Comp sci people are wrong a lot. This happens, it's obvious, the program fails, you don't know why. You admit you don't know, learn, and fix it. There's humility. Folks who write pretentious, cynical comedy articles? Never provably wrong == no reason to learn and improve.

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Cryptocurrency is for criming. Unfortunately it turns out the definition of “criming” is very expansive depending on where you live and who you are

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Even the AI companies & hyperscalers feed this misperception a bit. There are a lot of infrastructure/supplychain/regulatory bottlenecks to building out data centers. A chunk of what's been announced will never get built (it was only optioned) & what does get built will be over multi-year timeframes

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Relatedly, I very much *can* see *some* of the hyperscalers losing their shirts here, but the economics of *inference* remain excellent even in a scenario where AI infrastructure is overbuilt. In fact, in this crash scenario, inference gets cheaper and end users will do more of it.

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Everyone has their knives out for Ed Zitron because he's badly wrong about basic details of how AI works, whether inference can ever be profitable (the success of open models shows it can be, because ppl are literally paying their own costs to use them for inference), and the corpo bond markets.

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