selected These Funds

MarketWise chose its best tech funds based on the following criteria:

• Funds with exposure to the semiconductor, software, AI industries, and others
• Funds with at least three years of strong returns
• A reasonable expense ratio
• No leveraged or inverse funds

1. VanEck Semiconductor ETF (SMH)

This fund tracks the MVIS U.S. Listed Semiconductor 25 Index, which includes 25 semiconductor production and equipment companies. This fund also makes our list of best semiconductor ETFs.

This VanEck fund is the market’s largest semiconductor-focused ETF, and it charges a fair 0.35% expense ratio. Its returns were notably strong over the past year and three years, and even its five-year returns bested the largest chip-focused funds, too.

Assets under management: $70.5 billion

Top holdings: Nvidia, Taiwan Semiconductor Manufacturing (TSM), Broadcom, Micron Technology (MU), Advanced Micro Devices (AMD)

2. Invesco PHLX Semiconductor ETF (SOXQ)

This passively managed Invesco fund tracks the PHLX Semiconductor Sector Index, which includes the 30 largest semiconductor companies listed on U.S. exchanges. The fund’s low expense ratio of 0.19% means that more money stays in your pocket rather than going to the fund manager.

This chip fund recorded the best one-year returns on our list as well as the second-best annualized returns here over the past three years. It’s a testament to the fact that you don’t need a high-cost fund to achieve attractive total returns.

Assets under management: $2.9 billion

Top holdings: Nvidia, Broadcom, Micron Technology, Applied Materials (AMAT), Marvell Technology (MRVL)

3. State Street SPDR S&P Kensho Final Frontiers ETF (ROKT)

This passive fund tracks the S&P Kensho Final Frontiers Index, which includes companies driving the exploration of space and the deep seas.

The fund has had a tremendous run over the past year and three years, and yet it still charges a not-too-costly expense ratio of 0.45%, putting it among the lower half of expense ratios on the list, despite those stellar returns. This State Street fund also ranks in our list of best space ETFs.

Assets under management: $209.2 million

Top holdings: Oceaneering International (OII), Ducommun (DCO), RTX (RTX), Forum Energy Technologies (FET), Heico (HEI)

4. Franklin Intelligent Machines ETF (IQM)

This Franklin actively managed fund invests in stocks that fit the theme of intelligent machines, where AI is driving the “transformation of products, software, systems and machinery as well as product design, manufacture, logistics, distribution and maintenance….,” according to the prospectus.

Despite being an actively managed fund, it doesn’t charge a steep expense ratio, at just 0.5%. And it has delivered some outstanding annual returns over the past year and three years.

Assets under management: $108.7 million

Top holdings: Nvidia, Taiwan Semiconductor Manufacturing, Celestica (CLS), Broadcom, SanDisk (SNDK)

5. Procure Space ETF (UFO)

This passively managed fund tracks the S-Network Space Index, which includes companies with a majority of their sales coming from space-related sectors, including satellite-based telecoms, space technology and hardware, as well as rocket and satellite manufacturing, among others. The fund’s above-average expense ratio of 0.75% has been worth the extra returns you’re getting, at least so far.

This fund’s portfolio is more tightly focused on telecom names such as Viasat and Sirius XM, as well as rocket companies such as SpaceX (SPCX) and Rocket Lab (RKLB). So, the fund may be a better pick for investors with that kind of investment angle on space.

Assets under management: $609.7 million

Top holdings: Viasat (VSAT), Sirius XM (SIRI), Trimble (TRMB), Garmin (GRMN), AST SpaceMobile (ASTS)

6. Invesco AI and Next Gen Software ETF (IGPT)

This passively managed Invesco ETF tracks the STOXX World AC NexGen Software Development Index, which includes “companies with significant exposure to technologies or products that contribute to future software development through direct revenue,” per the prospectus.

The fund’s one-year performance at more than 80% is nothing short of amazing, while its three-year annualized performance approaches 40% – all for a reasonable expense ratio.

Assets under management: $1.2 billion

Top holdings: Advanced Micro Devices, Alphabet (GOOGL), Nvidia, Meta Platforms (META), Micron Technology

7. Amplify Bloomberg AI Equal Weight ETF (AIVC)

This passively managed Amplify fund tracks the Bloomberg AI Value Chain Equal Weight Total Return Index, which includes cloud computing, semiconductor, and hardware companies that form the basis of AI technologies. The fund uses an equal-weight approach, where stocks have a broadly similar position size in the portfolio.

The fund’s price has effectively doubled over the past year, while its 44% annualized returns over the past three years would have generated some significant wealth. This fund’s returns have been among the best on this list of superstars, and it charges a not-too-high expense ratio.

Assets under management: $120.9 million

Top holdings: Alibaba (BABA), Atlassian (TEAM), Hewlett Packard Enterprise (HPE), Microsoft (MSFT), Snowflake (SNOW)

Are Tech Stocks a Good Long-Term Investment?

Tech stocks have long been among the market’s most popular investments. The best stocks offer scalability – that is, their profits can grow much faster than their sales. As they grow, their profits often soar as their operating margin improves.

Semiconductor stocks have performed very strongly in the past few years, as Big Tech companies, such as Microsoft and Alphabet, have poured money into AI investments. However, much of this high return has occurred in the past year, with two funds in the list up about 100% or more.

This level of performance will be hard-pressed to continue over time, even if semiconductors do post attractive long-term returns. It’s effectively impossible for a stock or fund to put up this level of return over extended periods. So, investors should expect returns to come back to more normal levels, say 20% annually over time. Even this more manageable level will build huge wealth over time.

For investors who like the prospects of the top tech stocks, it’s important to invest cautiously, especially after the phenomenal returns over the past year and three years. Take a long-term view on the market and invest regularly over time. Doing so helps reduce your risk of buying at a relatively high point, and it still can deliver attractive long-term returns.

Regards,

James Royal, PhD

Editor’s Note: One company quietly beat Apple, Amazon, and the S&P 500 — combined. Over the long run it has returned more than 8,300%… enough to turn $10,000 into $830,000. Yet most investors have never heard of it. Former fund manager Whitney Tilson says right now it’s trading at a rare discount — and he’s revealing the name and ticker, free of charge. Click here for the details…

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In Tolkien lore, the “palantíri” were indestructible dark crystals used to “see” across vast distances telepathically. The stones themselves weren’t necessarily dangerous. But the person who controlled them could be a major threat… Alex Karp, who named his company after these stones, seems to wield this massive power. And Wall Street is hanging on his every word.

This past Monday, Aug. 3, Palantir Technologies (PLTR) reported an “otherworldly” quarter as revenue accelerated to its fastest pace ever. At the same time, U.S. commercial sales grew 149% year-over-year, and management lifted full-year guidance by roughly half a billion dollars.

The next morning PLTR stock rose about 30%, its largest single-day move in years, and closed back above a technical line it had failed to hold all year. So, is Palantir stock a buy? Karp’s conference call seemed to answer with a simple idea: in the age of interchangeable frontier AI models, the value goes to whoever holds the stone.

And right now, that’s Palantir.

Palantir’s Q2 2026 Earnings, by the Numbers

Palantir posted second-quarter revenue of $1.935 billion, up 93% year-over-year, its highest growth rate as a public company. Adjusted earnings came in at 41 cents per share against consensus near 35 cents, the ninth straight beat. GAAP earnings also reached 41 cents, a sign the profits were real rather than a product of adjustments.

The U.S. business is what carried the quarter. U.S. commercial revenue surged 149% to $764 million. U.S. government revenue grew 90% to $809 million. Combined, U.S. revenue reached $1.573 billion, up 115%, now more than 81% of the total.

The forward-looking metrics have changed how analysts are modeling the company.

Net dollar retention climbed to 157%, up 700 basis points from the prior quarter, meaning existing customers spent 57% more than they did a year earlier. U.S. commercial total contract value bookings hit $2.132 billion, up 153% and nearly $800 million above the prior record. Adjusted operating income was $1.194 billion, a 62% margin. Adjusted free cash flow reached $1.22 billion, a 63% margin. The company’s Rule of 40 score, which adds revenue growth to profit margin, reached 155%, well above the 40 threshold considered elite.

Management raised full-year 2026 revenue guidance to a range of $8.15 billion to $8.158 billion, roughly 82% growth at the midpoint, up from $7.65 billion to $7.66 billion. The company also guided U.S. commercial revenue above $3.424 billion, at least 134% growth. “This quarter was otherworldly,” Karp said in the release.

Palantir’s “SaaSmageddon” and Why Better AI Makes PLTR More Valuable

On the other side of the AI boom, one particular “anti-trend” dominated the discourse for much of 2026: “SaaSmageddon.” The idea is simple: if AI agents can do the same work as certain software, then enterprises will opt for the AI over a per-seat subscription model.

By SaaStr’s measure, software’s forward price-to-earnings (P/E) multiple collapsed from 84.1 times at the 2020-2022 peak to 22.7 times by March 2026, the first time the sector traded below the S&P 500 on that basis. Salesforce (CRM) fell about 30% and Workday (WDAY) fell 33% over that same stretch.

Initially, Palantir itself was part of the SaaSmageddon thesis, with investors worried the company would be eaten alive by frontier AI. But Karp turned that criticism of his company on its head, going to the media to argue that raw model access is the commodity, and value only goes to the layer that connects AI models to proprietary data and workflows.

This layer is what Palantir calls its “Ontology,” which is wrapped in its Artificial Intelligence Platform (AIP) and staffed with engineers who deploy at client sites. Take its partnership with Nvidia (NVDA): Palantir runs Nemotron models air-gapped in customer-controlled environments. And, as Karp notes, more and more enterprises are refusing to become “vassals” of the large-language labs.

Bottom line: The cheaper AI models become, the more valuable the plumbing (the layer that governs and connects AI to enterprise operations) becomes. If you needed evidence of that, look no further than the 157% net dollar retention metric Palantir posted this quarter. If SaaSmageddon were affecting Palantir, customers would not be expanding their usage. This marks the first quarter with hard evidence against that thesis.

Is Palantir Stock Still a Buy After Its 30% Pop?

Palantir’s recent earnings surge repaired some of the technical damage to the stock, but PLTR is still down ~13% as of this writing. Let’s talk about this a bit before getting to the meaty bits.

PLTR stock peaked around $207.52 in November 2025, before collapsing throughout 2026 and bottoming near $106 in June. That’s a ~49% drawdown from Palantir’s highs. Heading into earnings, shares were still close to a 30% shave YTD. Palantir stock formed a death cross when it fell below its 200-day moving average (MA) in February. After earnings, the stock is back above the 200-day MA (around $153). Nevertheless, it’s still below its old high, so there’s more room for PLTR to run.

After the recent quarter, several analysts lifted (or affirmed) their Palantir stock price targets. Citi’s Tyler Radke lifted his target to $245 from $200, Mizuho to $215, and D.A. Davidson to $200, while Bank of America reiterated its Street-high $255 target. Deutsche Bank’s Brad Zelnick upgraded the stock to “Buy” at $200, calling Palantir “a time traveler, having already arrived in the AI future others are still aspiring towards.” Per TipRanks, the consensus is a “Moderate Buy” across 21 analysts, with a pre-surge average target near $187 to $189.

On the road to $200+, Palantir’s nitrous boost, if you will, is the sovereign AI argument. That is, if enterprises and governments increasingly reject frontier AI labs in favor of AI they own and control, then it is Palantir that’s best-positioned to be the operating layer for such demand.

Still, the risks involved with investing in Palantir stock cannot be overstated.

The first big risk is valuation.

Even after the drawdown and even on raised guidance, PLTR trades near 43 to 50 times forward sales, against a software peer group closer to five times enterprise-value-to-revenue. RBC’s Rishi Jaluria kept an “Underperform” rating with a $90 target, writing that PLTR “remains the most expensive stock across our RBC All-SaaS universe at ~40x EV/CY26” and that “we struggle to underwrite a scenario that justifies current valuation levels.” Morningstar’s Mark Giarelli pegs fair value at $153, below where the stock closed after the pop. A move from a 77-times forward P/E down to a still-rich 40 times, with no change in estimates, would roughly halve the stock.

The second big risk is political contagion.

On Aug. 5, the Centre for International Corporate Tax Accountability and Research published an analysis, commissioned by European public-service unions, estimating Palantir’s global effective tax rate at 1.4% on pre-tax profit of about $1.66 billion, with under $21.7 million in global net corporate tax and zero U.S. federal tax in 2025, achieved by booking European revenues in the U.S. parent. Unison’s Andrea Egan said “systems that enable tax to be shirked on an industrial scale clearly have to change.” But Palantir calls this sort of transfer pricing “entirely standard practice.”

That’s not all, however.

The European backlash to Palantir is pulsating and tangible. Germany’s domestic intelligence service, the BfV, picked French firm ChapsVision over Palantir, the German army cut ties entirely, France’s Thales is courting Belgium, the Netherlands and others, and Palantir is suing London’s Mayor’s Office for Policing and Crime (MOPAC) after losing a Metropolitan Police contract. All the while, a £330 million NHS contract faces parliamentary pressure. As such, Palantir’s international revenue slipped to roughly 19% of the total in Q2, from 26% a year earlier. For a company billing itself as selling sovereignty, there’s an irony in being the sovereign no European nation actually wants.

So again, is PLTR stock a buy? Going only off Palantir’s growth, it’s an album with a story told in two sides:

The A-Side: An American growth machine and sovereign AI beneficiary.

The B-Side: A European trust deficit.

The verdict: Palantir delivered the quarter the bulls were waiting for, and the fundamental case is stronger than at any point in its history. But the valuation now prices in flawless execution, and the European resistance caps the global ambition the multiple assumes. PLTR is a buy for investors who can hold through 20%-plus swings and who are buying the operating layer rather than the price. For everyone else, the layers around Palantir are cheaper

3 Palantir Alternatives to Buy

If data and workflow layers increase in value the more frontier models are commoditized, then there are several stocks to buy that own those layers at a fraction of Palantir stock’s multiple. Here they are, in no particular order:

PLTR Alternative No. 1: Snowflake (SNOW)

Snowflake is the proprietary-data layer. Its fiscal Q4 2026 product revenue grew 30% to $1.23 billion, remaining performance obligations jumped 42% to $9.77 billion, and net revenue retention held at 125%. More than 9,100 accounts use its AI weekly, and consumption pricing means revenue scales as AI workloads grow. It trades near 12 to 14 times forward sales, rich for software but well below Palantir. The catch is GAAP losses and a forward P/E near 124. Clean, governed data is the fuel every enterprise AI system needs, and Snowflake stores it.

PLTR Alternative No. 2: ServiceNow (NOW)

ServiceNow is the workflow and agent-orchestration layer, what CEO Bill McDermott calls the “AI control tower.” Q2 2026 subscription revenue grew 24.5% to $3.877 billion, AI annual contract value crossed $1 billion for the first time, and agentic AI production deployments grew ninefold in nine months. The stock fell about 37% in 2026 on the same SaaSmageddon fear, leaving it near 5.8 times enterprise-value-to-revenue, a discount that looks misplaced against accelerating growth. As enterprises deploy fleets of agents, someone has to govern them. ServiceNow is building to be that someone.

PLTR Alternative No. 3: MongoDB (MDB)

MongoDB is the operational data backbone of AI-native applications. Fiscal Q4 2026 revenue grew 27% to $695.1 million, Atlas grew 29%, and the company posted its first GAAP-profitable quarter. Its document model plus integrated vector search and Voyage AI embeddings puts it under the applications developers are building on top of models. It trades far below Palantir’s revenue multiple.

The Bottom Line on Palantir Stock

Palantir’s earnings, much like the palantíri seeing-stones, do not lie. The company is more valuable than ever to enterprises, especially those who wish to free themselves from frontier model vassalage.

Yet, the road ahead for Palantir stockholders isn’t clear of wheel-breaking stones. Both the valuation question and the resolution to the European backlash still encircle the company. For the remainder of 2026, Alex Karp needs to prove that the company selling sovereignty is sovereign in its own right.

Editor’s Note: What ever happened to the AI stock boom? Even AI darlings like Nvidia have essentially gone nowhere since summer 2025. Our friend and colleague at InvestorPlace, Louis Navellier, may have the answer. According to Louis, the AI industry is quietly “staging” ahead of the next great AI breakthrough… a new class of AI he calls “Superintelligence… but better.” How will it trigger a $100 trillion reset of the AI markets. How will the launch of this tech send some stocks to zero, and others soaring? And why does Louis say: Don’t buy or sell an AI stock in 2026 until you see what’s coming next? Go here for the full story (and Louis’ #1 pick).  

Is Palantir Stock a Buy? Your Questions Answered (FAQ)

Is Palantir stock overvalued? By conventional measures, yes. At roughly 43 to 50 times forward sales, it is among the most expensive large-cap software stocks, and bears like RBC see fair value near $90. The counter is that Palantir grows several times faster than peers with 60%-plus margins, which no traditional software comparison captures.

Is it too late to buy Palantir stock? It is too late to buy it cheap. It closed near $162 after the pop, below its $207 high but far above its June low near $106. Investors buying now are paying for years of execution, and the technical reclaim of the 200-day moving average argues the trend has turned.

What are the best alternatives to Palantir? For exposure to the same “own the layer” thesis at lower multiples: Snowflake for data, ServiceNow for workflow and agent governance, and MongoDB for the operational backbone.

Will Palantir stock keep going up in 2026? Analysts lean yes, with a median target near $200, but the range runs from $90 to $255, which tells you how uncertain the answer is. The upside needs continued triple-digit U.S. commercial growth. The downside is a valuation reset or a widening European backlash.

The post Is Palantir Stock a Buy After Earnings? The Bull Case, Plus 3 Alternatives appeared first on MarketWise.

There are two wildly different artificial-intelligence (“AI”) tales showing up in Big Tech’s latest earnings.

On one hand, you have cloud-focused hyperscalers like Alphabet (GOOGL), Microsoft (MSFT), and Amazon (AMZN) reporting stellar results that, combined, helped the companies add nearly $1.5 trillion to their market capitalizations.

On the other hand, you have Meta Platforms (META), Apple (AAPL), and Tesla (TSLA) – three tech giants that still don’t seem to know what to do with AI – that lost nearly $450 billion in combined market value after reporting earnings last week.

At this point, the message from Wall Street seems crystal clear: If you don’t have a firm AI strategy already producing tangible financial results, we don’t have faith in your business.

The Cloud-Focused Winners of This Past Quarter: Alphabet, Microsoft, and Amazon

It’s no coincidence that the most successful tech companies this past quarter have been the ones with a sound AI strategy. The winners here have all established themselves as AI cloud-computing forces, as you’ll see below.

Alphabet

Alphabet, Google’s parent company, reported its 2026 second-quarter earnings on July 22.

Some of the highlights include:

• $119.8 billion in revenue, a 24.2% year-over-year increase

• $40.8 billion in operating income, up 30% year over year

• A staggering $9.11 in earnings per share (“EPS”), which shattered expectations of roughly $3.00 and represented a year-over-year increase of 294%

And it was the cloud business that drove many of these gains. Google Cloud revenue soared to $24.8 billion for the quarter, an 82% year-over-year increase. Google’s cloud division also reported $8.8 billion in operating income, a 35.6% operating margin (up from 20.7% the year prior), and an impressive cloud backlog of $514 billion.

Google Services, which includes Gmail, YouTube, and Google Search, still drives most of the business. In the second quarter of 2026, the category earned $94.5 billion in revenue, up 15% year over year. Operating income jumped 20% to $39.5 billion, and YouTube ad revenue increased by 13%.

I must point out, however, that Alphabet stock took a roughly 7% dip after its earnings call despite massive revenue growth. All the AI-related spending pushed the company’s free cash flow (“FCF”) below zero for the first time since Alphabet’s public-trading debut.But Alphabet quickly bounced back, gaining more than 17.5% between July 23 and August 3.

So, while Alphabet has successfully monetized AI, its AI spending is still worth monitoring moving forward.

Microsoft

Microsoft reported its fiscal fourth-quarter 2026 earnings on July 29, exceeding Wall Street expectations behind strong performance by – you guessed it – its Azure cloud services and AI growth.

Among Microsoft’s fourth-quarter highlights were:

• $90 billion in revenue, up 18% year over year, and full-year revenue of $331.8 billion, also up 18%

• $40.6 billion in operating income, an 18% year-over-year increase, and full-year operating income of $155.2 billion, with year-over-year growth of 21%

• GAAP (generally accepted accounting principles) net income of $35.8 billion (up 31%) and non-GAAP net income of $35.3 billion (up 22%)

• GAAP diluted EPS of $4.81 (up 32%) and non-GAAP diluted EPS of $4.74 (up 23%)

And just as Google Cloud drove Alphabet’s second-quarter success, Microsoft Cloud was a huge difference-maker for the company in its fourth quarter.

Microsoft Cloud generated $59.3 billion in revenue, growing 27% year over year. Drilling down a bit more, revenue for the company’s Intelligent Cloud – which includes server products and cloud services mainly anchored by Microsoft Azure, enterprise server software, and cloud-based AI and data platforms – reached $39.3 billion, a 32% year-over-year increase.

Intelligent Cloud revenue actually surpassed that of Microsoft’s Productivity and Business Processes segment. This unit, which includes Microsoft 365, LinkedIn, and Dynamics 365, delivered $37.8 billion in revenue.

And Microsoft’s cloud services continue to grow yearly. Microsoft 365 Commercial cloud revenue increased by 16%, and Microsoft 365 Consumer cloud revenue grew by 24%. Azure and other cloud-services revenue surged 43%.

Not to mention that Azure revenue passed $100 billion for the first time during fiscal 2026. Plus, Microsoft 365 Copilot passed the 30 million paid seats milestone, and the company added 88 new data centers during the year to support demand for its rapidly growing AI services.

Amazon

Amazon enjoyed another stellar quarter, reporting $200.6 billion in net sales – up 20% year over year – during the second quarter. Of course, much of Amazon’s revenue is driven by its ginormous e-commerce and retail machine.

But Amazon Web Services (“AWS”) is steadily closing the gap as the company’s cloud platform continues to make money hand over fist.

In the second quarter:

• AWS sales grew 37% year over year to $42.2 billion and reached a $169 billion annualized run rate.

• AWS operating income jumped from $10.2 billion to $16.6 billion year over year.

• Amazon’s AI and custom chips – which include Trainium, Inferentia, Graviton, and the Nitro System – doubled last year’s annualized revenue run rate.

During the earnings call, Amazon President and CEO Andy Jassy said, “AWS is booming, growing 36.7% year-over-year in Q2 – our fastest growth in 18 quarters – and our AI and Chips businesses each eclipsed run rates of more than $25 billion.”

And this is just the tip of the iceberg. Amazon’s second-quarter earnings press release reads like a laundry list of AI achievements and milestones.

That, plus the results delivered by Alphabet and Microsoft, is exactly what investors and analysts want to see from companies focused on AI. It’s no longer good enough for a tech company to say, “We’ve got really cool ideas and AI innovations coming up, and they’re going to change the world.”

Wall Street is past the point of promises and grand visions. It wants tangible AI strategy, technology, and – most importantly – results. The companies above have been delivering that already. The next three… well, we’re all still waiting.

This Past Quarter’s Big AI Losers: Meta, Apple, and Tesla

Alphabet, Microsoft, and Amazon have developed clear AI strategies and executed them. But Meta, Apple, and Tesla are fumbling around in the dark, still not entirely sure what to do with AI and how to make something tangible and useful out of it – and, more importantly, something that will move both the top and bottom lines.

Meta

In early July, I wrote a piece on Meta about how it’s finally getting into the AI cloud business, and stated:

It’s no secret that Meta’s forays into AI have not gone well.

When I analyzed Meta’s massive layoffs in late May, I wrote:

[CEO Mark] Zuckerberg’s laser focus on Meta’s AI ambitions is understandable, considering the company has fallen behind many of its competitors.

Earlier this year, after pouring billions into the project, Meta delayed the release of its new foundational AI model (code name: Avocado, official name: Muse Spark) until April due to performance issues…

That delay was just the latest AI setback for Meta. In February, the company stopped the release of its chatbot because internal testing found that it egregiously (between roughly 55% and 67% of the time) failed to block dangerous content involving minors…

On a less disturbing note, back in September 2025, Meta’s AI repeatedly – and rather embarrassingly – failed during a live demonstration of the company’s new smart glasses at its Meta Connect event.

All of this, to me, leads to a simple question: What exactly is Meta’s AI goal?

Now we know. Meta, in fact, had no specific AI goal. The company took more of a “throw everything at the wall and see what sticks” approach. Unfortunately for Meta, hardly anything stuck to the wall.

So, Zuckerberg wisely pivoted, with Meta announcing that it plans to sell access to its expansive – and excess – AI compute power and models.

Interestingly, with Meta finally recognizing the value of the AI cloud space, it holds an advantage over its hyperscale competitors, as mentioned in my July 8 article:

What we do know is that Meta is planning to sell access to its AI-infrastructure models. Like Amazon’s serverless Bedrock platform, Meta would operate the hardware and data centers that power the AI models while charging developers for access. But that’s only one piece of Meta’s reported cloud puzzle.

The other is Meta Compute, a division that plans to sell raw compute capacity built specifically for AI computing, as a neocloud provider such as CoreWeave or Nebius does.

Meta’s two-pronged approach – selling both infrastructure access and raw compute capacity – is something AWS, Google Cloud, and Azure simply can’t currently offer.

Given this recent development, it may seem strange to see Meta listed in the “losers” portion of this article.

A look at its recent performance helps explain why:

• Meta’s year-over-year revenue did increase by 28% to $60.8 billion during the second quarter. Still, its costs and expenses skyrocketed by 55% to $42 billion, which drove income from operations down 8% and operating margins down by 12 percentage points.

• Net income fell 14% to roughly $15.8 billion.

• Diluted EPS dropped 13% to $6.18.

• Worst of all, Meta’s FCF plummeted 91% year over year thanks in part to capital expenditures (“capex”) that increased by roughly $14 billion year over year.

The numbers are rough. But the numbers aren’t even the main plot point in Meta’s sad AI story. It’s the decisions that were – and weren’t – made years ago on how to turn AI into a profitable business segment. Amazon, Microsoft, and Alphabet figured it out. Meta is just now putting the puzzle together.

It took Meta until 2026 to realize it could monetize its excess raw AI compute capacity and application programming interfaces (“APIs”) by renting them out to other businesses. It will take some time for this pivot to make an impact on Meta’s balance sheet.

Plus, as Meta continues to invest in building data centers, it does so with the money it makes from its primary advertising business, not to mention plenty of borrowing. Amazon, Microsoft, and Alphabet, on the other hand, use capital generated by a consistent stream of dedicated cloud revenue.

Josh Gilbert, lead APAC analyst at online investing platform eToro, said it best:

Meta is spending like a hyperscaler without a hyperscaler’s business model. Microsoft, Alphabet and Amazon can point their data center dollars at cloud businesses that sell compute straight back out the door, but Meta doesn’t ​have the same outlet, so every dollar of ​build-out leans on the ads business.

This has investors wondering whether or not they’re looking at another Metaverse-like flop. What we do know, however, is that Meta’s AI strategy still isn’t clear, and its second-quarter earnings reflect as much.

Apple

Apple spent a few days in late July reclaiming its position as the world’s most valuable company. It didn’t take long for Nvidia (NVDA) to nudge past Apple again, however. On July 31, Apple lost nearly half a trillion dollars in market value.

Why? Primarily weak fiscal fourth-quarter earnings guidance. Apple’s projected next-quarter growth of 9% to 11% fell short of Wall Street’s roughly 12% expectation. And the primary reason for the soft guidance is a shortage of memory chips and processors that Apple needs for iPhone and Mac computer production.

AI is hoarding these components, leaving precious few for consumer-electronics makers like Apple, forcing them to raise prices and tighten margins. Apple’s outgoing CEO Tim Cook labeled the supply-chain issues as “very significant” during his final earnings call. This all helped push Apple stock down nearly 10% on July 31.

The drop in stock doesn’t negate Apple’s strong third quarter, which included:

• $109.4 billion in revenue, a 16% year-over-year increase
• $29.8 billion in net income, up 27% from last year
• A third-quarter record operating cash flow of $34.4 billion
• $2.02 in diluted EPS, a 29% jump from last year
• A 50.1% gross margin, a year-over-year bump from 46.5%

As far as Apple’s AI strategy is concerned… well, it doesn’t really have one. And that has suited Apple just fine. Unlike most of the other “Magnificent Seven” tech companies, Apple entered the AI build-out fray very quietly and thoughtfully, which is one reason its stock has performed more steadily than the others.

My colleague Jim Royal recently wrote about Apple’s decision to stay out of the AI frenzy, stating:

One of the key takeaways for investors here is that companies can still deliver excellent returns by avoiding the reckless spending that’s driving the AI bubble. By staying focused on its tried-and-true investment discipline, Apple’s management has delivered for shareholders.

Unfortunately for Apple, even as it keeps itself relatively insulated from the day-to-day AI-driven market chaos, it’s still being impacted, primarily through the supply-chain bottlenecks. That alone was enough to contribute to its weak forecast and massive loss in market value.

Tesla

Finally, we have Tesla, which suffered its worst day in years on July 23, following its second-quarter earnings call. The company’s stock lost 14.5% that day, driven by a huge earnings miss, significant cash burn, tight margins, and no real answers or timelines on upcoming production.

Some of Tesla’s second-quarter reporting included:

• A $0.33 non-GAAP EPS that fell well short of Wall Street’s $0.54 expectation

• A 26% year-over-year overall revenue increase

• An operating margin that plunged from an already-tight 4.1% last year to 1.4%

• GAAP net income that fell 5%, while non-GAAP net income nosedived by 17% year over year

But Tesla’s FCF during the second quarter… it was absolutely ghastly. It fell off a cliff, dropping 848% year over year (yes, 848%) to negative $1.09 billion. That’s what $5.8 billion in capex will do to FCF.

Yes, that capex is going toward AI computing and chipmaking infrastructure to support Tesla’s full self-driving systems and its robotaxi and humanoid robotics production. Does that make them worthwhile investments? We’ll see. But it’s quite clear that analysts and investors are growing impatient with Elon Musk’s inability to offer firm details or updates on these projects.

During the second-quarter earnings call, Musk took several questions from investors on these topics, which he has been promoting as life-changing for years. But Robotaxi is only available in limited areas in the U.S., and Optimus is nowhere near ready for consumers to purchase.

Investors wanted concrete answers on rollout timelines, as Musk has missed most of his own target dates… as he is known to do. Instead, Musk talked around quite a bit without providing any real answers, and even brought up the many obstacles Tesla is facing, specifically regarding Optimus.

At a time when consumers may be looking closely at electric vehicles, considering the escalating gas prices stemming from the war in Iran, Tesla is moving away from its automotive success and funneling its capital into AI so Optimus and Robotaxis may someday come to fruition.

Not surprisingly, this isn’t sitting well with investors, as Tesla continues to burn through money with very little to show for it.

What Do These Recent Earnings Mean for Investors?

If you’re considering investing in a company not only with real AI ambitions, but with proven results, substantial revenue, and a solid AI strategy for the coming years, Alphabet, Microsoft, and Amazon look like more certain bets than Tesla, Apple, or Meta.

What’s important to remember, however, is that AI isn’t the only revenue stream for these companies. In most cases, it’s not even their primary revenue source.

Meta has its incredibly successful advertising model, which generates nearly 98% of its total revenue. Amazon’s colossal retail arm accounts for roughly 40% of its revenue, as of last year. In 2025, Google Search & Other brought in roughly 56% of Alphabet’s total revenue. And more than 70% of Tesla’s 2025 revenue came from automotive sales.

Only Microsoft can count AI/cloud business as its biggest revenue driver, with around 39% coming from its Server Products and Cloud Services unit in fiscal 2026.

All of that is to say companies like Meta, Apple, and Tesla aren’t necessarily bad investments. But there are warning signs that shouldn’t be swept under the rug, either.

Year to date, as of August 3, Meta stock was down roughly 11%, and Tesla had plunged 28%. Apple, however, was up around 12%, because it knows what it’s good at – innovating, making high-grade consumer electronics that its customers adore, and locking them into an extremely sticky ecosystem that, well, they also adore.

As for the winners here, Amazon is up roughly 23% year to date, Alphabet has increased 19.3%, and Microsoft is up around 0.8%, mostly due to high AI-related capex in 2026.

The bottom line for investors is that the companies successfully monetizing AI (Amazon, Microsoft, and Alphabet) are in far better shape – AI-wise – than those that are simply throwing money into the AI ether without having a firm, specific strategy for that spending. Looking at you, Mark and Elon.

Regards,

David Engle

Editor’s Note: CNBC nicknamed him “The Prophet.” He called Netflix at a split-adjusted 78 cents, Apple at 38 cents, and Amazon at $2.80 – long before anyone knew their names. He’s appeared on 60 Minutes twice. Now former hedge-fund manager Whitney Tilson is naming what he calls “America’s Greatest Retirement Stock” right now – one company at the center of the AI and energy boom. He’s giving away the name and ticker, free. Click here…

The post Big Tech Earnings: The AI Boom’s Biggest Winners and Losers appeared first on MarketWise.

SpaceX (SPCX), which I’ve long called the most overvalued large-cap stock of all time, reported earnings yesterday after the close…

And even the greatest stock promoter of all time, CEO Elon Musk, couldn’t keep the shares from tumbling as much as 13% early this morning.

Year over year, revenue grew 92% – from roughly $4.1 billion to $7.8 billion. Meanwhile, losses from operations narrowed from about $970 million to $143 million. And “Segment Adjusted EBITDA” (earnings before interest, taxes, depreciation, and amortization) grew from around $1.2 billion to $3.5 billion.

SpaceX also said that cash provided by operating activities rose from roughly $351 million to $3.5 billion. However, the company only reported “Selected Cash Flow Information” for the first six months of this year versus that period last year – which is totally unacceptable for one of the most valuable companies on the planet.

Take a look at this breakdown from page 10 of the earnings release:

So why did the stock take such a hit?

Massive Capex Spending Swallows Cash Flows

In part, it’s because of a massive increase in capital expenditures (“capex”) – largely in the company’s AI division (which includes chatbot Grok and social media platform X).

Take a look at the breakdown here on page 3 of the release:

The company’s roughly $28.5 billion capex amounted to more than 8 times its $3.5 billion operating cash flow. As a result, SpaceX’s free cash flow (“FCF”) was a horrific negative $25 billion in the first six months of the year.

This is consistent with what I wrote in my June 5 e-mail. SpaceX has two great businesses and one terrible one:

… the company’s gem is Starlink. It more than doubled its subscriber count from the first quarter of 2025 and is highly profitable…

Though it lost money in the first quarter, the space-launch business is also unparalleled. It accounts for more than 50% of all worldwide orbital launches and more than 80% of all mass sent into orbit.

But a totally unrelated segment, xAI, is dragging down these two great businesses. It’s burning huge amounts of cash in an attempt to keep up with its much larger competitors – not just [Alphabet’s (GOOGL)] Google but also Meta Platforms (META), Amazon (AMZN), and Microsoft (MSFT), among others.

SPCX Float Creates a Drag on its Share Price

Another major factor weighing on the stock is that the number of SpaceX shares that are eligible to trade (its so-called the “float”) nearly tripled. SpaceX sold 555.6 million shares in its June 12 IPO at $135 each – raising about $75 billion while valuing the company at roughly $1.77 trillion.

Under the IPO prospectus, up to 911.5 million shares – about 20% of the early-release eligible pool held by employees and most pre-IPO investors – become transferable just after the first earnings report.

At SpaceX’s price early this morning, that’s around $100 billion of stock.

I have to imagine that many holders will be eager to sell to diversify – especially in light of the stock’s absurd valuation.

And that’s the main problem with SpaceX’s stock…

With a tiny float of 4% to 5% since the June 12 IPO and a huge $500 million payoff to the Wall Street banks – whose analysts of course debased themselves pumping it (as I covered in my July 9 e-mail) – the stock was manipulated to the moon.

What SpaceX Might Actually Be Worth

The company just reported around $7.8 billion in quarterly revenue. Annualized, that comes out to roughly $31.4 billion.

But on the conference call, Musk said SpaceX will reach a $100 billion annual revenue run rate (“ARR”) by the end of the year thanks to AI compute deals.

This is as ridiculous as his claim a year ago that, by the end of 2025, Tesla (TSLA) would be serving half of the American population with fully autonomous robotaxis. The actual number at year end was roughly 15 robotaxis in one city – Austin, Texas.

Being extremely generous, I’ll give SpaceX a $50 billion ARR by year-end and an equally generous multiple of 10 times revenue. That’s $500 billion.

The stock price decline early this morning put the market cap at around $1.5 trillion. That would mean the stock would be overvalued by at least 3 times – by roughly $1 trillion.

I continue to believe that SpaceX is the most overvalued large-cap stock ever.

Editor’s Note: This article was adapted from today’s edition of Whitney Tilson’s Daily. Every day, Whitney emails his readers with his comments on the most important topics of the day, including stocks he’s investigating… great articles he has read… his media and podcast appearances. You can sign up here to receive all of Whitney’s daily thoughts and insights.

The post SpaceX Earnings Show Stock Overvalued by 3x appeared first on MarketWise.

Soaring prices for computer memory chips, skyrocketing debt at hyperscalers, and price wars have been worrisome for investors in the artificial intelligence (“AI”) trade. You can add the Federal Reserve to that growing list of concerns, as the U.S. central bank may raise interest rates at its next meeting in September.

The Fed is looking to reduce inflation, which has risen significantly from the bank’s long-term target of 2% in recent months. From a recent low of 2.4% in February, inflation rose to 4.2% in May but then dipped back down to 3.5%. Fed policymakers are waiting to see if inflation cools further or whether soaring energy prices will become more embedded in the economy.

The soaring inflation is due to President Trump’s tariffs as well as the effects of the Iran War, which has drastically cut the supply of oil coming from the Persian Gulf. Rising oil prices affect almost all sectors of the economy, which then raise their own prices to offset the impact.

Newly appointed Fed chair Kevin Warsh has talked a good game about getting inflation under control. But his reputation – a key reason that President Donald Trump appointed him – is as someone who would be more interested in keeping interest rates low.

Currently, there’s about a 60% chance that the Fed raises rates by 0.25 percentage points at its September meeting, according to the CME Group’s FedWatch. It also estimates the odds at more than 33% that the Fed will raise rates by 0.50 percentage points or more in total by its December meeting.

If the Fed raises short-term rates, it could put significant pressure on an increasingly tenuous funding environment for the AI industry. Rising rates would reduce the affordability of credit for funding the AI build-out. Higher rates translate into less money flowing through the industry, while AI firms desperately need adequate access to capital to continue.

But if the Fed sees inflation staying low, AI stocks may rebound hard from a ripping point. That’s why it’s important to keep a close eye on inflation and the Fed’s response to it.

AI Requires Massive Debt Financing

The AI build-out – the massive spending going into AI data centers, costly memory chips, and AI model training – can continue at its breakneck pace only as long as firms can borrow cheaply.

The biggest AI investors, including Amazon (AMZN), Microsoft (MSFT), Alphabet (GOOGL), Oracle (ORCL), and Meta Platforms (META), are borrowing hundreds of billions of dollars so that they can keep building the capabilities that they say will be needed in future years.

In total, the big four hyperscalers – everyone above but Oracle – are expected to spend some $725 billion this year. Many analysts expect this figure to top more than $1 trillion in 2027. They simply don’t have the cash flow to pay for this level of build-out without borrowing heavily.

In fact, the borrowing has already become so intense that investors are beginning to pull back somewhat. They’re requiring incrementally higher yields on debt being issued by even top-tier borrowers, such as the hyperscalers above, and showing less overall interest in buying bonds.

For example, last month, Amazon marketed $25 billion in bonds and had to raise the rates on its longest-duration notes. Plus, demand was not as robust as it had been. Orders came in at just 2.5 times the bonds being offered, compared with 3.2 times in a March debt offering.

In the case of Oracle, investors are becoming even more skittish about the company’s debt. The cost to insure the company’s bonds against default over the next five years, through derivatives known as credit default swaps, has risen aggressively since mid-2025 and keeps rising.

Oracle is already substantially indebted and will likely have to sell even more bonds to meet its investing commitments. S&P Global Ratings recently downgraded Oracle’s debt to one notch above “junk” status, and a further downgrade could raise its future cost of borrowing. This setup means that Oracle stock could fall another 50% after already being cut in half earlier this year.

Meanwhile, less well-heeled AI players such as CoreWeave (CRWV) are being forced to cough up junk bond-like yields for much more modest borrowings. It’s negotiating a bond at a rate 5.5 percentage points above the benchmark, or up to 1.25 percentage points above its initial talks. Already, that amounts to a yield of more than 9%. Firms needing to raise money could see their benchmark rate rise and therefore their actual rate, if the Fed decides to raise short-term rates.

So, if the Federal Reserve raises interest rates, it could rapidly put a damper on the fundraising that’s so critical to the AI build-out, even as investors are already questioning AI’s economics.

OpenAI, Anthropic Must Raise Money to Survive

The necessity of even the largest companies to raise money shows how much the AI build-out relies on affordable credit. This is something that will be felt the most by financially weaker players, names such as OpenAI and Anthropic, that need financing to survive. These companies are burning cash furiously – OpenAI recorded an operating loss of $20.9 billion in 2025 alone.

These AI modelers are effectively no longer being funded by the usual Silicon Valley venture capital investors. The same companies above that are funding them must raise money and so are subject to the same dynamics in the credit market as everyone else.

For example, in its March funding round, OpenAI raised $122 billion, but almost all of it ($110 billion) came from three investors:

• Amazon: $50 billion

• Nvidia (NVDA): $30 billion

• SoftBank (SFTBY): $30 billion

If the Fed raises interest rates, it will reduce the capacity of large investors such as these and the hyperscalers to raise incremental capital, hurting their ability to fund OpenAI and Anthropic.

Perpetual money burners such as OpenAI MUST raise money to survive, since it cannot make money on its own. Given its estimated $1.4 trillion in spending commitments – money that’s spent all over the AI industry – OpenAI is essential to propping up the AI sector.

If companies find it increasingly less affordable to raise money – perhaps due to the Fed raising short-term rates – it has the potential to spiral out of control, popping the AI bubble. The road to bursting the AI bubble may run right through the Federal Reserve.

Regards,

James Royal, PhD

Editor’s Note: Whitney Tilson — the hedge fund manager CNBC called “The Prophet” — says America has reached its “Ripping Point.” The old financial order is being torn apart, and he believes most investors have no idea what’s coming in the next six months. He’s named the stocks he thinks will be destroyed in the chaos — and the ones he believes will soar. Watch his free presentation while it’s still available. 

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