Michael Burry's next 'Big Short'

Key Concepts

• Shorting/Betting Against: An investment strategy where an investor profits if the price of a stock or other security declines.
• Generative AI: A type of artificial intelligence capable of generating new content, such as text (e.g., ChatGPT).
• AI Infrastructure: The foundational hardware (like chips), software, and network components necessary to develop, deploy, and operate AI systems.
• Telecom Boom (early 2000s): A historical period characterized by massive investment in telecommunications infrastructure, particularly fiber optic cables, which ultimately led to overcapacity and a market correction.
• Hedge Fund: An investment fund that pools capital from investors and employs diverse strategies, often complex, to generate returns.
• Deregistration: The act of removing a hedge fund from regulatory oversight, which can eliminate requirements for public disclosure of investment positions.

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Michael Burry's Bearish Stance on AI

Michael Burry, widely recognized from "The Big Short," has publicly declared AI to be a bubble. A recent regulatory filing from the end of September indicated that Burry was actively betting against two prominent beneficiaries of the AI surge: Nvidia and Palantir. This move garnered significant attention, particularly given that these companies are perceived as "making all the money" in the current AI landscape, leading to initial reactions describing the shorting of chip-related companies as "super weird" and "bat crazy," even after Nvidia's "massive earning beat."

Deep Research Behind the Call: Phil Clifton's Analysis

The rationale underpinning Burry's bearish outlook is detailed in exclusive research conducted by his colleague, Phil Clifton. Clifton's analysis highlights a significant disconnect between the widespread adoption of Generative AI and the actual revenue generated, especially when compared to the colossal investments being poured into AI infrastructure.

• Revenue vs. Investment Discrepancy:

  • Despite the pervasive use of Generative AI tools like ChatGPT, the financial returns are currently modest. OpenAI, a leading Generative AI company, is projected to bring in "a little over $20 billion in revenue" this year.
  • In stark contrast, big tech companies have "quadrupled their investment to nearly $400 billion a year" to build out AI infrastructure. This represents a 20-fold difference between the projected revenue of a leading AI company and the annual investment by big tech.

• Business Proposition vs. Societal Benefit:

  • Clifton emphasizes a critical distinction: "just because the technology is good for society or revolutionizes the world doesn't mean that it's a good business proposition." This statement underscores the argument that technological advancement and societal impact do not automatically translate into sustainable, profitable business models, especially in the short to medium term.

• Parallel to the Telecom Boom of the Early 2000s:

  • Scion, Burry's firm, draws a direct parallel between the current AI investment climate and the telecom boom of the early 2000s. During that period, companies invested heavily in fiber optic cables, far exceeding what market demand ultimately justified, leading to overcapacity and a subsequent market correction.
  • Clifton argues that big tech companies are repeating this pattern with AI infrastructure, "spending massive sums before there's real proof that revenue will catch up." This suggests a speculative bubble driven by infrastructure build-out ahead of proven, commensurate demand and profitability.

Regulatory Status of Burry's Fund

Recently, Michael Burry deregistered his hedge fund with regulators. This action means his fund is "no longer required to disclose his positions," making it more challenging to track his current investment strategies and short bets.

Conclusion

Michael Burry's call that AI is a bubble, supported by Phil Clifton's detailed research, posits that the current AI landscape is characterized by an unsustainable imbalance between massive infrastructure investment and relatively modest revenue generation. The core argument rests on the idea that technological utility does not guarantee business viability, drawing a historical parallel to the over-investment and subsequent bust of the telecom sector in the early 2000s. This perspective suggests that the current spending spree on AI infrastructure may be premature, lacking sufficient evidence of future revenue streams to justify the scale of investment.