The AI boom is hitting turbulence, and the cracks are getting too big to ignore. The so-called “Magnificent Seven” have committed nearly $1 trillion to AI infrastructure, but make no mistake—this is a strategic bailout-in-the-making. They’re angling to be “too big to fail” under a second Trump administration, ensuring taxpayers foot the bill when reality catches up.
Just months ago, these tech giants were hostile to the GOP. Now, they’re suddenly making themselves indispensable. But there’s a problem: a lot of this spending is smoke and mirrors. Many of these commitments are just press release fluff designed to pump stock prices while insiders quietly exit at the top. Microsoft is a prime example—it’s been trading sideways for a year, and now? They’re pulling the plug on major AI projects.
The Microsoft Retreat—And What It Means for AI Demand
Microsoft just walked away from OpenAI’s Stargate project. The reason? Overestimated demand. They’ve also begun canceling massive data center leases, cutting over $100 billion in future commitments that were supposed to roll out between 2025 and 2030. This isn’t a minor course correction—it’s a sign that the AI capex bubble is hitting a wall.
And if Microsoft is pumping the brakes, Nvidia is in serious trouble.
Grok 3.0’s Verdict: Nvidia’s Earnings Are Set to Implode
Grok 3.0 laid it out in brutal terms: “Nvidia’s upcoming earnings are poised to be a trainwreck.” Wall Street’s been running on AI-fueled euphoria, but the numbers are starting to tell a different story.
For months, Nvidia has been riding on hyperscaler demand—Microsoft, Meta, Alphabet, Amazon—gobbling up their GPUs to fuel the AI race. But now? The spending spree is slowing down. Microsoft’s pullback is a flashing red warning sign.
- Microsoft’s CFO, Amy Hood, has already signaled that capex growth will slow dramatically in 2026.
- Meta, Alphabet, and Amazon have committed over $228 billion to AI infrastructure, but the cracks are showing.
- **Meta’s Q1 sales forecast was weak, Alphabet is throwing money at diminishing returns, and Amazon is using older Nvidia H100 chips—**not exactly a ringing endorsement for Nvidia’s newest, most expensive lineup.
DeepSeek’s Disruption—A Direct Threat to Nvidia’s Business Model
Then there’s DeepSeek, the Chinese AI firm quietly rewriting the rulebook. Their R1 model competes with OpenAI’s best, but it was trained on older Nvidia H800s—not the top-tier, high-margin H100s or the upcoming Blackwell GPUs Nvidia is banking on.
The numbers are shocking: DeepSeek’s entire training run cost just $5.6 million. They didn’t need the most expensive Nvidia hardware, and yet they’re still delivering elite performance.
Even if SemiAnalysis is right about DeepSeek owning 50,000 GPUs and $1.6 billion in hardware, the fact remains: they just exposed Nvidia’s biggest weakness. If AI labs can get top-tier results without Nvidia’s cutting-edge chips, why would companies keep pouring billions into them?
The AI Capex Boom Is Peaking—And Nvidia’s Next Earnings Will Prove It
Nvidia’s Q3 numbers were insane—$30 billion in data center revenue. But that was fueled by an AI capex binge that isn’t sustainable. Wall Street expects $42 billion in Q1 fiscal 2026, but Grok 3.0’s warning looms large:
- Microsoft’s retreat means less demand for Nvidia’s top-end GPUs.
- DeepSeek and other AI players are proving you don’t need Nvidia’s most expensive chips.
- Capex spending across Big Tech is peaking—2025 may be the last big year before a major slowdown.
Nvidia’s dominance isn’t vanishing overnight, but the easy money phase is ending. If growth slows, Wall Street will have to rethink its sky-high expectations.
Sources:
https://x.com/ns123abc/status/1893910743805825524
https://x.com/unusual_whales/status/1893978428086358346
https://x.com/JPATrades/status/1894029146528850138
https://x.com/DarioCpx/status/1893948235900678221