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Discussion (10 Comments)Read Original on HackerNews
I’m still not seeing any equally compelling arguments as to why this is not the case. Only accusations of doomerism and links to him calling the bubble collapse early.
Zitron relies too heavily on how big the numbers are and not how workable the numbers are. Further, he seems to think that it will all just implode, which is pretty unlikely.
AI companies are making money. 1T in purchase negotiations is something that can be renegotiated if the numbers don't improve. And there's actually a pretty good chance that these AI companies sell the US federal government on AI being a strategic advantage which can ultimately gets a nice federal funding source.
Even in the worst case of what ed predicts, the more likely outcome is that the AI companies slow rollouts and purchases. The general market takes a hit, but it's ultimately not the end of the world.
But further, even with AI reducing their consumption, that doesn't mean chip manufacturers are hosed, we've already built up huge demand for things like RAM which are supremely supply constrained. That' has slowed the sale of consumer and enterprise electronics. Easing back on the AI market means those markets will likely pick up the slack again. Especially because I suspect businesses will be seriously thinking about things like "Why don't we deploy deepseek locally to save on compute cost?".
I suspect that prices for AI will ultimately increase before any of this happens and with those price increases that's where I can see there being more a demand to break ties with the bigger AI companies.
What Ed misses is that big business has much MUCH more flexibility when it comes to financing than even a midsize corperation. They have direct lines to bank presidents.
Microsoft’s total depreciation and amortization in Q2 2027 was $11B - not clear how much of this is AI related. Apparently they had $34B in AI ARR as of May.
So let’s say their AI capex amortization and revenue are about equal. Not amazing, obviously they’re relying on continued growth, but doesn’t seem like the end of the world?
Compare that to Ed’s framing - Microsoft has $34B in revenue but spent $116B in capex last year to “make it”. They’re doomed!
But that capex spend is to make future revenue. Clearly he assumes demand won’t increase in the future, and that future projected revenue is “fake”. And sure, it definitely might not increase enough to make profitability.
But his whole analysis hinges on that one assumption. The entire article, all the numbers he gish gallops at you, could basically be replaced with “I don’t think AI demand and revenue will increase much beyond today.” Yeah, we know.
this is a funny way of spelling "cites sources" and "does basic math"
We see that these companies have no moat.
We see that companies are already balking at the cost and are increasingly looking at what the actual return of their current spend is, let alone when these prices have been increasing.
Where is the increase in demand going to be coming from? Especially the increase needed to make this make sense?
Also: note that the Wall Street analyst estimates Ed cites (and then declares impossible targets) are predictions by serious people with a lot of money at stake. Of course they could be wrong, but they’re not made up.
> As Nik Suresh noted in his recent piece, refusing to say that AI is giving you massive productivity benefits will lead to actual professional consequences, because so much is riding on the overall grift about what AI can do (which is much, much less than the boosters will promise). This runs antithetical to productivity or good sense, and everybody involved in it should be both eternally shamed and shunned from any sensible business.
> And while the AI industry and its fandom will claim that people like me are “skeptics” and “haters,” the outright hatred and vitriol that they spew for not falling in line behind a nakedly false narrative built on outright disinformation is disgraceful.
sigh
Ed has repeatedly done the "why are people using LLMs?" bit but ignores what well-respected software engineers have actually said about them because he thinks they're AI boosters and they are just lying. At the least, it's an obvious blind spot to explain how the AI industry is what it is despite the numbers he reports arguing otherwise, and many of his industry trend predictions have been incorrect as a direct result.