Super Data Science: ML & AI Podcast with Jon Krohn 974: When Will The AI Bubble Burst? How Bad Will It Be?
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Mar 13, 2026 A rapid look at signs of AI hype, from questionable startups to massive spending on compute and researchers. A tour of historical bubbles like railways and dot-coms that left lasting infrastructure. Discussion of how big bets signal demand and lock in adoption. Practical warnings about timing and how technical fundamentals can protect practitioners if a correction comes.
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Cluely Cheating Tool That Attracted Big Funding
- Jon Krohn recounts the Cluely startup saga that marketed an AI to help people cheat on interviews and raised millions despite controversy.
- Cluely pivoted after backlash, its CEO misstated ARR, and top VCs still funded it, illustrating frothy AI-era hype.
OpenAI's Trillion Dollar Compute Commitment
- Jon Krohn highlights staggering AI spend: OpenAI committed roughly $1.4 trillion in infrastructure over eight years, later revised toward $600 billion by 2030.
- That scale eclipses past tech booms and contrasts with OpenAI's $13B revenue, signaling extreme capital intensity and risk.
Bubbles Can Make Complementary AI Layers Self Reinforcing
- Jon Krohn summarizes Hobart's argument that bubbles lower risk aversion and create complementary investments across layers like chips, grids, and products.
- When layers all invest expecting more AI, it becomes a productive, self-reinforcing ecosystem even if speculative.
