The private credit boom is facing a new test after Blue Owl Capital permanently restricted withdrawals from one of its retail-focused debt funds.

Shares in Blue Owl Capital fell nearly 6% on Thursday after the private market and alternative assets manager sold $1.4 billion of loan assets held in three of its private debt funds.

The biggest portion of the sale came from a semi-liquid private credit fund marketed to U.S. retail investors called the Blue Owl Capital Corporation II, which will stop offering quarterly redemption options to investors, reigniting debate over whether stress was beginning to resurface in one of Wall Street’s fastest-growing corners.

“This is a canary in the coal mine,” Dan Rasmussen, founder and adviser at Verdad Capital told CNBC. “The private markets bubble is finally starting to burst.”

The broader concern is that years of ultra-low interest rates and thin yield spreads encouraged lenders to make riskier moves, financing smaller, more leveraged companies at yields that appeared attractive compared with public markets, market watchers said.

“Years of ultra-low rates and ultra-low spreads and very few bankruptcies led investors to go further and further out the risk spectrum in credit,” Rasmussen said. “This is a classic case of ‘fool’s yield,’ high yield that doesn’t translate into high returns because the borrowers were too risky.”

Private credit, which are generally direct loans made by non-bank lenders to companies, have ballooned into a roughly $3 trillion market globally.

Publicly traded business development companies, or BDCs, which are investment vehicles that lend to small and mid-sized private companies and are a major part of the private credit market, are increasingly funded by retail investors rather than institutions, according to Duke University’s Fuqua School of Business. 

The Fuqua research, which was published last September, showed that institutional ownership of BDC shares has steadily declined over time, falling to about 25% on average by 2023.

“This trend indicates that retail investors are playing an increasingly large role in supplying equity capital to publicly traded BDC,” the researchers pointed out.

In 2025, the eight largest members of the S&P BDC Index offered dividend yields which can go up to 16%, with Blue Owl’s at over 11%. For comparison, the S&P Global’s U.S. high yield corporate bond index 1-year, 3-year and 5-year returns stand at around 7.7%, 9% and 4%, respectively.

“The majority of loans in private credit funds that individual investors tend to own, they’re high yield loans. They are, by their nature, somewhat risky,” said Guy LeBas, chief fixed income strategist at Janney…

Amazon shares sunk more than 9% on Friday after the company’s hefty spending forecast surprised investors who were already wary that the artificial intelligence boom is at risk of becoming a bubble.

The e-commerce company on Thursday was the latest tech giant to announce plans for a massive increase in capital expenditures, after Google parent Alphabet, Microsoft and Meta all signaled they expect their spending sprees to continue.

Amazon, Alphabet, Microsoft and Meta reported about $120 billion in capital expenditures in the fourth quarter alone. That figure could exceed more than $660 billion this year, the Financial Times reported, which is higher than the gross domestic product of countries like the United Arab Emirates, Singapore and Israel.

Wall Street has responded differently to the companies’ spending plans, cheering Meta and Alphabet’s forecasts, while punishing Amazon and Microsoft.

Amazon, Microsoft, Nvidia, Meta, Google and Oracle collectively shed more than $1 trillion from their valuations over the past week, according to FactSet data.

Shares of companies developing hardware for the AI build-out will likely face continued volatility as “sentiment contagion takes hold,” Paul Markham, investment director at GAM Investments, told CNBC.

“Questions over the extent of capex as a result of LLM build-outs, the eventual return on that, and the fear of eventual over-expansion of capacity will be persistent,” he added.

While management is confident of long-term returns on investment, the lack of visibility is not sitting well with investors, Mamta Valechha, consumer discretionary analyst at Quilter Cheviot, said Friday morning.

“We have suddenly gone from the fear that you cannot be last, to investors questioning every single angle in this AI race.”

Analysts at D.A. Davidson downgraded Amazon’s stock on Friday to neutral from a buy rating over concerns around its spending plans, risks to its cloud dominance and the potential for AI to erode its retail business.

“With the context of results from Microsoft and Google, we see AWS continuing to lose its lead and now scrambling to catch up through escalating investment,” the analysts wrote in a research note. “We are also increasingly concerned about Amazon retail’s transition to a new chat-driven internet dominated by Gemini and ChatGPT.”

Apple, on the other hand, which has faced pressure from Wall Street over its AI strategy and has previously committed far less on capex than other Big Tech firms, has seen its stock jump 7% since Monday on the back of what CEO Tim Cook described as “staggering” demand for the iPhone.

“The bet is becoming binary,” Michael Field, chief equity strategist at Morningstar,…

A million bubbles were swirling inside each glass of Champagne poured on New Year’s Eve — which seems about like the number of times artificial intelligence bubbles have been mentioned by tech investors, economists and media pundits in recent months.

Bubble fears surrounds stocks within the Magnificent 7 — Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla — as well as Oracle and Softbank and other tech companies’ multi-billion-dollar investments in the unrelenting buildout of humungous data centers to power their AI systems. Data centers are expected to require roughly $7 trillion in capital outlays by 2030, according to a report by McKinsey & Co. The bubble speculations rage almost daily as breaking news and earnings reports send Mag 7 stock prices rising and falling, leading analysts to constantly update their buy, sell or hold recommendations.

That’s essentially the 30,000-foot, macroeconomic view of AI from Wall Street’s bulls and bears. For a zoomed-in, micro look at the volatility surrounding AI, there may be no better example of adjacent players in the space than Bloom Energy.

A one-time privately funded startup darling from Silicon Valley’s initial push into renewable energy which grabbed some marquee customers early on (e.g. Google and Walmart), Bloom was often in the red since its founding in 2001. Following its 2018 IPO at a price of $15 per share, it has been an unremarkable stock, trading near that IPO price as recently as last April. But Bloom has skyrocketed roughly 400% over the past year, ignited by its emergence as a standalone, onsite power supplier for electricity-guzzling AI data centers. It uses stacks of solid oxide fuel cells to provide an immediate, always-on alternative to connecting to public utilities’ strained grids. Bloom is now among the priciest energy stocks, at 125 times forward earnings.

Bloom’s performance chart for 2025 resembles one depicting the elevation trajectory from flat, mile-high Denver west to 12,000-foot-high Rocky Mountain National Park. The stock price had come back down to Earth lately — from a 52-week high of $147.86 in November on the strength of strong third-quarter earnings and a major deal with utility giant American Electric Power. But it continues to fluctuate in reaction to good and bad news regarding its AI customers, with the latest boost coming on Thursday.

Bloom’s stock soared on Thursday and Friday with the news that a Wyoming data center project had won a key approval. The 1.8 GW facility is expected to include 900 MW of Bloom’s fuel cells, representing about $3 billion in revenue for the company in coming years, according to an analysis from Morgan Stanley’s David Arcaro. In a related development, AEP announced a $2.65 billion deal to acquire a substantial portion of Bloom’s fuel cells as part of a deal with an unnamed customer, presumably the same…

Are we in an artificial intelligence bubble?

It’s the debate that dominated the tech industry in 2025, and it’s not going away anytime soon.

Record valuations and deals driven by major investments in artificial intelligence have fueled the AI boom, leaving some to brace for the potential burst.

AI leaders like OpenAI and Nvidia have spun an impressive web of staggering deals with cloud infrastructure companies, while hyperscalers including Amazon, Microsoft and Google continue to spend billions on data center buildouts.

Although companies are racing to supply the rapidly accelerating AI demand, the enormous debt financing these buildouts have sparked worry that the spending spree may prove to be an overreach.

Economic bubbles occur when asset prices in a specific market rapidly rise, often due to speculation or overenthusiasm, followed by a crash when prices suddenly drop.

Bubble talks ignited again at the end of last year after Nvidia CEO Jensen Huang dismissed fears of a possible AI bust during the company’s third-quarter earnings call.

“There’s been a lot of talk about an AI bubble,” he said. “From our vantage point, we see something very different.”

Others have been less confident in the stability of the AI surge, including “The Big Short” investor Michael Burry.

The fund manager, who rose to fame for predicting the 2008 housing crisis, drew parallels between the current spending euphoria and the dot-com mania of the late 1990s in a lengthy Substack essay.

“Sometimes, we see bubbles,” Burry wrote in an October X post. “Sometimes, there is something to do about it. Sometimes, the only winning move is not to play.”

OpenAI CEO Sam Altman made a similar comparison during a dinner with reporters in August.

“Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes,” he said.

A note on methodology:

CNBC compiled responses from 40 tech executives, analysts and other professionals in the space, who shared their thoughts over the past four months about the current AI frenzy.

Although the question of whether or not the market is in a bubble seems binary, many answers have landed across a spectrum of bubble potential — and worry.

To give each response a more rounded perspective, CNBC also weighed the level of concern.

CNBC scored each person’s remarks on a scale from 0 to 10 on two factors: How much they believe that AI is in a bubble (0 being no and 10 being yes) and how concerned they are about it (0 being not concerned at all and 10 being very concerned).

The big AI bubble question has been the tech industry’s buzziest debate all year, and one robot has weighed in with its opinion.

KOID is a short but slender humanoid robot with a black metal body and a bright ring of light for a face. KOID is manufactured by Unitree, one of China’s hottest tech companies, and the Nvidia-powered robot shares a name with an ETF launched in June by KraneShares that focuses on robotics companies.

The walking, talking machine on Tuesday told CNBC that the AI bubble debate is certainly a “hot topic,” but KOID gave a neutral outlook on whether the artificial intelligence boom is actually a looming bubble.

“We might see a lot of excitement around AI right now, but whether it’s a bubble or just a transformative wave, is something only time will tell,” KOID said.

The AI-powered machine added that AI and humanoids are “here to stay” and will continue to evolve.

Weighing in at about 77 pounds, KOID is one of Unitree’s G1 models. Those humanoids have 23 degrees of freedom, or specific points where it can move independently, allowing it to achieve full body maneuvers from dancing to boxing.

KOID is available to purchase on RoboStore, the largest U.S. distributor of Unitree robots, with the models ranging from $8,990 to $128,900.

RoboStore CEO Teddy Haggerty told CNBC’s “Power Lunch” on Tuesday that while KOID can be programmed to do many kinds of tasks, the industry is still in a “prototyping” stage of figuring out where robots fit into everyday living.

“What is it that we really want robots to do?” Haggerty said. “Do we want robots to become our new housekeepers? Do we want them to help manufacturing? Do we want them to replace jobs?”

KOID, however, seems a little more certain of its own future. It said that robots will likely become “even more versatile and integrated” into daily life.

“They’ll help out a variety of fields, from home assistants to industrial tasks, making life a bit easier and more efficient,” the robot said.

The humanoid robotics race has been heating up this past year, with companies including Boston Dynamics and Agility Robotics emerging in the space. Tesla’s Optimus robots have taken center stage, with CEO Elon Musk saying that they are a future key contributor to the company’s valuation.

Yet while Optimus robots have yet to hit the market, Chinese companies have been ramping up production to beat the U.S. to the punch — with Unitree spearheading the pack.

The company outperformed its peers in events like the World Robot Conference and World Humanoid Robot Games. 

Unitree, which is heading for an initial public offering that could value it at up to $7 billion, debuted its latest H2 model earlier this year.

Everything is bigger in Texas. That’s also true for data center demand in the Lone Star State, where project developers are rushing to cash in on the artificial intelligence boom.

Cheap land and cheap energy are combining to attract a flood of data center developers to the state. The potential demand is so vast that it will be impossible to meet by the end of the decade, energy experts say.

Speculative projects are clogging up the pipeline to connect to the electric grid, making it difficult to see how much demand will actually materialize, they say. But investors will be left on the hook if inflated demand forecasts lead to more infrastructure being built than is actually needed.

“It definitely looks, smells, feels — is acting like a bubble,” said Joshua Rhodes, a research scientist at the University of Texas at Austin and a founder of energy consulting firm IdeaSmiths.

“The top line numbers are almost laughable,” Rhodes said.

More than 220 gigawatts of big projects have asked to connect to the Texas electric grid by 2030, according to December data from the Electric Reliability Council of Texas. More than 70% of those projects are data centers, according to ERCOT, which manages the Texas power grid.

That’s more than twice the Lone Star State’s record peak summer demand this year of around 85 gigawatts, and its total available power generation for the season of around 103 gigawatts. Those figures are “crazy big,” said Beth Garza, a former ERCOT watchdog.

“There’s not enough stuff to serve that much load on the equipment side or the consumption side,” said Garza, director of ERCOT’s independent market monitor from 2014 to 2019.

Rhodes agreed. “There’s just no way we can physically put this much steel in the ground to match those numbers. I don’t even know if China could do it that fast,” he said.

‘Not all real’

Data center requests have exploded in Texas since state legislation in 2023 required projects that have not signed electric connection agreements to be considered in power demand forecasts.

The number of big projects requesting an electric connection has nearly quadrupled this year. But more than half of them, representing about 128 gigawatts of increased potential demand, have not submitted studies for ERCOT to review yet. About another 90 gigawatts are either under review or have had planning studies approved.

“We know it’s not all real. The question is how much is real,” said Michael Hogan, a senior advisor at the Regulatory Assistance Project, which advises governments and regulators on energy policy.

The huge numbers in Texas reflect a broader data center bubble in the U.S., said Hogan, who has worked in the electric industry for more than four decades, starting at General Electric in 1980.

“As with everything else in Texas, it’s an outsized example of it,” he said.

The number of projects that have actually connected to the grid or have been approved by ERCOT is much smaller, at only around 7.5 gigawatts. It is still a large…

The fight between Nvidia and one of its loudest naysayers, investor Michael Burry, is escalating.

Following the “Big Short” investor’s series of social media posts arguing that the artificial intelligence investment boom is replaying the dotcom bubble from the 1990s, with Nvidia at the center of it, the chipmaker quietly circulated a private memo to analysts that explicitly name-checked Burry to push back on many of his claims.

The Nvidia seven-page response to “questions and claims we’ve received,” began by citing “Michael Burry on Twitter / X” as its first collection of source documents the company sought to refute.

For his part, Burry answered in a post on Substack that, “Nvidia emailed a memo to Wall Street sell side analysts to push back on my arguments on [stock-based compensation] and Depreciation … I stand by my analysis. I am not claiming Nvidia is Enron. It is clearly Cisco.”

Burry has repeatedly warned that today’s AI infrastructure frenzy mirrors the late-1990s telecom buildout far more than the dot-com wipeouts investors remember. He pointed to massive capex plans, extended depreciation schedules and soaring valuations as evidence that markets are again mistaking a supply boom for durable demand.

The Nvidia memo, first reported by Barron’s, responded to Burry’s criticism of Nvidia’s stock-based compensation dilution and stock buybacks.

“NVIDIA repurchased $91B shares since 2018, not $112.5B; Mr. Burry appears to have incorrectly included RSU taxes,” the memo said, referring to Restricted Stock Units. “Employee equity grants should not be conflated with the performance of the repurchase program. NVIDIA’s employee compensation is consistent with that of peers. Employees benefitting from a rising share price does not indicate the original equity grants were excessive at the time of issuance.”

The memo also disputed Burry’s claims around depreciation life. To Burry’s charge that customers are overstating the useful lives of Nvidia’s graphics processing units in order to justify runaway capital expenditures, Nvidia counters that its customers depreciate GPUs over four to six years based on real-world longevity and utilization patterns.

Nvidia added that older GPUs such as A100s, released in 2020, continue to run at high utilization rates and retain meaningful economic value well beyond the two to three years claimed by critics.

The memo also rejects Burry’s suggestion of “circular financing,” saying Nvidia’s strategic investments represent a small fraction of revenue and that AI startups raise capital predominantly from outside investors.

Today’s Cisco

Burry said he believes Nvidia now occupies the same position that Cisco — the key hardware supplier that powered a massive capital investment cycle — held in 1999-2000.

Just as telecommunication companies spent tens of billions of dollars laying fiber optic cable and buying Cisco gear based on forecasts that “internet traffic doubles every 100 days,” today’s hyperscalers are promising nearly…

Michael Burry — the investor known for predicting the housing meltdown ahead of 2008 — has turned his attention to one of the market’s most beloved themes: artificial intelligence.

Burry recently deregistered his hedge-fund firm, Scion Asset Management, removing it from routine regulatory disclosures. But he remains actively investing, and he is doubling down on what he sees as the next major mispricing in markets.

Central to that view is Phil Clifton, Scion’s former associate portfolio manager, whose research underpins the skepticism. Clifton argues that while generative AI adoption is accelerating, the economics behind the industry’s massive infrastructure buildout have yet to justify the cost.

In his farewell letter to Scion investors in late October, Burry called Clifton “the most prodigious thinker” he’s ever encountered. CNBC obtained several of Clifton’s research notes from earlier this year, written before he launched his own firm, Pomerium Capital, that help outline Scion’s bearish thesis on AI.

The investment world is “expecting far more economic importance out of this technology than is likely to be provided,” Clifton wrote. “Just because a technology is good for society or revolutionizes the world doesn’t mean that it’s a good business proposition.”

Low margins

On the surface, AI usage appears ubiquitous. More than 60% of U.S. adults say they interact with AI at least several times a week, according to Pew Research Center. Yet Clifton said the economics on the demand side are “surprisingly small.”

OpenAI — market leader and cultural phenomenon — is set to surpass $20 billion in annualized revenue this year, but that figure is tiny compared with the size of the AI build-out. Hyperscalers have quadrupled their capex spend in recent years to almost $400 billion annually, with expectations of $3 trillion over the next five years, according to Man Group.

“We assume other generative AI services in aggregate are insufficient to justify the sums being spent on infrastructure,” Clifton wrote.

History’s warnings

Scion sees a clear historical parallel with the early-2000s telecom boom, when heavy investment in fiber-optic networks far outpaced actual usage. U.S. capacity utilization fell to about 5%, and wholesale telecom pricing collapsed roughly 70% in a single year, Scion noted.

Clifton argues the cloud giants are now in a comparable race, expanding AI infrastructure on the assumption that future demand will catch up eventually. But if mass AI adoption takes longer than expected, the economics on these massive data center deals could become untenable.

Some Big Tech companies are starting to wobble on commitments already, he noted. Microsoft has canceled data center projects set to use 2 gigawatts of electricity in the U.S. and Europe, citing an oversupply. Alibaba’s chairman has warned a bubble is forming in AI infrastructure.

The Nvidia Exposure

No company has benefited more from AI spending than Nvidia. The stock has surged alongside…