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In 1951, two comics named Dennis the Menace launched. One in the U.S. and another in the U.K. Both starred a slingshot-wielding troublemaker. Same name, same character, same month. Weird thing is… There was zero communication between the two creators. They lived in different countries, worked in different media, and published within days of each other, completely independently. This is a textbook case of simultaneous discovery: When the same idea pops up in different minds, in different places, at the same time—without collaboration. It happens more than you might think. For example: In 1869, Dmitri Mendeleev said the periodic table came to him in a dream. That same year, Julius Lothar Meyer published nearly the same table—independently, in another country. In 1876, Alexander Graham Bell and Elisha Gray filed for the telephone on the exact same day, despite working on it independently and with no contact. (Bell got there first by just a few hours… the rest is history.) In the 1930s, Frank Whittle and Hans von Ohain built the jet engine—separately, without contact, in different countries. Both machines took flight within a decade. The same happened with the discoveries of oxygen and calculus. With photography. With sunspots. With Neptune. Different people. Different places. Same idea. Same time. And, in 2025, it just happened again… Not in a lab. Not in a university. Source: https://altucherconfidential.com/posts/the-trade-that-crashed-the-party Profits from free accurate cryptos signals: https://www.predictmag.com/

First prediction: AI infrastructure will become as essential as physical manufacturing infrastructure. Every company that builds a physical machine will also need to operate a second kind of factory: one that produces the AI brains for those machines. Cars and car minds. Drones and drone minds. Lawnmowers and—God help us—lawnmower minds. It’s not enough to build the hardware anymore. You’ll also need a dedicated system to build the software intelligence that controls it… An ongoing process of training, updating, and improving the models that govern behavior. At least, that’s how NVIDIA has stayed ahead. NVIDIA’s edge lies not just in hardware, but in its software moat—CUDA. This enables NVIDIA’s chips to get better over time, making them more valuable long after purchase. As a result, GPUs like Hopper (H100) retain 75–80% of their value even a year after release. (Unlike your car. Or your Peloton. Or that memecoin your cousin Todd made you buy.) But it was Huang’s next prediction that got the most airtime on X: “AI will create more millionaires in 5 years than the internet did in 20.” We’re used to hearing bold predictions from tech billionaires. But this one? If he’s right, we’re living in the single-biggest wealth transfer in history. Read that prediction again. Now look around: Has anything prepared you for that kind of wealth explosion? Probably not. So What’s the Play? You don’t need to code. You don’t need a VC fund or a PhD in computer vision. What you need is leverage. Here’s the simplified version of Jensen’s framework—translated from silicon-speak into plain English: Identify where AI removes friction: Wherever something is annoying, repetitive, or slow… AI is coming for it. Think infrastructure, not just products: Platforms, protocols, and pickaxes are where the real wealth is made. Bet on intelligence arbitrage: Those who move fastest to integrate AI will outcompete those still stuck in meetings. Capitalize on trust: AI is powerful. But people still crave humans they can trust. Be the bridge. This isn’t a gold rush. It’s something bigger. Gold rushes end. Infrastructure lasts generations. You’ll either look back at this moment and say: “I wish I started then…” Or: “Thank God I did.” Here’s What Steve Would Do When it comes to investing, the same rules apply: You won’t get outtraded by AI. You’ll get outtraded by Steves… who use AI. So what is Steve doing? He doesn’t code. He doesn’t day-trade. He thinks Python is just a brand of golf polo. But he’s definitely looking to use AI to spot under-the-radar opportunities in the markets. Models just like James’ DeepBlue 2.0. In the past, DeepBlue 2.0 flagged: Lockheed Martin before Russia invaded Ukraine Weight Watchers before Ozempic The 2020 crash before it hit CNBC Right now, as you read this, the next signal’s already loading.” – Chris Campbell (AltucherConfidential) Profits from free accurate cryptos signals: https://www.predictmag.com/

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