This episode reveals that AI is not a bubble but a 40-year-old paradigm shift creating infinite demand for intelligence, rendering traditional macro indicators obsolete and positioning deflation as the primary long-term risk.
Jordi Visser's Probabilistic Worldview
- Jordi Visser, President and CIO of Weiss Multi-Strategy Advisers, explains that his entire investment framework is built on probability, not absolutes. Shaped by a childhood learning odds from his father, a professional hustler, Visser approaches markets by identifying where the perceived odds are misaligned with reality. His career in derivatives and macro investing has been guided by this principle, leading him to view the current "AI bubble" narrative as a low-probability outcome.
- Visser’s perspective is grounded in skepticism and quantitative analysis, viewing all market information as opinions to be weighed within a probability distribution.
- He applies this framework to find asymmetric bets, such as his current conviction that the market is underestimating the long-term, structural impact of artificial intelligence.
The Failure of Traditional Macro Indicators
- Visser argues that old-school global macro frameworks are failing because they were designed for an industrial economy and cannot measure the modern digital, intangible economy. He points to the Leading Economic Index (LEI)—an index created by Geoffrey Moore to forecast economic activity—which has been negative for a record period without a recession, as a prime example of a broken indicator.
- The creator of GDP, Simon Kuznets, himself acknowledged that the metric could not measure intangibles. The value created by software, like the apps on an iPhone replacing countless physical goods, is largely invisible to these legacy systems.
- This disconnect explains why recession calls based on indicators like the LEI have been consistently wrong. The digital economy's growth is not being captured, leading to flawed analysis.
The Two-Part Economy and Wealth Concentration
- The modern economy is split between the old industrial economy and the new digital economy, with the latter becoming more dominant each year. Visser dismisses fears of a consumer-led recession, highlighting the massive $178 trillion in household net worth, which is six times the size of the US economy and provides a massive cushion for spending.
- This has created a system where wealth concentration at the top fuels economic growth, while government transfer payments (up 8.5-9% year-over-year) act as a form of Universal Basic Income (UBI) for the bottom.
- This dynamic squeezes the middle class, who neither benefit from asset inflation (Quantitative Easing) nor receive significant transfer payments, fueling the political anger and social division seen today.
Why AI Is Not a 40-Year Bubble
- Visser refutes the "AI bubble" narrative by framing it as a 40-year secular trend that began with the advent of coding in the 1980s. He argues that profit margins, not flawed productivity statistics, are the best way to measure technology's profound economic impact.
- He highlights the stark contrast in profitability: while the S&P 500 average profit margin is around 14%, Nvidia's margins exceed 70%. This demonstrates the immense economic power of the "coding part of the economy."
- "This is a 40-year bubble guys because coding started in the early 1980s," Visser states, emphasizing the long-term, structural nature of this technological revolution.
The Economics of the AI Buildout
- Visser contrasts the current AI capital expenditure cycle with the dot-com bubble. The dot-com buildout was funded by low-margin telecom companies with weak balance sheets. In contrast, the AI buildout is funded by the massive free cash flows of the world's most profitable tech giants.
- Strategic Implication: These companies are not just chasing quarterly revenue; they are in a race for military supremacy, personal legacy, and solving humanity's biggest problems like aging and disease. This provides a much stronger and more durable incentive for continued spending.
- While not every company's spending will be justified, the key players are the global experts in AI, using their own cash to fund the expansion. This makes the investment thesis far more robust than in the dot-com era.
The Transition to Vision and Infinite Compute Demand
- The current AI buildout is just the beginning, focused on Large Language Models (LLMs), which are text-based. Visser emphasizes the coming transition to Visual Language Models (VLMs), which integrate visual data and real-world interaction.
- A VLM (Visual Language Model) is an AI model that can understand and process information from both text and images, enabling it to interpret the world more like a human. This is a critical step toward advanced robotics and autonomous systems.
- Visser argues this shift will require 50 to 1,000 times more compute power for applications like robotic surgery and military humanoids. This creates a practically infinite and unending demand for compute.
- "We are literally plugging intelligence into every machine that has ever been built to make it be more efficient," he says, underscoring the limitless scope of AI integration.
The Government's Role and the "Genesis Mission"
- Visser highlights the critical importance of a recent executive order he calls the "Genesis Mission," which merges the public and private sectors to accelerate AI development. This order makes the AI buildout "untouchable" by designating it as critical for national survival against China.
- Actionable Insight: This government mandate is a major de-risking event for investors. It opens up 17 national labs, their data, and supercomputers to private foundation models, effectively neutralizing state-level opposition and prioritizing power generation for AI.
The Inevitable Deflationary Spiral
- Visser's core macro thesis is that the exponential growth of AI intelligence will lead to a deflationary spiral. As AI solves major problems in energy, chip efficiency, and manufacturing, costs will plummet across the economy.
- "The faster we have intelligence grow, the closer we're getting to a deflationary spiral," he warns. This is not an asset crisis but a fundamental economic shift where the number of "losers" (disrupted companies and workers) accelerates dramatically.
- He believes inflation is capped on the upside but is unlimited on the downside. This makes traditional inflation-focused monetary policy increasingly irrelevant for long-term investors.
Nvidia's Moat and the Future of the Magnificent Seven
- Visser views Nvidia as "dirt cheap" relative to its five-year outlook. He estimates a potential $5 trillion global spend on data centers, with compute accounting for at least 30% ($1.5 trillion) of that.
- Even if Nvidia's market share drops from 90% to 50%, its revenues could reach $750 billion by 2030, far exceeding current estimates. Its moat is protected because companies in a race for survival will not risk using unproven chips from competitors.
- In contrast, he suggests the other Magnificent Seven companies may start to resemble utility companies, providing the essential infrastructure for the AI economy but with potentially lower growth profiles over time.
Bitcoin's Role in a Financialized, AI-Driven World
- Visser frames Bitcoin as one of only three durable "moats" in the world, alongside gold and religion. It is the accepted store of value for the digital economy, offering a scarce asset in a world of infinite money printing.
- His conviction was solidified by Michael Saylor's rationale: businesses being disrupted by AI and devalued by government money printing need a scarce asset to protect their balance sheets.
- The Bitcoin ETF launches represented an "IPO moment," broadening ownership and increasing legitimacy. Visser sees Bitcoin as the ultimate asset for a world where AI destroys all other corporate moats and for the 7.5 billion people outside the Western fiat system.
Conclusion
- AI is a powerful deflationary force creating a new economic paradigm where traditional macro analysis fails. Investors must focus on the long-term implications of infinite compute demand, government-backed buildouts, and the destruction of business moats, positioning scarce digital assets like Bitcoin as essential long-term holdings.
