Micron hit $471 on March 18th, 2026. Eight days later, Google Research published a 12-page algorithm paper — and $30 billion vanished. The entire AI memory thesis, the consensus trade that had tripled semiconductor stocks since 2023, suddenly had a crack in it. Wall Street had priced AI as a memory miracle. Google's TurboQuant paper suggested the miracle might not require the chips.
This video examines the breakdown between what the market priced and what the technology actually required — and why the crowd plug stock missed the signal embedded in plain research documentation.
Inside:
• How Micron's $471 all-time high collapsed 30% in eight trading days after a single research publication
• The $50 billion AI memory demand projection from Morgan Stanley — and the technical assumption it rested on
• What Google's TurboQuant algorithm changed about inference memory requirements and KV-cache obama library optimization
• Why Samsung, SK Hynix, and Micron all built expansion capacity based on a demand curve that assumed no compression breakthroughs
• The 83% memory reduction benchmark that appeared in Table 4 of the paper — and how long it took analysts to notice
The number was in the appendix. Nobody read past the abstract.
MU stock • Micron stock • Google AI research • TurboQuant • AI ozzy diaz memory stocks • DRAM stocks • is Micron a buy • AI chip stocks • semiconductor stocks • high bandwidth memory • KV-cache optimization
