
Is AI Trade DEAD? 🤖 $835B Capex vs $2.4T Backlog: The Real Math💥
The speaker analyzes the current state of the AI trade, weighing bearish and bullish arguments.
🔴 Bearish Arguments (AI Trade in Danger)
- Credit markets are collapsing: Neo-cloud providers like Oracle and CoreWeave struggle to get financing. Credit default swaps are at all-time highs.
- Data centers are unpopular: Nearly 70% of the US population opposes AI data centers, which could slow expansion.
- Bottlenecks and construction delays: Building data centers takes years, especially regarding power supply and permits.
- High CapEx: The Big Four (Amazon, Google, Microsoft, Meta) plan to spend around $835 billion, with more to come. Can they afford it?
- Financing difficulties: Rising interest rates (10-year US Treasury at nearly 6%) make capital more expensive.
🟢 Bullish Arguments (AI Trade is Alive)
- Massive demand: The backlog is $2.4 trillion – almost three times this year's CapEx.
- Jevons Paradox: As AI gets cheaper, demand skyrockets. Training costs dropped from $20M to $100.
- Cloud growth: Azure +43%, Google Cloud +82%, Amazon +37% – investments are paying off.
- High inference margins: Despite falling prices, margins rose from 40% to over 70%.
- AI infrastructure boom: Annual AI infrastructure spending is projected to reach $3-4 trillion by 2030.
- Chip shortage: Nvidia GPUs and HBM memory are sold out through 2027/2028. Google is securing HBM until 2035.
- Strong revenue growth: OpenAI and Anthropic are growing rapidly (revenues could reach $500B within 12 months).
⚖️ Verdict
- The AI trade is not dead. The bullish arguments overwhelmingly outweigh the bearish ones.
- There will be casualties (e.g., neo-clouds), but the big hyperscalers (Microsoft, Google, Meta, Amazon) have sufficient free cash flow to fund their investments.
- The speaker advises: Don't lose faith, use pullbacks as buying opportunities.
- The AI boom is driven by a double exponential function (more compute per task + more tasks).






