Nvidia pivots to capital as investors warn AI boom hides $3 trillion in off-balance-sheet risks

Nvidia's AI moat is shifting from chips to capital

* In the past week, Nvidia has announced a pact with Wall Street firms to pursue $500 billion worth of financing for chips, and has agreed to support OpenAI in Ohio to the tune of up to $105 billion. * While the chipmaker maintains its dominance in the market for AI processors, it's increasingly showing its willingness to take advantage of another great asset: capital. * Many frontier labs "are growing faster than their balance sheets and long-term credit profiles can support," Nvidia CEO Jensen Huang wrote. In this article * NVDA Follow your favorite stocksCREATE FREE ACCOUNT Jensen Huang, chief executive officer of Nvidia Corp., speaks to members of the media following the company's "Japan AI Ecosystem" reception in Tokyo, Japan, on Thursday, July 16, 2026. Kiyoshi Ota | Bloomberg | Getty Images Nvidia's massive head start in artificial intelligence turned the chipmaker into the world's most valuable company. Now, almost four years into the generative AI boom, competitors like Advanced Micro Devices and Google have chipped away at Nvidia's technology lead, pushing the company to take advantage of its other great asset: capital. Following last week's pact with Wall Street firms to pursue $500 billion worth of financing for Nvidia's graphics processing units, Nvidia said on Monday that it's providing up to $105 billion for a giant OpenAI data center in Ohio, offering a backstop of sorts should the ChatGPT creator see its fortunes turn. For Nvidia, the strategy involves fueling the AI boom by whatever means necessary, recognizing that demand for critical infrastructure is seemingly insatiable but that a handful of companies -- the hyperscalers -- account for an outsized amount of purchases. With its quarterly free cash flow up 18-fold over the past three years to $48.5 billion in the latest period, Nvidia is using the strength of its balance sheet and credit rating to ensure there's no dramatic slowdown following 12 straight quarters of revenue growth above 55%. Read more CNBC tech news "They remain dominant, but they're very paranoid about making sure they don't lose ground," said Ram Bala, associate professor of AI and analytics at Santa Clara University's Leavey School of Business. Nvidia declined to comment. In a note to clients on Monday, analysts at Cantor brushed off concerns that Nvidia is effectively buying revenue through its financial maneuvering. They reiterated their buy rating and said the latest agreement is a "clear signal that the current AI investment cycle will be elongated and durable." "We view this less as circular and more facilitating the coming AI buildout while at the same time creating additional competitive moats that will continue to enable NVDA to remain THE AI leader," the analysts wrote. Nvidia is swimming in money. Its cash generation is so great that the company said in May that it was increasing its quarterly dividend to 25 cents a share from a penny, and announced a new $80 billion stock buyback plan. The company pledged "to return roughly 50% of free cash flow to shareholders this year." VIDEO10:4610:46 Monday, August 17, 2026: Cramer says investors should go for this stock if they want exposure to memory One way the company has been putting its cash pile to work is through equity investments in companies across the AI ecosystem, including some businesses -- like model developers and neoclouds -- that spend heavily on Nvidia's chips and systems. Nvidia held $30.2 billion in marketable equity securities as of the most recent quarter, up from $12.9 billion a year earlier. In February, Nvidia invested $30 billion in OpenAI, which relies on training capacity from Vera Rubin, the chip giant's most advanced system. Monday's agreement included a $1.5 billion investment in SB Energy, a SoftBank affiliate that's building and managing the data center at the PORTS-Pike Technology Campus in Pike County, Ohio, through a 20-year lease to OpenAI. In addition to the SB Energy investment, Nvidia said it's putting its financial support behind about 4 gigawatts of development at the Ohio site for portions of lease and power and "a specified residual-value commitment," as data centers open between 2028 and 2030. Expanding access Nvidia CEO Jensen Huang acknowledged the significance of the company's financial prowess in a post on X about the agreement. "Frontier AI labs have extraordinary demand for training and inference compute, but many are growing faster than their balance sheets and long-term credit profiles can support," Huang wrote. "They may have strong customer demand and rapidly growing revenue yet still lack the decades-long infrastructure contracts and investment-grade financing capacity needed to secure the AI factory infrastructure independently." A week prior, Huang was on set at CNBC surrounded by six of Wall Street's leading financiers to announce the arrival of Nvidia graphics processing units as a new asset class. In signing a memorandum of understanding with firms including Goldman Sachs, Apollo Global Management, Blackstone and BlackRock, Huang indicated that the next phase of the AI buildout will be funded in part by third-party backers, who can start investing in GPUs the way they do real estate. "These are revenue-generating assets now," Huang told CNBC. "They're productive, they're long-lived, they're fungible, they're flexible." VIDEO34:5834:58 Watch CNBC's full panel with Nvidia's Jensen Huang, BlackRock's Larry Fink, Goldman Sachs' David Solomon, and other top Wall Street executives Key to obtaining financing for prospective borrowers will be a dedication to Huang's systems, with Nvidia obtaining the option of backstopping 25% of every loan. It's another way to get more of Nvidia's technology into the market, as competition builds from Google and AMD, as well as from specialized chipmakers like Cerebras. In the second quarter, Google began recognizing revenue from TPU system sales, contributing to the cloud unit's 82% growth. AMD, meanwhile, reported more than 100% growth in its data center business, and the company expects its first rack-scale system, called Helios, to ship later this year. Paul Meeks, head of technology research at Freedom Capital Markets, said the stepped-up competition eats into Nvidia's ability to yield "outrageous margins," and incentives the company to diversify its strategy. "Part of their thinking is let's broaden our reach," Meeks said. "We just can't ride this one horse, which is GPUs." AI bulls say that Nvidia is just responding to demand, and point out that the shortage in the market today is on the capacity side. There are plenty of numbers to back that up, as Anthropic told investors over the weekend that its annualized revenue run rate hit $65 billion in July, up sevenfold from a year earlier. OpenAI's run rate recently reached $40 billion. Matthew Vegari, head of research at Clearwater Analytics, said in an email that, based on the market dynamics, the "narrative around the AI trade's circuitous, 'house of cards' structure strikes us as somewhat misguided." "We might one day be at overcapacity," he wrote. "But that day isn't today." -- CNBC's Samantha Subin and Jonathan Vanian contributed to this report watch now VIDEO5:2205:22 AI chips aren't a new asset class, they're the entire market Squawk Box Asia Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

'Big Short' investor Steve Eisman sees an Achilles heel in the AI boom

'Big Short' trader Steve Eisman: Future of hyperscalers hinge on bet OpenAI and Anthropic will succeed Fast Money Steve Eisman is warning that the artificial intelligence boom has become increasingly dependent on the fortunes of just two companies: OpenAI and Anthropic. The investor, best known for his bet against the housing market ahead of the global financial crisis, said the two AI startups account for roughly 70% of AI-related revenue at Microsoft, Amazon, Alphabet's Google and Oracle -- and as much as 25% to 35% of their cloud revenue. "The futures of these massive companies, in a sense, are a bet that OpenAI, Anthropic are going to succeed," Eisman said late Tuesday on CNBC's "Fast Money." "The Real Eisman Playbook" podcast host and former Neuberger Berman senior portfolio manager believes that the biggest revenue threat could come from China, as Chinese open-source AI models are significantly cheaper and appear to be gaining market share. "The Achilles heel of this whole story ... is if something bad happens to Anthropic and OpenAI ... the Chinese open end models, open weight models are much cheaper. And if they start really taking a lot of market share and it sounds like, from what I'm hearing, that they're starting to, you could have a big price war. And then we have a problem," he said Eisman's warning adds another prominent voice to a growing debate over whether the extraordinary spending behind the AI boom can generate sufficient returns. Michael Burry, another investor whose wager against the housing bubble was chronicled in The Big Short, has taken an even more bearish view. Burry has questioned whether much of current and future AI demand ultimately comes from end customers, arguing instead that a significant portion is financed through what he has described as circular arrangements. Burry is putting his money where his mouth is, placing bearish bets against some of the biggest beneficiaries of the AI boom, including Nvidia, while also disclosing bearish positions tied to the broader semiconductor sector. Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

Michael Burry revives AI warnings, Big Short investor says 'You could have heard it first'

Michael Burry revived his AI bubble warnings after a report highlighted roughly $3 trillion in disclosed commitments by technology giants for AI infrastructure. He argued these off-balance-sheet obligations could signal excessive investment, echoing concerns over stretched valuations and market exuberance. Veteran American investor Michael Burry revived his AI warnings, sharing an analysis that found nine technology giants had amassed around $3 trillion in off-balance-sheet commitments related to the nascent technology. The former hedge fund manager took to X to share a report by The Wall Street Journal that said that Google-parent Alphabet, Amazon, Facebook-parent Meta and Microsoft together reportedly disclosed $3 trillion in commitments largely for AI infrastructure, but these obligations are not yet recognized as liabilities on the face of corporate balance sheets US MarketsPowered By As on 15 Aug 2026, 01:30 AM IST S&P 500 Top Gainers Copart31.61(7.55%) Advanced Micro Devices514.39(6.50%) Fox61.41(5.70%) Seagate Technology Hldgs973.44(5.65%) Gainers" S&P 500 Top Losers Coterra Energy32.56(-8.62%) Broadcom392.99(-5.94%) GoDaddy94.91(-5.56%) Applied Materials507.18(-5.12%) Losers" "Well, you could have heard it first, months ago, 2025 even," Burry, best known for correctly predicting the 2008 housing crisis, wrote on X. He has been vocal against the excessive frenzy around artificial intelligence for several months, even when global markets sharply rallied earlier this year amid the optimism. Also read | Without Warren Buffett, Berkshire Hathaway is no longer an attractive investment: 'Big Short' fame Michael Burry Also read | Without Warren Buffett, Berkshire Hathaway is no longer an attractive investment: 'Big Short' fame Michael Burry Michael Burry sees market near major top Recently, Burry said he continues to believe that the market is close to a major top, warning of a similar crash to that of 1987 when Dow Jones recorded a historic 23% plunge which led to the introduction of regulatory circuit breakers. However, the market investor noted that the S&P 500 making new highs likely will bring new money into the market. Burry continues to hold his short positions in the iShares Semiconductor ETF, Micron, Nvidia, Caterpillar, Palantir, Tesla and Applied Materials. "Again, shorting is not for everyone," Burry wrote. "I must short. Most should not." Earlier this year, Burry wrote on a Substack post that he sees many indicators, both technical and fundamental, lining up for the same conclusion as the Dotcom crash. "1999 went where no market had gone before, and I would say so can this one...It is already there on a number of indicators," he said, arguing that massive venture capital flows, rising AI debt issuance, and extreme market optimism are creating conditions where valuations may detach from economic reality. Burry's popular bet against the housing market was depicted in the 2015 movie titled 'The Big Short', which starred Christian Bale, Ryan Gosling, Steve Carell and others. Also read | Elon Musk vs Michael Burry: World's richest man says AI internet traffic will outpace humans, market expert asks who is paying (With inputs from agencies) (Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)

J.P. Morgan's Bill Eigen Says AI Boom is a Real Estate Cycle, Not Tech - NVIDIA (NASDAQ:NVDA)

JPMorgan's Bill Eigen Warns the AI Boom Is Starting to Resemble the 2008 Housing Crash: 'What I'm Terrified of Is...' J.P. Morgan Asset Management's Bill Eigen is growing increasingly cautious about the financial architecture underpinning the artificial intelligence boom, warning that investors should watch the pace of AI growth, spending and valuations rather than simply their headline levels. Watching The 'Second Derivative,' Not Just Growth Speaking on CNBC, Eigen said most investors are focused on AI revenue levels and growth rates, but he's more concerned with the rate of acceleration of that growth, what he called the "second derivative." "What I'm terrified of is when that starts to slow," Eigen said, adding that capital expenditure and private market valuations of AI labs already appear to be decelerating. Hyperscaler capex is projected to reach roughly 3.1% of U.S. GDP by 2027, according to Apollo Global Management chief economist Torsten Slok, more than twice the roughly 1.2% peak reached during the telecom boom. Markets Home Depot, Toll Brothers And 3 Stocks To Watch Heading Into Tuesday Some stocks that may gain investor attention today are Home Depot Inc (HD), Flexsteel Industries Inc (FLXS), Amer Sports Inc (AS), Duos Technologies Group Inc (DUOT), and Toll Brothers Inc (TOL). Home Depot and Duos Technologies reported better-than-expected earnings, while analysts expect Toll Brothers to post strong earnings. 1 min read Read this article A 'Duration Mismatch' Worries Him On Data Center Debt Eigen said he's wary of buying long-dated debt tied to data centers, given the mismatch between 30-year bond terms and the three-to-six-year depreciation cycle of the chips inside them. Much of the future financial obligation sits outside reported debt, with Goldman Sachs estimating roughly $1.5 trillion in aggregate hyperscaler lease commitments, including Meta Platform Inc.'s (NASDAQ:META) $27 billion Hyperion joint venture with Blue Owl, structured to keep debt off Meta's own books. Eigen said credit spreads across public markets remain near historic tights, but pointed to credit default swaps on AI-related companies, including Nvidia Corp. (NASDAQ:NVDA), which have begun to widen, a warning sign he said isn't yet showing up in headline valuations. According to a Wall Street Journal report, Alphabet Inc. (NASDAQ:GOOGL) (NASDAQ:GOOG), Amazon.com, Inc. (NASDAQ:AMZN), Meta, and Microsoft Corp. (NASDAQ:MSFT) have racked up $3 trillion in commitments off their balance sheets. Betting Against the Trade, But He's Not Buying Either Eigen said he isn't shorting AI-related assets, since it's impossible to know when a cycle like this will end, but he's also not buying at current prices. He pointed to roughly $2 trillion in remaining performance obligations reported by major hyperscalers, reflecting contracted future revenue from customers. "How's that going to get paid?" Eigen added. Benzinga edge rankings indicate Nvidia's stock has a Momentum score in the 69th percentile and a Growth score in the 99th percentile. Media Anthropic Hits $65 Billion Annualized Revenue Run Rate as Claude Drives Explosive Growth Ahead of Potential IPO: Report Anthropic's revenue run rate surged to $65 billion as strong enterprise demand for Claude fuels rapid growth and IPO ambitions. 2 min read Read this article Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Why Elon Musk Thinks AI Is Getting Cheaper, Not Just Smarter - NVIDIA (NASDAQ:NVDA)

The AI industry's biggest competition may no longer be about building the smartest model. Elon Musk's latest comments suggest the next phase of the race is about delivering more intelligence using less energy -- a shift that could ultimately make AI cheaper to run and more practical to deploy at scale. Replying to a post by Replit CEO Amjad Masad, Musk wrote that "Intelligence/Joule will keep improving," echoing a growing view that AI progress should be measured not only by how capable models become, but also by how efficiently they deliver those capabilities. The post referenced new research showing a sharp improvement in "intelligence per joule" over the past 16 months, driven by advances in both AI models and hardware. AI Is Entering an Efficiency Race For much of the past three years, the AI conversation has centered on larger models, more parameters and record-breaking benchmarks. But as companies move from training models to running them in real-world applications, the economics of inference are becoming increasingly important. A recent research paper by Avanika Narayan introduces "intelligence per watt" as a way to measure how much useful AI performance can be delivered for a given amount of energy. The researchers found that local AI systems improved this metric more than fivefold between 2023 and 2025, with gains coming from both better model architectures and more efficient hardware. They also reported an 18-fold improvement in "intelligence per joule" over a 16-month period when combining advances in models and accelerators [Figure 3 of page 8 of the research paper]. The takeaway is straightforward: AI isn't just becoming smarter -- it is becoming dramatically more efficient. Why Nvidia and AI Infrastructure Could Benefit The idea isn't entirely new. In a recent exclusive interview with Benzinga, DigitalOcean CEO Paddy Srinivasan said AI companies are increasingly optimizing for "intelligence per dollar" by routing workloads across different models instead of relying exclusively on expensive frontier systems. Tech EXCLUSIVE: Nvidia Is Helping This AI Company Get 'Better Intelligence Per Dollar' This AI company is using Nvidia technology to make its healthcare AI more efficient. DigitalOcean CEO sees better "intelligence per dollar". 3 min read Read this article Musk's comments point to the same broader trend from a different angle. If companies can generate more useful AI with fewer watts of power, the cost of running AI applications can fall even as model capabilities improve. That has implications across the AI ecosystem. Companies such as Nvidia Corp (NASDAQ:NVDA) have increasingly emphasized performance improvements that allow customers to complete more AI work with the same infrastructure, while cloud providers are looking for ways to lower inference costs as AI adoption expands. At the same time, growing demand for electricity has made power availability a key constraint for AI data centers, making efficiency gains even more valuable. What Investors Should Watch Next Musk's post wasn't simply an observation about AI hardware. It reflects a broader shift in how the industry may define progress. The next winners may not be the companies with the biggest models alone, but those that can deliver the most useful intelligence at the lowest energy and computing cost. For investors, that means AI efficiency -- not just AI capability -- could become one of the most important metrics to watch over the next phase of the industry's growth. Markets Anthropic Paying 33% Above Market for AI Capacity, JPMorgan Says JPMorgan says Anthropic is paying about 33% above industry rates for AI data center capacity at Riot Platforms, highlighting tight infrastructure supply. 2 min read Read this article Photo Courtesy: Frederic Legrand - COMEO on Shutterstock.com Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

'Big Short' investor warns AI boom has quiet weak spot

The artificial-intelligence boom is sold to investors as one of the broadest technology shifts in decades. And a shockingly substantial part of the answer may lie with just two corporations, says Steve Eisman. The investor best known for betting against the U.S. housing market before the financial crisis told CNBC that OpenAI and Anthropic account for roughly 70% of AI-related revenue at Microsoft (MSFT), Amazon (AMZN), Alphabet (GOOGL) and Oracle (ORCL). He also estimated that the two startups may represent roughly 25% to 35% of cloud revenue at those companies. Eisman views that concentration as the "Achilles' heel" of the AI trade. The problem is not that demand for artificial intelligence would evaporate quickly. However, the economics could change quickly if cheaper rivals gain the upper hand and launch a price war. Eisman notably mentioned Chinese open-source and open-weight AI models, which he argued are far cheaper and starting to gain share. That leaves investors with a bigger question regarding AI growth. If hyperscalers are spending hundreds of billions of dollars to serve AI demand, how much of the return on that investment is dependent on a small number of customers continuing to expand at extraordinary rates? "The futures of these massive companies, in a sense, are a bet that OpenAI, Anthropic are going to succeed," Eisman said on CNBC. Eisman's concern is about concentration, not AI demand itself Microsoft, Amazon, Google, and Oracle have all spent extensively to expand their AI infrastructure. Cloud capacity is one of the main beneficiaries of the development in AI, as startups and corporations rent access to pricey computer resources instead of building their own infrastructure from scratch. That is a powerful growth engine for hyperscalers. It also leads to customer concentration. If Eisman's estimate is right, then both OpenAI and Anthropic make up an exceptionally substantial share of AI-related revenue across several of the world's major cloud firms. That's important because investors frequently think of cloud demand as spread over thousands of clients. AI demand may be significantly more focused. A few frontier-model developers use vast quantities of processing power, so their success can have an outsized impact on suppliers. But for the hyperscalers, that can work well while those companies are developing swiftly. The risk emerges when one or two clients are responsible for too much of the incremental revenue. That concentration might increase both upside and downside. As OpenAI and Anthropic continue to grow, hyperscalers gain from more cloud use, larger commitments, and better utilization of data-center investments. If demand softens, or consumers switch to cheaper versions, or become more price sensitive, the economics could change far quicker than investors expect. HECTOR RETAMAL / Getty Images Chinese AI models could force the price war Eisman fears Eisman's second issue is competition. Chinese open-source and open-weight solutions are cheaper and seem to be taking market share. That matters because the AI industry has based its business model on the assumption that leading frontier models can charge enough to cover huge infrastructure costs. A pricing war would test that assumption. If cheaper models become "good enough" for more business use cases, clients might not require the most expensive frontier models for all tasks. That might put pressure on the pricing of AI services and, eventually, on what model developers are ready to pay cloud providers for computation, he said. For hyperscalers, the risk might not be an implosion in demand. It could be an aggravation of the economics of that demand. That matters because AI use can continue to grow with shrinking margins and returns on infrastructure spending. Eisman's warning goes right to one of Wall Street's major questions: whether the massive capital expenditures driving AI will provide adequate return on invested capital. The bull argument is that expenditure will ultimately be proven out by increased usage, cloud expansion, and enterprise acceptance. The bear case: decreased pricing, competition, and concentrated demand make for significantly less attractive returns. Michael Burry is making an even darker AI bet Eisman isn't the only investor tied to "The Big Short" having concerns. Michael Burry is even more negative and has questioned whether a large part of the AI demand is coming from real end consumers or from financing arrangements that he has termed "circular." Burry has also taken short positions on some of the biggest winners of the AI boom, such as Nvidia (NVDA). The two investors aren't quite making the same point. Eisman's problem is more about concentration and price risk. More structural is Burry's fear, however, whether some of the demand underpinning the AI buildout will prove as permanent as investors anticipate. But together, they hint at the same larger problem. The AI trade is so vital to big tech that if the economics underpinning it falters, it might have implications far beyond a handful of startups. That could simultaneously hurt cloud growth, semiconductor demand, data-center spending and stock market valuations. Hyperscalers now have more riding on AI than investors may realize AI is becoming crucial to the growth story for Microsoft, Amazon, Google, and Oracle. That has helped fund huge infrastructure expenses and fueled investor optimism about cloud development. But concentration risk modifies how investors need to think about those metrics. If most AI revenue at many hyperscalers comes from OpenAI and Anthropic, revenue growth may not be as diversified as it looks. That's not to say the AI growth is a bubble. This could suggest the industry has a smaller base than investors believe. What investors should watch next * OpenAI and Anthropic growth: If both continue expanding rapidly, hyperscaler AI revenue should remain supported. * Chinese open-weight models: Cheaper alternatives could pressure model pricing. * Cloud concentration: Investors should watch whether hyperscalers diversify AI revenue beyond a small group of large customers. * AI pricing: A broad price war would challenge return-on-investment assumptions. * Capital spending: Hyperscalers are still committing enormous sums to AI infrastructure. * Nvidia demand: Any slowdown in infrastructure investment would eventually matter to chip suppliers as well. The key element of Eisman's warning is not that artificial intelligence will fail. It is that success may be more concentrated than it seems. Wall Street has viewed the AI boom as a huge ecosystem of semiconductors, cloud providers, data centers, software businesses, and enterprise customers. Eisman's argument is that much of the current revenue engine may still run through only a few companies at the center of that ecosystem. If OpenAI and Anthropic continue to win, that concentration might not matter. If cheaper models start taking share and forcing prices lower, it could matter rapidly. That's why the next phase of the AI trade may be less about whether demand exists and more about who controls it and how much they are ready to pay. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 14, 2026 at 7:03 PM.

Nvidia Could Become The 'Federal Reserve Of AI' - NVIDIA (NASDAQ:NVDA)

Nvidia Could Become the 'Federal Reserve Of AI,' Gavin Baker Says: Will 'Dark GPUs' Become Its First Test? Nvidia (NASDAQ:NVDA) is building what could become the "Federal Reserve of AI," Atreides Management CIO Gavin Baker said on Friday's All-In Podcast. The investor says CEO Jensen Huang is transforming Nvidia's chips into a financeable asset class, opening the door for Wall Street to finance a much larger AI buildout. But co-host David Sacks warned there is one way the strategy could end badly for everyone: "dark GPUs." Nvidia last week unveiled a plan with Wall Street firms to mobilize more than $500 billion for AI infrastructure. On Monday, Nvidia backed SB Energy's Ohio data-center buildout and said it will invest $1.5 billion in the developer. Baker Says Nvidia Is Becoming AI's 'Federal Reserve' Baker said financing has become a bottleneck for AI growth, with the market "constrained by the ability to finance this buildout." Latest Private Market Opportunities Join 400,000+ Investors Nvidia is trying to remove that constraint by making GPUs easier for Wall Street to lend against. The chips generate rental income, can remain productive for years, and Nvidia may provide residual-value support of up to 25% on individual deals. That makes Nvidia a "matchmaker" between compute buyers and lenders, Baker said, potentially turning it into the "central bank of AI, the Federal Reserve of AI." Sacks Warns of 'Dark GPUs' Making compute easier to finance raises an obvious question: what if too much gets financed? Sacks, framing it as the downside scenario rather than a prediction, said the biggest risk is a "glut of compute" echoing the dot-com era, when unused fiber-optic lines became known as dark fiber. "If you had dark GPUs, that'd be a disaster for everyone," he said. Easier financing could fuel a huge buildout, leaving supply ahead of demand and pushing down rental prices and GPU residual values. Sacks added that permitting fights, power constraints and political resistance to data centers may act as a natural brake against overbuilding. Prediction Markets Put a Price on Nvidia Compute Kalshi traders aren't pricing a compute glut: they give a 61% chance H100 SXM rental prices finish the year above $3.23 an hour, versus $2.79 currently. A sustained decline in rental prices would be a warning sign of the oversupply Sacks describes. Baker sees the financing push as removing the biggest constraint on the AI buildout. Sacks' warning is that removing it too successfully could create a new problem: too much compute. Image: Shutterstock Kalshi and Benzinga have an existing data collaboration agreement. Markets SpaceX Launches 2 Rockets Just 38 Minutes Apart, Setting New Record for Musk's Launch Machine SpaceX launches 2 rockets just 38 minutes apart, setting what Space.com called a new record for the shortest time between orbital flights. 2 min read Read this article Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

"Big Short" Steve Eisman says China's AI models are "Achilles' heel" of AI trade By Investing.com

Investing.com -- Steve Eisman said the artificial intelligence boom depends largely on the success of just two companies: OpenAI and Anthropic. The investor, known for betting against the housing market before the global financial crisis, said Tuesday on CNBC's "Fast Money" that the two AI startups represent about 70% of AI-related revenue at Microsoft, Amazon, Alphabet's Google and Oracle. He added they account for 25% to 35% of cloud revenue at these companies. "The futures of these massive companies, in a sense, are a bet that OpenAI, Anthropic are going to succeed," Eisman said. Get instant alerts on market-moving headlines with InvestingPro -- now 55% off. The podcast host and former Neuberger Berman senior portfolio manager said the biggest revenue threat could come from China, as Chinese open-source AI models cost less and appear to be gaining market share. "The Achilles' heel of this whole story ... is if something bad happens to Anthropic and OpenAI ... the Chinese open-end models, open-weight models are much cheaper. And if they start really taking a lot of market share and it sounds like, from what I'm hearing, that they're starting to, you could have a big price war. And then we have a problem," he said. Michael Burry, another investor featured in "The Big Short," has taken a more bearish stance. Burry has questioned whether current and future AI demand comes from end customers, suggesting a portion is financed through circular arrangements. Burry has placed bearish bets against Nvidia and disclosed bearish positions tied to the broader semiconductor sector.

Michael Burry Takes Victory Lap as Big Tech's $3 Trillion AI Spending Tab Comes Into Focus - Alphabet (NA

Famed "Big Short" investor Michael Burry is taking a public victory lap over a new Wall Street Journal report revealing that technology giants have accumulated $3 trillion in future artificial intelligence spending that remains hidden off their official balance sheets. 'You Could Have Heard It First' Taking to X on Aug. 17, Burry shared a graphic from the WSJ article titled "Why Big Tech's AI Spending Is $3 Trillion Higher Than It Seems." Seizing the moment to highlight his early foresight on these massive capital expenditures, Burry posted, "Well, you could have heard it first, months ago, 2025 even." Burry did not just stop at claiming vindication; he also issued a cryptic forward-looking warning about future market dynamics. He compared the financial media's delayed realization of the true AI spending tab to current market risks, stating, "Like compression's threat now, to be covered in 2027 by @WSJ and @CNBC." The Hidden AI Iceberg The WSJ analysis paints a picture of financial obligations that go well beyond public financial statements. While giants like Alphabet Inc. (NASDAQ:GOOG) (NASDAQ:GOOGL), Amazon.com Inc. (NASDAQ:AMZN), Meta Platforms Inc. (NASDAQ:META), and Microsoft Corp. (NASDAQ:MSFT) currently report a combined $248 billion in lease liabilities and $356 billion in long-term debt on their balance sheets, the vast bulk of their financial commitments remain beneath the surface. Tech Justin Wolfers Says AI Won't Kill Your Job -- but It Will Change What It's Worth: 'Lab-Grown Diamonds Didn't Abolish Diamonds Economist Justin Wolfers said AI's shock to labor markets may resemble lab-grown diamonds, not eliminating jobs but reducing their worth. 3 min read Read this article According to the WSJ data as shown in its graphic, the companies had about $1.2 trillion in obligations from leases that haven't started and another $1.9 trillion in purchase commitments. Alphabet Leads the Spending Surge A deeper breakdown of these off-balance-sheet purchase commitments reveals that Google's parent company, Alphabet, is taking the most aggressive financial posture in the AI arms race. Latest Private Market Opportunities Join 400,000+ Investors Alphabet alone accounts for an enormous $811.0 billion in hidden purchase commitments. By comparison, Meta holds $349.3 billion in similar commitments, while Microsoft reports $228.6 billion and Amazon holds $130.1 billion. How Have These Stocks Performed? Markets Michael Burry Calls Nvidia's $500 Billion AI Financing Push a 'Wall Street Stunt': 'Meet the New Boss...' Michael Burry slams Nvidia's $500B AI deal as a 'Wall Street stunt,' warning of hidden risks in private credit schemes. 3 min read Read this article Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.