200 Gigawatts or Bust: Dylan Patel on the Engineering Reality of AGI Scaling

Welcome back to Neural Intel. In this deep dive, we move beyond the hype to analyze the "Atoms" problem of AI. Dylan Patel (CEO of SemiAnalysis) explains why the industry is currently "short of everything"—from HBM memory to high-voltage electricians.Key technical topics covered:The EUV Math: Why it takes roughly 3.5 ASML tools to satisfy a single gigawatt of compute.The Memory Crunch: Why 30% of Big Tech CapEx is now flowing into memory, and why your next iPhone might cost $250 more because of AI.The Power Arbitrage: How "behind-the-meter" gas turbines and modular data center blocks are bypassing grid delays.Geopolitics of Silicon: Why a fast takeoff favors the U.S., but a long-duration race might give the advantage to a vertically integrated China.Neural Signal Check: We analyze why Elon Musk’s "Space GPU" plan faces massive physics and reliability hurdles compared to terrestrial liquid cooling.Follow the discussion on X: @neuralintelorg Read our architectural analysis: neuralintel.org