"First, although core firms in the AI ecosystem have been profitable so far—easing pressure on AI-related equity valuations—weaker or less durable investment and profitability in AI could trigger a correction"
Is that correct - that the AI firms have been "profitable"?
[1] https://www.imf.org/-/media/files/publications/gfsr/2026/oct...
Although Anthropic supposedly has a good margin on each token, so the inference is substantially less expensive than what they charge customers. Training is eating into that.
Genuine question: why are people still saying the plans are heavily subsidised?
https://news.ycombinator.com/item?id=49698936
I haven't digged myself but many people have argued that Anthropic used accounting tricks to appear profitable to investors, but they removed some costs from their calculation.
I think the message to investors is that operating the model is profitable. Like the income they get from paying customers pays for the infrastructure of running the models.
"Hyperscalers have strong earnings from their core businesses. Yet, free cash flows are rapidly declining as hyperscalers try to sustain large AI investment needs, leaving debt financing increasingly necessary"
On the one hand it's treated like an open secret that we're nearing the end of an AI bubble that even the IMF is flagging as a risk as reality doesn't live up to the hype.
On the other hand the capability of systems in just the last two months has improved so much that it feels like the average hype undersells what's happening right now but that knowledge is extremely unequally distributed as the greatest capabilities are most familiar to software engineers that have fully embraced agentic coding, which even earlier this year was still somewhat questionable but now is too highly productive to avoid.
The question I have is if everyone is this bearish on AI stocks are they not more likely than not to move against consensus much higher?
The “it’s dangerous, regulate us please” angle as an out for explaining terrible financial performance doesn’t seem to be working. The final Hail Mary pass is the “if we fail you fail” play.
However all data indicates the risk here is fairly concentrated in private markets. It will be painful but it’s unlikely to take the whole economy out with it. Some VCs are in for a world of hurt and private credit markets will lose their shirts, but the average person would see limited direct impact.
With everything going on in the datacenter space a bailout for AI seems incredibly unlikely. The general sentiment amongst the masses seems to be “let it burn.”
The question is, if this happens then how do you incentivise more R and D? Which investor would invest without the returns?
Edit: not surprisingly people don’t understand the point.
Would you rather NVIDIA and OpenAI get rich and capture the value or the public? Such a strange thing to see people rooting for the big companies.
nice place you got here, be a shame if something happened to it....
People have been saying this every month since 2022 lol
[1] https://x.com/karpathy/status/2109361546505966046?s=20
[2] https://www.businessinsider.com/minecraft-creator-markus-per...
As you pointed out, reality does live up to the hype.
Pessimists argue that the large investments into data centers are unreasonably high and that this debt is going to bankrupt AI labs.
However, as of yet the demand is there and the data centers are fully utilized.
We can see that currently OpenAI is struggling to serve their inference.
Inference speed on 6.1 Sol went to like 20-30 tokens per second and it frequently fails with the "model at capacity" error.
It's imo a bit too early to state with any confidence that there will be a crash. It seems dependent on the development of AI capabilities, resulting demand, and compute requirements.
It feels so good, that you forget that this is just a holiday.
But at the same time it is absolutely real, you're experiencing it, other people at the resort are experiencing it (though maybe not at a similar level as you).
You love it so much you start planning with your partner about which school the kids should go to. You start planning your whole life in this paradise.
The problem is that private credit agencies also asked for loans from banks and therefore they are exposed to this as well. I believe the current estimate is that 11% of outstanding loans from the big 4 US banks were issues to private credit firms which then very likely lent themselves to the AI industry complex.
Additionally, by the Fed's own admission, they will never let another "Great Depression" happen again. So they intervened in 2008 and they will intervene again by buying up those worthless assets. And the average person will see their savings real value plummet without even mentioning that a lot of private credits come from pension funds...
Finally, if private credit really goes belly up, private investors will likely lose a good portion of their purchasing power, meaning that the economy will at best correct and at worst crash only because of that. And this effect will be in addition to the AI economy grinding to a halt which will already hit the worldwide economy HARD (also IMHO).
A reckoning is coming. I believe the "let it burn" is not doable as it will take a few banks and the economy with it. A more measured slow bleed with the Fed printing money to buy these junk assets will be more likely.
Some banks will suffer losses but there isn’t data to say the banks will fail en mass. This is bad, but not 2008 bad in so far as the stability of the financial system.
They will walk out only rich rather then super rich. They will talk about it as if they were poor, but nope, they will still have toms of power and money.
AI is here to stay, but the market needs a big forest fire to wipe most things out. A few strong plants survive to build a better future.
It’s a cycle that keeps repeating, and we’re overdue for a big forest fire in tech.
No... This is not accurate at all. AI valuations are based on high future growth. Prices could stay the same but growth slows and that could cause a crash by itself.
TSLA should have crashed by now, but the hype just keeps on coming. Eventually reality will set in, but the market can remain irrational for longer than you can remain solvent. Big AI may be like that.
Why is this controversial?
Its like a gold rush where half of the picks are sitting in storage because there are not enough miners to wield them.
If a crash unlocks capital and eases the compute price squeeze, it might be worth the pain.
[1] https://www.tradingview.com/news/seekingalpha:bce1fc46a094b:...
The 11% I mentioned above is the verifiable exposure for banks. It could be a much much higher number and at a time where delinquencies on all sorts of debts are historically high that for sure doesn't bode well.
The money printing that the Fed would do to fix this would be gigantic (several Trillion dollars basically) and on the same scale as the covid intervention which sent inflation to 9+%. And we are already waiting for the oil shock to spread to everything else.
Yeah, the financial system might survive, but the pensions, savings, ... will be fucked up.
When you max out your Claude Max plan every billing period, are you consuming more tokens than you could realistically pay for with the same money spent on API inference? Definitely! This works because many Claude Max subscribers don't use it to the max (and you probably aren't using it to the max every single time either), so overall subscriptions might still be profitable. Technically, the subscribers subsidize each other, but this is entirely sustainable (see any other subscription model that is based on its consumers not maximizing their usage, e.g. gyms).
What people mean (or want to say) when they say inference is subsidized is that it is subsidized in an unsustainable way (e.g. with investments that will not last forever - if this is true at scale it should worry us!). What happens now is that they take the fact that an individual subscription used to the max by itself is a financial drain for the company offering it, attach the "subsidized" term to it, and infer from that a bunch of stuff that is usually associated with the term (such as unsustainability) but doesn't really apply here.
OpenAI released an AI video app to the masses for free, made a bunch of promises, and then just shut it down.
So there’s a growing body of evidence that while neither of these are in great financial shape, Anthropic looks to be the more disciplined of the two.
OpenAI released an AI video app to the masses for free and then just shut it down.
So there’s a growing body of evidence that while neither of these are in great financial shape, Anthropic looks to be the more disciplined of the two.
Some people then assume that this price means the subscriptions are deeply unprofitable at least for users that make heavy use of their usage limit.
If you look at estimates based on serving Kimi K3, margins at API pricing must be well north of 95%.
And that's assuming frontier labs don't serve inference more efficiently than Kimi K3.
I believe most people dramatically overestimate the inference costs.
It doesn't help that in many discussions about profitability, people mix many different metrics, including other costs like R&D.
Short of an emergency rate hike to 10%, nothing stops this bubble.
That's quite the framing. I'd say the trajectory count way more than how productive you are to follow it in assessing someone is good.
There has to be a name for this fallacy.
You fundamentally believe that AI is useless and that it wastes energy and hardware. Shouldn't you then want the bubble to burst even faster? If not, you are just delaying the bubble.. but to what end? So that you personally won't be affected? This is a morally bankrupt stance to take.
My ideology is at least more coherent in this context. I think AI is useful, and AI being cheaper for the masses is good for them rather than the value being captured by a few companies.