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The AI bubble is popping; we just don't know it yet

theregister.com

121–130 of 154 posts

Re: The AI bubble is popping; we just don't know it yet

#121

> The same thing happened with their massive investment in Anthropic. They accounted for $53.4 billion due to deals with Anthropic last quarter. He said if you follow one Anthropic dollar through the earnings release, it's counted in AI business revenue, chips business, and AWS segment revenue. That is insane if that is true, is that even legal?

There's a bit of Chinese whispers happening here. If you read the original piece they're talking about -- https://www.theregister.com/paas-and-iaas/2026/07/31/amazon-... (definitely worth a read, it's hilarious) -- you'll realize it means that that Anthropic dollar is "counted" multiple times in the marketing of three different Amazon businesses.

As far as accounting of revenue is concerned, it would have been counted as appropriate. Else, like you, I would guess it's not very legal.

Re: The AI bubble is popping; we just don't know it yet

#122
post #12

Outside a relatively small world of circular investment and FOMO feeding FOMO the general consensus seems to be “let it burn.” It appears very unlikely we will ever see an IPO of OpenAI. Anthropic appears less doomed, but still iffy at best. Tons of other large, but little discussed, AI startups are just dead-companies-walking at this point. The likes of AWS are showing good headline numbers but are taking out massiv…

Anthropic is almost purely a model company. They own close to no data centers. If models are becoming commodities, and the main bottleneck is actually serving them at scale, Anthropic does not appear particularly well positioned. If AWS had a ~60-80% margin for decades, I see no reason why inference can't have a ~60-80% margin for quite some time. The problem is, if costs continue to drop ~90% for the same level of q…

> If models are becoming commodities, and the main bottleneck is actually serving them at scale, Anthropic does not appear particularly well positioned.

That has been my thesis ever since Dario went on about how difficult it is to forecast capacity on the Dwarkesh podcast right about the time Claude started having 9's comparable to GitHub's.

Even as an outsider, seeing all the cloud providers bemoan their lack of capacity and their growing backlogs, I could tell compute capacity was already the biggest constraint on industry growth and that it would be very hard to come by in the future... which also probably made it the only moat.

And now we see Anthropic making very expensive deals with competitors to secure the necessary capacity. Claude likely still has enough momentum to make it worthwhile. But I can't believe Dario, probably the most AI-pilled of them all, would under-estimate demand so severely.

Re: The AI bubble is popping; we just don't know it yet

#123
> If you look at most big tech earnings this quarter, with the exception of Amazon, almost all others lost significant value after reporting. Microsoft, Alphabet, Meta, and Apple did.

Microsoft spiked on earnings, and is now actually about ~24% above it's pre-earning level.

Alphabet did lose about 7% the day of the earnings, but it recovered and now, after MSFT earnings, is actually 9% above the pre-earnings level.

Meta dropped 10% on earnings but is now back to its pre-earnings level.

Apple dropped ~10% and has not recovered (yet) but it's also famously "sitting out the AI bubble", so not sure why it's included here other than a "tech stock that went down."

Oracle has been dropping forever but after Microsoft's earnings it's climbing again.

If you zoom out, the stories change, and as you keep zooming out, they keep changing all over again.

My point is, 1) reading stocks in isolation is like reading tea leaves, and 2) if you want to point to any stocks, you should make sure they support your narrative.

Re: The AI bubble is popping; we just don't know it yet

#124
post #115

Earlier quoted context omitted.

Anthropic is almost purely a model company. They own close to no data centers. If models are becoming commodities, and the main bottleneck is actually serving them at scale, Anthropic does not appear particularly well positioned. If AWS had a ~60-80% margin for decades, I see no reason why inference can't have a ~60-80% margin for quite some time. The problem is, if costs continue to drop ~90% for the same level of q…

> I see no reason why inference can't have a ~60-80% margin for quite some time. Same as anything with low margin: Viable competition and low switching costs. Many sysadmins lazily do 100% AWS because they don't know any alternatives. CFO's might enforce using more economical inference providers if the cost is even 10% less.

> Same as anything with low margin: Viable competition and low switching costs.

So why didn't this happen to AWS?

Re: The AI bubble is popping; we just don't know it yet

#125

Earlier quoted context omitted.

If a fruit company developed fruit that was cheaper but people ended up buying more fruits, would you then call fruits more expensive or more cheap? I assume cheap. Then why would you call AI more expensive?

I think you're arguing with the wrong person. Please note what I actually said: > This is poorly stated in the podcast, but the underlying point is correct: while cost-per-token is going down, overall token use is way up. This is causing the cost of using LLMs in corporations to skyrocket.

> If the model consumes four times as many tokens to deliver a result, it’s not cheaper

This is literally what the guy says in podcast. So the underlying point is not correct. He’s specifically talking about per task cost. There’s no “but actually they meant something else”.

I don’t discount your point about overall cost increasing but that’s not relevant here.

Let’s agree that the podcast is fundamentally wrong in their main claim.

I want to show that the podcasters should be discredited because they don’t understand a fundamental aspect of the economics so you can’t trust the main thesis.

Re: The AI bubble is popping; we just don't know it yet

#126
post #115

Earlier quoted context omitted.

> I see no reason why inference can't have a ~60-80% margin for quite some time. Same as anything with low margin: Viable competition and low switching costs. Many sysadmins lazily do 100% AWS because they don't know any alternatives. CFO's might enforce using more economical inference providers if the cost is even 10% less.

> Same as anything with low margin: Viable competition and low switching costs. So why didn't this happen to AWS?

High switching cost.

Re: The AI bubble is popping; we just don't know it yet

#127

Earlier quoted context omitted.

> We don't have sci-fi AI Current frontier models are absolutely sci-fi AI by any measure that existed up until the late 2010s. If you showed a current frontier agentic AI, with bidirectional speech, tool use etc. to a person from 2010, they'd say it can't be real, there must be a person inside that mechanical turk.

> Current frontier models are absolutely sci-fi AI by any measure that existed up until the late 2010s. Sci-fi is Lt. Cmdr. Data, HAL, Skynet, Culture Minds... > Current frontier models are absolutely sci-fi AI by any measure that existed up until the late 2010s. If you showed a current frontier agentic AI, with bidirectional speech, tool use etc. to a person from 2010, they'd say it can't be real, there must be a pe…

>Sci-fi is Lt. Cmdr. Data, HAL, Skynet, Culture Minds...

The current state of things is closer (not close to by a long shot) to Fred Pohl's "AI" programs from his novel Gateway[0] than it is to the above examples.

But even those are decades (at least) beyond what we have now. What we have now is the foreseeable (from at least 30 or 40 years ago) evolution of what was once called "expert systems."[1]

[0] https://en.wikipedia.org/wiki/Gateway_(novel)

[1] https://en.wikipedia.org/wiki/Expert_system

Re: The AI bubble is popping; we just don't know it yet

#128

Earlier quoted context omitted.

> Current frontier models are absolutely sci-fi AI by any measure that existed up until the late 2010s. Sci-fi is Lt. Cmdr. Data, HAL, Skynet, Culture Minds... > Current frontier models are absolutely sci-fi AI by any measure that existed up until the late 2010s. If you showed a current frontier agentic AI, with bidirectional speech, tool use etc. to a person from 2010, they'd say it can't be real, there must be a pe…

>Sci-fi is Lt. Cmdr. Data, HAL, Skynet, Culture Minds... The current state of things is closer (not close to by a long shot) to Fred Pohl's "AI" programs from his novel Gateway [0] than it is to the above examples. But even those are decades (at least) beyond what we have now. What we have now is the foreseeable (from at least 30 or 40 years ago) evolution of what was once called "expert systems."[1] [0] https://en.w…

How was it foreseeable? Expert systems worked on quite different principles. Knowledge representation, expert interviews, ontologies etc.

Re: The AI bubble is popping; we just don't know it yet

#129
post #77
post #43

Earlier quoted context omitted.

What it we would prefer that there were not other people in our homes for interpersonal reasons?

All robotic home appliances will feature cameras with which people will be watching you and microphones with which people will be listening to you, all the time, forever.

Sounds false

Re: The AI bubble is popping; we just don't know it yet

#130
post #27

Earlier quoted context omitted.

It's holding up the entire US stock market and therefore the entire US economy and the dollar value. You probably don't want this particular Atlas to shrug.

I would rather be market-corrected out of a job for a few weeks or months than have this inflate into an economy-wrecking bubble that derails my career and life for years. I'm worried that we're at that state already...

The thing about the past is that it's the past. Things change, big changes do not bring back the past. They change things.

If you are market-corrected out of a job that situation most software engineers will be out of a job for years and wages will not recover for decades, or just never.

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