To The Moon

Everyone talks about $Amazon.com(AMZN)$ 's AI spending. I think they're looking at the wrong number. The more important announcement wasn't another quarter of heavy CapEx. It was this: Amazon has now completed its $50 billion investment in OpenAI. That changes the relationship completely. Amazon is no longer simply renting cloud infrastructure to AI companies. It is becoming part of the capital stack behind the entire AI industry. Amazon now gets paid in multiple ways Think about how the relationship works. Amazon invests billions into OpenAI. OpenAI uses AWS infrastructure. OpenAI buys Trainium chips. Amazon earns cloud revenue. Amazon sells AI hardware. If OpenAI becomes more valuable, Amazon's equity stake appreciates as well. Instead of partic

This week’s earnings delivered a fascinating contrast in the AI race. $Alphabet(GOOG)$ $Alphabet(GOOGL)$ $Meta Platforms, Inc.(META)$ $Microsoft(MSFT)$ $Amazon.com(AMZN)$ all sent the same message: AI demand is real, and they are willing to spend enormous amounts of money to capture it. But the market is starting to ask a harder question: Will all that spending actually translate into better returns? Meanwhile, $Apple(AAPL)$ is taking the opposite path. It is not building massive AI factories. It is not committing tens of billions of d

The biggest debate in technology right now is no longer whether AI demand exists. It does. The real question investors are asking is: How much are companies willing to spend to capture that demand — and will the returns justify the investment? Based on the latest earnings reports, the answer from the biggest technology companies is clear: They are still aggressively building. The AI factory buildout keeps accelerating $Amazon.com(AMZN)$ became the latest hyperscaler to show the scale of this investment cycle. The company reported $53 billion in capital expenditures during the second quarter, up 69% year over year, as it expanded AI data centers and supporting infrastructure. That follows a similar pattern across the industry:

For months, investors have been asking the same question: Can Big Tech keep pouring billions into AI without crushing cash flow? $Microsoft(MSFT)$ may have just delivered the strongest answer yet. Microsoft reported another standout quarter. Q4 revenue reached $90 billion, up 18% year over year, beating expectations by roughly $2.4 billion. Adjusted EPS also came in ahead of forecasts at $4.74. Azure continued to fire on all cylinders with 43% growth, while Microsoft Cloud revenue climbed to $59.3 billion. But the number that grabbed everyone's attention wasn't revenue. It was capital spending. Microsoft invested $35.8 billion into AI infrastructure in just one quarter, bringing full-year CapEx to $115.9 billion. Yet despite spending at that scale

For the first time since April 2025, $Apple(AAPL)$ has overtaken $NVIDIA(NVDA)$ to become the world's most valuable public company again. Current market value: Apple: approximately $4.95 trillion Nvidia: approximately $4.8 trillion The change wasn't driven by Apple suddenly announcing a breakthrough AI model. It happened because investors are beginning to look at the AI boom through a different lens. The Market Is Starting to Ask a Different Question Over the past few years, the dominant narrative was simple: Build more AI infrastructure. Buy more GPUs. Spend more on data centers. That strategy created enormous winners, with Nvidia becoming the face of the AI revolution. But recently, investors have beco

Six weeks ago, investors were desperate to get into $SpaceX(SPCX)$ . Today, many seem just as eager to bet against it. The stock was priced at $135 in its IPO, surged to $225.64, and finished last week at $115.07—nearly 49% below its peak. Along the way, an estimated $15.5 billion in paper profits accumulated on short positions. The mood has completely flipped. And that's exactly why this story is becoming more interesting. The first lesson was about hype. The second is about positioning. Before the IPO, the biggest risk wasn't the business itself—it was investor behavior. Too many buyers chased too few shares, and scarcity helped fuel an explosive rally. When the stock later fell back to its IPO price, some investors immediately assumed $135 had

The latest earnings season delivered a clear message: AI demand remains strong, but the market is becoming far more selective about how it rewards AI spending. $Alphabet(GOOG)$ $Alphabet(GOOGL)$ and $Tesla Motors(TSLA)$ both reported solid top-line results, yet their stocks sold off sharply after earnings. That wasn't because investors suddenly stopped believing in AI. It was because the conversation has shifted. Bigger AI budgets are no longer enough Alphabet continues to invest aggressively in AI infrastructure, with full-year capital expenditure expected to reach $180–190 billion. Revenue continued to grow, but investors focused on something else: capital spe

$Alphabet(GOOG)$ $Alphabet(GOOGL)$ just sent a clear message to the AI market: The AI infrastructure race is not slowing down. The company raised its 2026 capital expenditure forecast for the second time, lifting the range from $180–190 billion to $195–205 billion. Management also indicated that capital spending will remain significantly higher in 2027. The market’s immediate reaction was notable, with semiconductor stocks rebounding after hours as investors interpreted the move as another confirmation that AI infrastructure demand remains strong. Google Cloud Becomes the Key Growth Engine The biggest highlight from the quarter was not just AI spending — it was the performance of Google Cloud. Google Clo

$Tesla Motors(TSLA)$ 's latest message wasn't really about EV deliveries. It was about Optimus. During recent remarks, Elon Musk made it clear that he believes Tesla's humanoid robot could ultimately become the company's most important product—larger than anything it has built before. That statement says a lot about where Tesla believes its future lies. From building products to building platforms Looking back, Tesla's biggest achievements were never just the products themselves. The company didn't simply build electric cars. It built factories, battery technology, charging infrastructure, and manufacturing systems that allowed EV production to scale. The same pattern can be seen elsewhere in Musk's companies. Rather than focusing on a single prod

$Tesla Motors(TSLA)$ used to be the headline act of every earnings season. Investors watched every delivery number, every margin update, and every comment from Elon Musk. The stock was known for its ability to move sharply on even small changes in expectations. But the spotlight has shifted. With $SpaceX(SPCX)$ becoming a major market focus after its public debut, Tesla is no longer the only Musk-related asset attracting investor attention. At the same time, the stock has lagged behind major AI infrastructure names such as $Microsoft(MSFT)$ and $Meta Platforms,