Premium: The Hater's Guide To The AI Bubble 3.0

2026-06-05 · Source: Ed Zitron's Where's Your Ed At · Field: Finance & Economics — Capital Markets & Investment Management, Economic Analysis & Policy · Depth: Intermediate, extended

Summary

Ed Zitron's "The Hater's Guide To The AI Bubble 3.0," published June 5, 2026, asserts that the current AI boom is a speculative bubble driven by hype and ignorance, not sustainable value. While large language models (LLMs) exist, they fail to deliver on promises from figures like Dario Amodei and Sam Altman. The article claims 89%+ of AI revenues and 90%+ of compute demand originate from OpenAI and Anthropic, largely through money-losing subsidized subscriptions. The total AI industry revenue in 2026 is barely \$100 billion, with no profit outside hardware vendors like NVIDIA. Both OpenAI and Anthropic lose billions annually, yet Anthropic has filed for an IPO. Enterprises such as Walmart and Uber are capping AI spending due to high costs and unmeasurable ROI, with some blowing through annual budgets in months. The author highlights massive data center debt, including \$178.5 billion in 2025 and \$50 billion in April 2026, driven by speculative demand for compute that often doesn't materialize. He argues AI products are inconsistent, unreliable, and prone to "mathematically-certain hallucinations," making them unsuitable for most jobs.

Key takeaway

For investors considering AI-related stocks or executives evaluating AI integration, recognize that the current market is characterized by unsustainable economics and unproven returns. Your due diligence must extend beyond hype to scrutinize actual profitability, measurable ROI, and the inherent limitations of probabilistic models. Be wary of companies like OpenAI and Anthropic, which are deeply unprofitable yet pursuing IPOs, as they may represent exit liquidity for venture capital rather than sound long-term investments.

Key insights

The current AI boom is a financially unsustainable bubble fueled by hype, ignorance, and unproven ROI, not genuine technological advancement.

Principles

• Conflating capital expenditures with industry success is misleading.
• Probabilistic models inherently produce unreliable, "brainless" outputs.
• Unmeasurable costs and ROI indicate a fundamentally flawed business model.

In practice

• Scrutinize AI vendor claims for measurable ROI and actual capabilities.
• Evaluate AI costs based on token-based billing, not subsidized subscriptions.
• Avoid investing in companies with unproven profitability and high burn rates.

Topics

• AI Bubble
• LLM Economics
• Data Center Investment
• OpenAI
• Anthropic
• NVIDIA

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Investor, Executive, Tech Journalist

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• The ‘AI is inevitable’ trap — Public sentiment towards AI is souring despite its advancements, creating a market paradox.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Ed Zitron's Where's Your Ed At.