Why most investors are reading AI news wrong
There are two types of AI investors right now.
The first type reads every headline — "Company X launches new model!" — and makes allocation decisions based on vibes. They chase the hype cycle, buy after the pop, and wonder why their returns look like everyone else's.
The second type asks different questions: What's the actual revenue impact? Which companies have distribution moats? Where's the real margin expansion happening vs. where it's just narrative?
The difference between these two investors comes down to one thing: signal vs. noise.
Here's a quick example. Everyone knows NVIDIA prints money selling GPUs. But the smarter question is: which inference providers are building sustainable margin businesses on top of that hardware? Who's locking in enterprise contracts with 3-year terms? That's where the next wave of compounding returns lives.
Most AI coverage is written by tech journalists for tech enthusiasts. Almost none of it is written for investors who need to make actual allocation decisions.
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