New newsletter: THE FOUR HORSEMEN OF THE AI BUBBLE APOCALYPSE
I am neither anti-AI nor certain that AI is a bubble. But the last four weeks have made clear that the AI buildout now faces a very clear quadruple-headed risk hydra.
1. A spending risk, as the hyperscalers run low on cash and take on $170b in annual debt—which is more than the projected UK deficit.
2. A revenue risk, as open-weight models threaten to compress the margins of frontier labs ... and as AI become the sort of internationally competitive asset-heavy industry requiring stable and determined long-term policy consistency, which is arguably China's competitive advantage.
3. A political risk, as anti-AI populism becomes one of the easiest applause lines, even as AI becomes a more and more foundational pillar of US economic growth
4. A technological risk, as the frontier labs bear down on RSI, which I think could significantly change the basic business model of the labs, as compute costs rise and rise for a set of super-advanced models that are fit for, and affordable to, a small minority of users (in, eg, cyber security)
In one sentence: The capabilities of AI are becoming more powerful, while some economic underpinnings of the AI buildout—and, as we’ll discuss, the political support for AI—are becoming more vulnerable.
Today's (long, 5k word) piece deeply considers each risk and also—because over-confidence in this space is typically a sign that you're not thinking hard enough—I offer the strongest reason to think each risk might be overblown.
derekthompson.org/p/the-four-hor
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The below tweet has come in handy more and more:
Quote
Alex Elliott
@alexpotato
Replying to @liminal_warmth
The dot com bubble popped despite FAANG going on to make so much money people can’t even fathom it.
Shouldn't there be a 5th risk - energy? If the industry somehow survives those four risks, the energy constraint would kick in good and hard.
Why are Americans pathologically obsessed with comparing EVERYTHING to the UK?
To this i would add - 1) inference shifting local further eroding API revenues - Apple and potentially Nvidia to gain from this; 2) capex/ end user applications revenue (properly counted) for sector as a whole - 700-1000%; 3) slow AI adoption by traditional economy suppressing
Essentially the entire thesis of The Alignment Myth. Couldn’t agree more.
The Alignment Myth: Why AI Feels Right But Gets Things Wrong
The crazy level of spending on compute right now is the proof that it’s temporary.
Microsoft is cash flow positive, maintaining margins, accelerating growth of its $100B/yr cloud business and compounding the entire $3.5T business at 18% per year.
Even if open source models win out, you still need compute to serve the intelligence. The demand for compute is insane. The return on capex for compute investment is insane, which is why Alphabet for example is going into debt.
