Michael Burry is wrong about AI and Nvidia

TLDR

Burry’s AI thesis mistakes early-stage experimentation for fake demand. Tokenmaxxing, benchmarking, and inefficient usage are not signs that the AI boom is hollow; they are exactly what adoption looks like before workflows mature, costs fall, and usage expands. Enterprises may optimize spend and route around expensive models where they can, but they are not going to compete with frontier labs or eliminate the need for massive compute. We’re still in the early innings of the AI boom: efficiency will improve, but usage should compound faster, keeping aggregate demand for compute on an upward trajectory.

Overview

Burry is bearish on AI and Nvidia. He’s provided his point of view in The Heretic’s Guide to AI’s Stars Part III: Tracepalooza & the Bezzle and here

Cassandra Unchained@michaeljburry

Great commentary yet again from BTIG’s Jonathan Krinsky
•Party Like It's 1999. In 1999, the best performing Nasdaq 100 stock was Qualcomm (QCOM, not rated), up 2600%. The best rolling 52-wk return for QCOM during the entire dot-com bubble was 2600%, so SNDK is beating that by

3:52 PM · May 6, 2026 · 234K Views

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Burry’s core point is that a meaningful portion of today’s AI demand is temporary, experimental, overfinanced, and being capitalized by the market as if it were durable, recurring demand. He thinks companies are “tokenmaxxing,” harvesting traces, benchmarking models, overbuying infrastructure, financing data centers through increasingly fragile channels, and mistaking a temporary training phase for a permanent demand curve.