$7.6 trillion is being spent on AI infrastructure between 2026 and 2031 — and Nvidia is forecast to capture roughly 75% of the entire compute layer. Here is where every dollar goes, and the accounting gamble hiding underneath it. David and Sophia break down Goldman Sachs' map of the AI build-out: $5.1 trillion for chips, $2.1 trillion for data centers, and $358 billion for the power to turn them on. They explain how Nvidia's software moat produced roughly 75% gross margins on $80,500 chips, why server racks jumping from 15 kilowatts to 500+ kilowatts are forcing a total shift to liquid cooling, and why Meta is locking up 2,600 megawatts of nuclear power for 20 years. Then the uncomfortable part: the $1.76 trillion depreciation swing that hinges on one question — how long before an $80,000 chip becomes a brick? Michael Burry's short thesis says profits are inflated by over 20%. CoreWeave's rental data says 2020-era A100s still earn 95% of their original price. And underneath it all sits a closed loop of circular financing where the money never leaves the ecosystem. Chapters 00:00 The 40-homes-from-one-outlet problem 01:56 How $7.6 trillion breaks down 02:51 How Nvidia cornered 75% of compute 04:56 Training vs inference: AMD's agentic AI angle 06:52 From 15kW to 500kW racks: the liquid cooling shift 09:30 Power is the gatekeeper: Meta's nuclear deal 10:54 The $1.76 trillion depreciation gamble 15:00 The trillion-dollar closed loop 17:32 Copilot loses $20-80 per user; OpenAI's $14B loss 19:29 The paradox that could obsolete it all Key points - $7.6 trillion projected global AI infrastructure spend, 2026-2031; $765 billion flowing in 2026 alone - Nvidia forecast to capture ~75% of the $5.1 trillion compute layer, at ~75% gross margins - AI racks now demand 500+ kilowatts, pushing the liquid cooling market toward $15.75 billion by 2030 - A 3-year vs 7-year chip lifespan assumption swings industry depreciation costs by $1.76 trillion - GitHub Copilot reportedly lost $20-80 per user monthly; OpenAI projected to lose $14 billion in 2026 More from TechDaily: https://techdaily.ai Thumbnail photo: Frontier supercomputer, Oak Ridge National Laboratory / OLCF, CC BY 2.0, via Wikimedia Commons. #AIInfrastructure #Nvidia #TechNews

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