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Milk Road AI
@MilkRoadAI
Helping millions of investors navigate the AI markets. Capitalize on the biggest technological change in history across the infrastructure & app layers of AI.
Joined October 2025
420 Following    50.1K Followers
Oracle got crushed and it's no longer just a neocloud problem. $ORCL fell 8.8% on Wednesday to close at $130.55, after the hot CPI report pushed up bets on another Fed rate hike. The stock is now down about 58% from its high of $308.87 a year ago. Debt is the issue because S&P cut Oracle to BBB minus in July, one notch above junk. Yields on its 2032 bonds rose to 7.24%, and the cost of insuring Oracle's debt against default hit a RECORD high. Oracle is the only one of the big AI spenders without an investment grade rating from S&P. Alphabet, Amazon, Meta and Oracle have issued more than $228 billion in bonds so far this year, more than double all of 2025. BUT the bull case is the backlog, Oracle has about $638 billion in contracted business, and Mizuho just reiterated Outperform with a $320 price target after an update showing construction on its New Mexico data center is moving forward. Higher rates are hitting the AI names that are building on borrowed money hardest, and Oracle is the biggest of them.
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The amount of money Big Tech is about to pour into AI infrastructure is actually INSANE. Capital expenditures from the five major hyperscalers, $AMZN, $MSFT, $GOOGL, $META, and $ORCL are projected to increase from roughly $430 billion in 2025 to nearly $1.2 TRILLION annually by 2028. That's almost THREE TIMES as much spending in just three years. These companies are essentially rebuilding the computing infrastructure that the global economy will depend on for decades. Think about everything that goes into an AI data center. You need GPUs to train and run models, CPUs to manage workloads, HBM and DRAM to feed those processors with data, networking equipment to connect thousands of chips together, optical transceivers to move information at enormous speeds, and massive amounts of electricity to power and cool everything. And as AI models become more capable and adoption increases, the infrastructure required to support all of this becomes even more demanding. This is exactly why I've been so bullish on the companies supplying the infrastructure behind AI rather than trying to predict which AI model or application will ultimately win. Now, obviously, not every dollar of this spending will turn into profits for suppliers. Competition, pricing pressure and execution will matter a LOT, especially as these companies continue expanding capacity. But when you're looking at more than $1 trillion in annual spending from just FIVE companies, I think it's pretty clear why the opportunities across memory, networking, optical components, power, and semiconductors could be enormous. That's why I continue to believe AI infrastructure will be one of the biggest investment opportunities of this decade. The spending is already happening and the companies supplying the critical components are in a position to benefit for years to come.
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