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An inside look at his analysis showing AI is a bubble

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What Michael Burry sees in AI that has him betting big against the boom

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 unprecedented GPU orders from cloud providers. But Scion questions whether those customers will ever generate economic returns on that investment.

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Nvidia one year

A key element here is depreciation policy. Tech giants have lengthened server lifespans on the books to six years. Yet Nvidia’s product cycles run every year now, making older chips functionally obsolete and less energy-efficient, long before they’ve been written down, Scion claims.

Nvidia has pushed back at this claim, saying its hardware remains productive far longer than critics say, thanks to efficiencies driven by the company’s CUDA software system.

Still, Burry and other critics are seizing on a contradiction. Nvidia says the newest chips are superior in performance, efficiency and capability, at the same time as it promises that older chips remain economically viable. One of those defenses, they say, has to give.

Burry has launched a new Substack newsletter to lay out his bearish thesis on AI. Whether generative AI ultimately proves to be a bubble remains to be seen, but for now, Burry is again positioning himself on the cautious side of a fast-moving story.

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Private Credit Expansion and Regulatory Oversight in 2026 Capital Markets

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The global private credit market has solidified its role as a fundamental pillar of enterprise finance, expanding rapidly across middle-market lending, asset-backed finance, and infrastructure financing. As non-bank financial institutions capture a larger share of corporate debt origination, global regulatory bodies are increasing oversight to evaluate market transparency and systemic risk interconnections.

Growth Drivers in Direct Lending
Direct lending platforms have continued to attract substantial institutional allocations from pension funds, sovereign wealth entities, and insurance companies seeking attractive risk-adjusted yields. Private debt funds offer corporate borrowers customized financing structures, faster execution timelines, and confidentiality compared to syndicated loan markets.

In 2026, private credit managers are increasingly financing larger corporate transactions, providing multi-billion-dollar credit facilities for buyout deals and corporate restructurings. The flexibility of private debt contracts—featuring unitranche pricing and tailored covenant packages—has made direct lending the preferred capital source for middle-market enterprise sponsors.

Regulatory Scrutiny and Systemic Risk Assessment
The rapid growth of non-bank intermediation has drawn heightened scrutiny from financial regulators in North America and Europe. Because private debt agreements are negotiated privately without public exchange disclosures, central banks are evaluating potential vulnerabilities related to asset valuation consistency and fund liquidity profiles.

Regulatory agencies are introducing guidelines aimed at improving reporting standards for private investment vehicles managing institutional assets. Key focus areas include monitoring leverage ratios within private credit funds and evaluating indirect credit exposures between commercial banking institutions and private debt funds.

Navigating Elevated Refinancing Costs
With benchmark interest rates remaining elevated, private debt borrowers face higher debt service obligations on floating-rate credit facilities. Financial advisory firms report an increase in proactive liability management strategies, including payment-in-kind (PIK) interest options, equity infusions from sponsors, and covenant modifications.

Private credit managers with deep operational capabilities are actively working alongside portfolio companies to optimize working capital and maintain cash flow coverage ratios during periods of higher borrowing costs.

Key Financial Takeaways
1. Mainstream Asset Class: Private credit has expanded beyond niche alternative asset status into a core corporate finance solution.
2. Enhanced Transparency Standards: Regulatory frameworks are evolving toward greater disclosure requirements for private debt managers.
3. Proactive Risk Management: Lenders and sponsors must prioritize debt sustainability and active portfolio monitoring amid high benchmark rates.

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Venture Capital and Startup Valuations in 2026: Focus on Unit Economics and Sustainable Growth

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The global venture capital (VC) ecosystem is operating under a disciplined investment framework in 2026. Following years of valuation adjustments and shifting liquidity environments, venture capital firms and private equity investors are prioritizing proven unit economics, positive cash flow pathways, and capital efficiency over rapid, unconstrained user acquisition.

The Shift Toward Disciplined Startup Valuations
Early-stage and growth-stage startup valuations have stabilized at sustainable historical averages. Venture capital partners are conducting rigorous due diligence processes before deploying capital, scrutinizing gross margins, customer acquisition costs (CAC), net revenue retention (NRR), and lifetime value (LTV) metrics.

While total capital deployed remains robust, seed and Series A funding rounds are taking longer to finalize. Founders are expected to demonstrate clear product-market fit and defensible intellectual property rather than relying on top-line revenue projections unsupported by strong underlying economics.

M&A Activity and Liquidity Solutions
The market for venture-backed exits is seeing renewed momentum through strategic mergers and acquisitions (M&A) and secondary market liquidity facilities. Established corporate enterprises are acquiring high-performing technology startups to integrate proprietary artificial intelligence models and specialized software solutions into their product ecosystems.

Simultaneously, secondary market transactions have become an essential liquidity mechanism for early employees and institutional investors. Specialized secondary funds are purchasing pre-IPO shares at discounted valuations, providing liquidity opportunities while companies remain private for longer durations.

Sector Allocation: Deep Tech, Clean Energy, and Enterprise Automation
Venture capital investment is heavily concentrated in deep technology and capital-intensive engineering sectors. High-growth investment themes include:
– Next-Generation Semiconductors: Hardware startups designing specialized AI processors and energy-efficient microchip architectures.
– Clean Technology: Battery chemistry innovations, carbon capture solutions, and grid-scale energy storage startups.
– Enterprise Process Automation: Software platforms that automate complex workflows in healthcare, financial services, and industrial logistics.

Key Insights for Entrepreneurs and Investors
1. Prioritize Capital Efficiency: Startups focused on achieving operational profitability receive higher valuation premiums from institutional investors.
2. Strategic Exit Planning: Corporate M&A is serving as a primary exit route for venture-backed startups navigating prolonged IPO windows.
3. Focus on High-Moat Technologies: Deep tech and proprietary software architectures are securing the majority of growth-stage capital allocations.

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The Evolution of Digital Payments: Cross-Border Settlement and Central Bank Digital Currencies in 2026

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The infrastructure supporting global commerce is undergoing a major technological upgrade as real-time digital payment rails, cross-border settlement solutions, and Central Bank Digital Currency (CBDC) pilot programs achieve widespread commercial adoption. Financial institutions and fintech developers are reimagining payment processing to eliminate friction, lower transaction fees, and accelerate settlement speed.

Transforming Cross-Border Settlement Infrastructure
For decades, international corporate payments relied on legacy correspondent banking networks characterized by multi-day settlement delays, opaque fee structures, and high foreign exchange markups. In 2026, modern cross-border payment networks are enabling near-instantaneous settlement for international trade transactions.

Financial technology platforms are leveraging distributed ledger technology and real-time gross settlement (RTGS) interconnections to settle transactions in seconds. International trade participants benefit from reduced working capital requirements and minimized foreign exchange volatility risks during cross-border transfers.

Commercial Expansion of Central Bank Digital Currencies
Central banks representing major global economies are advancing CBDC initiatives from research phases into active commercial deployment. Wholesale CBDCs—designed specifically for interbank settlement and financial institution clearing—are demonstrating substantial efficiency gains in domestic and international transactions.

At the retail level, several nations have introduced public digital currency options alongside existing commercial banking networks. These sovereign digital payment channels aim to expand financial inclusion, lower consumer transaction fees, and improve the efficiency of government-to-citizen financial disbursements.

Open Banking and Embedded Finance Ecosystems
Alongside settlement infrastructure upgrades, open banking regulations and embedded finance frameworks are transforming merchant-consumer interactions. Commercial businesses across retail, travel, and business-to-business (B2B) services are integrating seamless payment APIs directly into their customer software interfaces.

Through open banking frameworks, consumers can initiate secure bank-to-bank payments without relying on traditional credit card networks, significantly reducing merchant processing fees. Integrated Buy-Now-Pay-Later (BNPL) options and point-of-sale credit facilities continue to expand, driving higher conversion rates for digital commerce platforms.

Strategic Financial Takeaways
1. Treasury Optimization: Corporate treasurers should leverage instant cross-border payment platforms to minimize liquidity buffers and foreign exchange exposure.
2. CBDC Integration: Financial institutions must prepare internal core banking systems to interface with emerging wholesale CBDC payment rails.
3. Merchant Fee Reduction: Enterprise merchants can lower payment processing overhead by adopting account-to-account (A2A) open banking checkout solutions.

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