Comment by thenaturalist
9 hours ago
The hits are coming closer.
Microslop CEO begging for AI $$$ because astronomical overprovisioning is becoming obvious, all big spenders frantically trying to hide CapEx from their books and hallucinate revenue projections like its Enron reloaded and Oracle is already getting sued by bondholders over AI spend [0].
It will be worse than the dot com bust.
0: https://www.reuters.com/sustainability/boards-policy-regulat...
To me CoreWeave is the one to watch. They have to actually bring all these promised datacenters online, operational, and profitable. They basically got a $2B bailout from Nividia a week or so ago but they're back to sinking.
https://ts2.tech/en/coreweave-stock-slips-as-class-action-no...
Consumer can eat all the GPUs they have and more if we stop trying to force B2B
Right we have a loop where AI is so expensive (because it's priced to feast on B2B margins) that the best consumer experiences aren't affordable, and they're not affordable so they don't go mainstream, and they're not mainstream so no one is willing to take less money and bank on the incredible volume that would emerge if it went mainstream.
If we can get model pricing cheaper AI entertainment alone will probably carry things (I'm 99% sure NovelAI is already one of their largest customers outside of major AI labs)
Even if consumer can eat all the gpus, it cannot have the margins (as you say), and thus won’t sustain the current valuations all these companies have and which fuel the (necessary) investments.
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> Consumer can eat all the GPUs they have and more if we stop trying to force B2B
You should really crunch the numbers on buying and then running enough compute to run a leading edge model. The economics of buying it (never mind running it) just dont add up.
You still haven't factored in "training", the major problem right now that every one remains head in sand about.
I dont need a model to know who Tom Cruise is or how to write SQL if I am asking it "set up my amazon refund" or "cancel xyz service". The moment someone figures out how to build targeted and small it will take off.
And as for training, well having to make ongoing investment into re-training is what killed expert systems, it's what killed all past AI efforts. Just because it's much more "automated" doesn't mean it isnt the same "problem". Till a model learns (and can become a useful digital twin) the consumer market is going to remain "out of reach".
That doesn't mean we dont have an amazing tool at hand, because we do. But the way it's being sold is only going to lead to confusion and disappointment.
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If you believe it will happen in the next 6 months how do you prepare for that?
If you truly believe this, slowly divest everything into cash, wait for the crash, then buy back in. Even buying in slowly over the course of a crash, on the way down, will save you a ton of money if you're out before it hits.
But you're more likely to just cash out early, lose a bunch of gains, then buy back in later at higher prices.
If you can time the crash you can make a shitload of money. But you can't, so you'll come out better if you just keep buying in every paycheck and ride it out just like you have been.
Yes to this. Take no alternative actions. Just keep investing and don't watch the market for a year or two.
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Doing nothing different is the kind of plan I can easily execute !
It doesn't have to be 'ride it till it dies' or 'sell everything'. The AI bubble is almost exclusively contained to the US stock market and a few east Asian manufacturers.
You're right that selling everything and 'going to cash' would be a mistake, but diversifying away from US large cap growth absolutely wouldn't. I'm 60/40 stocks/bonds. My stocks and bonds are 50/50 us/intl. ~ 10% of my us portfolio is small cap value.
What's funny to me is that nobody learns from the past. This is far from the first tech bubble we've had even before the .com crash (canals, railroads, radio...). The answer, every time was diversification.
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Invest into stuff that people will need regardless of the bubble popping like medicine, food, internet access, energy, ... . Stay away from luxury/travel stuff.
Also, during a crash there is the so called "flight for quality" where people cash out from risky assets and invest in stable ones that can weather the storm. So, try to invest in assets that are A or above (https://en.wikipedia.org/wiki/S%26P_Global_Ratings). The chart is for countries, but analysts grade companies as well in case you want to stay away from treasuries/national bonds.
Also diversify geographically. US will likely take the biggest hit if the bubble pops, so perhaps European markets that lagged behind in adopting the technology are safer (IMHO).
Personally, I am preparing by moving money from growth items to stable ones a bit at the time. To diversify even further I am using ETFs that, in addition to what mentioned above
1) pay dividends (whether these distributed or reinvested doesn't really matter) 2) are denominated in or hedged in safer currencies (CHF especially, but also Euro)
You definitely get smaller returns, but the name of the game is to maintain what you have, not to make heaps of money.
Finally, I am not a financial advisor, so do your own valuations/risk assessment analysis.
Almost all the gains in the SNP500 are NVidia, and other huge tech.
https://www.investopedia.com/your-s-and-p-500-index-fund-mig...
https://www.cnbc.com/2025/10/22/your-portfolio-may-be-more-t...
Buy Puts
>It will be worse than the dot com bust.
And whose fault is that?
Big scale fraud like this always has its origin and motive force in the executive suite and board.
However, the consequences are always applied to everyone but the executives and board.
The post dot com winners? Ironic.
> And whose fault is that?
Primarily the fault of our governments not using anti-trust laws for real in, like, decades.
Governments actually do have the power to regulate the economy and to prevent catastrophic crashes from occurring. The warning signs for the AI bubble have been visible for well over a year now, when the entity relationship map between the major players began to resemble a Habsburg family tree... and yet, nothing was done.
> astronomical overprovisioning
???
Literally all the cloud providers have been reporting severe capacity crunches for the past few quarters -- to the tune of backlogs of triple-digit billions each. As a reminder, a backlog or "Remaining Performance Obligation" (RPO) is money their customers have committed to them but they could not realize because they didn't have enough capacity to serve their workloads. Which is why they are all committing to double-digit billions each in AI CapEx spend over the next few quarters.
And most of them (aside from Oracle, which is trying to borrow its way into this gold rush) are investing money from their double digit billions in profit (per quarter!) into this spend... money that they could have otherwise comfortably held on to for something more palatable to share-holders.
Revenue and return on investment is a valid concern to bring up in this whole GenAI shebang; demand is not.