The Delusion of Scaling Laws
The thesis behind AI investment today is that AI systems will get exponentially smarter with exponentially more investment. This is the "Scaling Law", as I understand it.
Today's AI may be an 8-year-old, who can do some stuff, but imagine if it's a 16-year-old. They can do lots more stuff.
In theory, that seems true.
But we know OpenAI is burning ~$5 billion this year. The ROI on $64 billion of investment is NEGATIVE!
Why do we think OpenAI's economics will be significantly better if they 10x their investment?
Why would the ROI improve even further if they 100x their investment?
To torture the analogy further, an 8-year-old is expensive. But a 16-year-old needs a car, and that's REALLY $*%&ing expensive! And that 16-year-old still isn't even paying rent!
We're spending trillions of dollars on a hope and a prayer that scaling laws not only work technically, but come with some kind of business model/ROI magic if they do.
I don't see where the application layer payback is with all of these investments. ALL of U.S. capex is less than $9 trillion. 1 company is talking about needing over $1 trillion, at least! Several trillion if we're going to build enough power for AI.
Are AI people delusional that the economics will work eventually or am I the delusional one?
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I've been consuming a lot of interviews with smart people in AI.
Every time I end up thinking, "Owning $Alphabet(GOOG)$ $Alphabet(GOOGL)$ is the best bet AND it comes with the lowest risk."
I'm going to keep it simple.
IMO, portfolio diversification is more about psychology than math.
If you own <5 stocks, it's easy to be emotionally attached to them, which clouds your judgment.
If you own 20-30 stocks, it reduces emotional dependence and gives a wider view of the investing world.
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