Why are billionaires buying plumbers?

Investors rushed to buy both AI and gold Something unique started happening in August. Investors simultaneously started aggressively buying AI companies, gold, and even Bitcoin. What’s the connection here? It’s actually a very unusual one. To build AI data centers, the biggest tech companies are spending hundreds of billions of dollars. They need money for that. A lot of money. Which they keep borrowing in the market. In 2026 alone, their spending could approach $700 billion. And the problem is that the U.S. government is borrowing money in exactly the same way. And the more they borrow, the higher the interest rate they have to offer on that debt. But in August, the Treasury stepped in. And increased its buybacks of its own bonds to bring that very rate down. Investors immediately understood: Debt is becoming too expensive, and now the government will be looking for ways to make it cheaper. And the more interventions like this we see, the stronger the fear that the dollar will lose value. That’s why some of the money is moving into gold and Bitcoin. Which, as a result, saw inflows of $7 billion in just 5 days. At the same time, no one is giving up on AI either. Nvidia keeps climbing, and money is still flowing into tech funds. The market is now simultaneously buying AI as a bet that technology will make the world richer, while also buying gold and Bitcoin as insurance in case the bill for this party turns out to be too big and the system can’t handle it.

Tesla will release a “human” for $20,000 Musk officially confirmed: the first Optimus robots will go on sale in 2027. And the bet on them is so massive that, to make room for these robots, the company has already discontinued its legendary Model S and Model X cars. Tesla wants to create a truly universal assistant: clean the house, put things away, bring in groceries, load the washing machine, open the door, use regular tools, and learn new tasks simply by being told what to do. In short, a new member of the family for every household. And on top of that, a universal worker in any factory. The target price is around $20–30K, although Tesla has not announced the final price yet. Right now, in Texas, they are designing a factory to produce 10 million robots a year. That’s 20 times more than the number of robots being made worldwide right now. So Tesla is going almost all-in on this field. Although the bet is worth it. If Optimus learns to work like a human, for the first time, the workforce could simply be produced on an assembly line. And here’s a solution to demographic problems around the world. Do you believe robots can partially replace physical labor this quickly? ❤️ – It’s possible 👍 – I don’t believe it

Apple just released a $2,000 iPhone It’s called the iPhone Duo. And yes, as many of you may have already heard, it’s the first foldable iPhone in history. The price starts at $1,999. This is an experiment. Apple is essentially testing whether millions of people are willing to pay for a smartphone like they would for a good laptop. If they are, the price ceiling for premium phones has just been pushed significantly higher for the entire market. Analysts are already expecting 6–10 million Duo sales in its first year. In a strong scenario, that number could reach 15–20+ million. If the Duo actually sells better than expected without hurting margins, analysts will have to raise their forecasts for Apple’s earnings. In a strong scenario, that points to around $400–430 per share, versus the current ~$315.

Is ChatGPT destroying Wall Street? OpenAI rolled out ChatGPT for finance today. It includes data on roughly 13 million companies and 3 million transactions. You can give it a specific stock – anything from a company like Apple to a little-known business. And get a full breakdown: how revenue and earnings are growing, how much debt the company has, how it stacks up against competitors. And how much the stock could be worth under different scenarios. It pulls all of this together in Excel and backs it up with sources. A professional deep-dive that a team of Wall Street analysts could previously spend days or weeks putting together can now be done with a single prompt in a matter of minutes. The product was built in partnership with Morgan Stanley. There, 98%+ of financial advisor teams are already using the AI. OpenAI is now testing the tool with banks and funds. The next step – add it to regular ChatGPT, so the kind of analysis used by the world’s biggest banks to evaluate virtually any asset could end up in anyone’s phone.

“Stop AI!” It may seem like we’ve heard those words from just about everyone in recent years. But now the head of Anthropic (the company behind Claude) has officially joined them. He published an entire essay and called for slowing down the development of the most powerful AI systems. He was quickly backed by Sam Altman, Elon Musk, and the head of Google DeepMind. Now, that’s something new. And honestly, the reason behind these statements is just as surprising. OpenAI ran a test: the AI was simply supposed to hack a specially designed training server. But it found a way not only to break in, but also to escape the environment and start attacking real services on the internet. The test involved 533 AI agents working simultaneously, with a shared chat where they could coordinate with one another. When one of them found a way to reach real servers, it posted the instructions there — and the others picked them up. Anthropic later ran a similar test with Claude and found something comparable. The AI uploaded a malicious program to the public internet, and it was actually run on 15 real computers. And all of this is happening at a time when Claude already writes more than 80% of the code inside Anthropic 👍 That’s why the company’s CEO has now called, for the first time, for pausing the development of new models until developers learn how to properly control them. But the problem is that if one company does this while its competitors in the U.S. or China keep making AI more powerful, it will simply lose the race. That’s why the conversation is now shifting from what one company should do to common rules for the biggest AI developers — and even agreements between countries.