Memory has only 3 players (MU, SK Hynix, Samsung); HBM yields are low, margins at 75%, and demand is infinite from AI, robotics, defense, and consumer devices. This supply-constrained oligopoly combined with exploding demand (every hyperscaler, robot, car needs MU) creates a structural pricing power that is not reflected in MU's cheap P/E. Buy MU for a multi-year compounder as the "floor" (non-AI revenue) is already diversified, and HBM adds exponential upside. Cyclical memory downturn (though author argues infinite demand changes the cycle); technology disruption from 3D X-DRAM or Z-angle (years away); geopolitics (China/Taiwan tensions); oversupply if competitors overbuild.
Memory has only 3 players (MU, SK Hynix, Samsung); HBM yields are low, margins at 75%, and demand is infinite from AI, robotics, defense, and consumer devices. This supply-constrained oligopoly combined with exploding demand (every hyperscaler, robot, car needs MU) creates a structural pricing power that is not reflected in MU's cheap P/E. Buy MU for a multi-year compounder as the "floor" (non-AI revenue) is already diversified, and HBM adds exponential upside. Cyclical memory downturn (though author argues infinite demand changes the cycle); technology disruption from 3D X-DRAM or Z-angle (years away); geopolitics (China/Taiwan tensions); oversupply if competitors overbuild.
Hyperscalers (Google, Amazon, Meta) are building in-house AI chips (TPU, Trainium, MTIA) that cost 3-4x less than NVDA's, and OpenAI is developing CUDA alternatives. Both software and hardware moats are eroding. The market still values NVDA as the sole AI beneficiary, ignoring that memory (MU) is equally essential and that NVDA's customers are actively escaping its ecosystem. NVDA is overvalued relative to its true competitive position; a short position can benefit as reality catches up with the narrative. NVDA's software ecosystem (CUDA) still dominates; hyperscaler chips may take years to scale; inference shift could still favor NVDA; short squeeze risk.
Hyperscalers (Google, Amazon, Meta) are building in-house AI chips (TPU, Trainium, MTIA) that cost 3-4x less than NVDA's, and OpenAI is developing CUDA alternatives. Both software and hardware moats are eroding. The market still values NVDA as the sole AI beneficiary, ignoring that memory (MU) is equally essential and that NVDA's customers are actively escaping its ecosystem. NVDA is overvalued relative to its true competitive position; a short position can benefit as reality catches up with the narrative. NVDA's software ecosystem (CUDA) still dominates; hyperscaler chips may take years to scale; inference shift could still favor NVDA; short squeeze risk.