this post was submitted on 03 Oct 2026
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So I saw a few relevant newspieces:
~ Companies are now ceasing their mandate to workers to use AI to do things that used to be done without AI. They're now saying don't use AI just to use AI. They're trying to reduce their token purchases.
~ The estimation now for AI use cases is to reconsider if tokens cost ten times their current price. If the use case is still worth it, then that use case will likely survive the bubble. If it's not worth it, it's time to hire back employees.
~ The hyperscale AI industry will have to make $6 trillion annually to break even. Amazon makes $2 trillion by selling people material stuff. Walmart is similar. There may not be a market for $6 trillion in tokens every year, even from government projects. Also, it's a bad sign if government projects are propping up the whole stock market.
~ China is mostly turning to a software AI model which does home and small business AI tasks fairly well without buying compute from a hyperscaler. You get a gaming machine, get open source AI software and a dozen terabytes of training data, and you should be able to create slop, vibe code or fix the grammar and style of your report. Also, hyperscale models are opinionated and don't like certain topics. Home-grown AI doesn't have those objections.
Some companies already run Chairman Xi's big models on-prem and do not limit token usage on those.
Unless you create or review the training data and train your model yourself, home grown AI models do have those objections.