Railroads, semiconductors, plastics, networking... the utility was there for all of them, and so was the potential profit.

Everybody knew it.

But some investors don't have the patience for these "sure things" to mature into their commercial destiny and others know they can siphon off a killing by taking advantage of them as they speculate.

These bubbles aren't about potential, they're about timing.

And today's AI, for as revolutionary as it may be, is taking just as long to mature as anything in the past.

Most of the top players involved in AI right now are going to be rich. And in 20 years, the world is going to involve a lot of AI in soooo many things. But a lot of shirts are going to be lost below those top players and a lot of companies are going to fold because infrastructure, refinement, and integration take time while the FOMO speculation starts as soon as the big discovery is recognized.

I'm not imaginative enough to see more use cases and who will pay. You can burn a lot of tokens and dollars on math proofs. Same for white hats finding vulnerabilities in all the software. Generating video.

Personal assistants dealing with your email, filling out paperwork, and booking reservations don't use a lot of tokens.

If every software developer paid $200/month, every academic paid what they pay for Matlab or Mathematica licenses, every YouTuber paid for whatever video processing, and every normal person paid a subscription comparable to their TV subscriptions and cell phone plans - does that justify the valuations?

The government pays for surveillance? Companies pay for customer service replacements and target advertisements?

It seems like there are a few small categories that use a lot of tokens, and a large category that doesn't need many at all.

Im not convinced by the claims of infrastructure only being expensive to build initially. Hardware doesn't last forever especially in a data center, maintenance isn't free, electricity is not going to get significantly cheaper. If models get more efficient we won't need super expensive and expansive hardware build outs, if models keep getting more powerful and needy and are hardware limited, each new hardware generation will stomp over all this expensive and soon to be old hardware in electrical efficiency requiring another massive round of funding that players already holding debt will struggle to afford.

I dont know if the valuations make sense, but the usability is all there and so are the potential profits. Over a decade, that's probably all that matters. If the valuations pop or dip (anytime soon), I think that's mostly irrelevant. I get that the press probably doesn't like to hear this boring conclusion.

P.S: A Matlab/Physics simulation guy running for a Liberal party seat in Canada? Say more!

Big red flags that I think point the other way:

- anthropic IPO repricing

- pareto frontier gap decreasing by the month between open and closed models

- SpaceX disappoinment

- enterprise buyers as main consumers of closed tokens are being displaced by OS competition for pennies

- job loss and entry level hiring collapse

- massive discounts of current data center contract debt

- consumer open weights model efficiency improving constantly

- the Chinese arms race

- a possible rapid downward spiral that may force governments to step in and subsidize

Am I missing anything?

If you don't talk about competition from DeepSeek you haven't really thought it through all the way. You might argue it's like Windows vs Linux, but operating systems have huge natural motes. Any person can just switch to a provider of an open weight model instantly. Most people don't know about it but we may very well see people learn about this broadly in the next few years. Changing models is not super complicated. Anthropic is unlikely to make $2 to the dollar when competitors are taking only pennies of profit.

Unless I misread it, this article simply doesn’t mention training or the cost of it.

so many variables here. Do anthropic and openai as "AI" companies last longer term? If LLMs curve off in terms of what they can do, and local hardware becomes capable of running local models, seems like they won't last that long. But if they keep improving such that massive amounts of compute will always be needed beyond what can be done locally? Then sure. But then does it just become a commodity market where all the margins get stripped right down? Do they invent AI tech well beyond what LLMs are capable of at the moment? I would imagine, no matter which way it goes, hardware companies will win.

The only modification I'd make is to amortize the investments over 5-6 years instead of 20 because most of the cost is GPUs not the buildings. This increases the required revenue by 4x.

I like the sentiment, but the author doesn't appear to be accounting for some harsh truths:

- Anthropic is already expected to have junk bond status; this is going to make dealing with their existing debt rough while costs likely continue to rise

- Datacenters are 'cheap' once they come online, but that assumes they will. Power infrastructure hasn't been able to keep up, and several pending datacenters (I've seen estimates in the 50% range) meant for AI growth have been significantly delayed because of it.

- The US has a lot of debt coming up in 2028. The AI investments have been far more lucrative than the traditional 30-year bond. The AI bubble doesn't have to pop at all for the global market to plunge.

Just because a technology is going to be successful in the future doesn't mean that the current beliefs are accurate of which company is going to capture the most profits from that technology.

The internet is successful and cisco is having a blast but its valuation has still been enormously wrong during the dotcom bubble. Same goes for pets.com, etc.

So in other words, maybe the valuation of some companies is totally wrong. Maybe Anthropic is not worth two trillion, or even a hundred billion, but Nvidia is worth 20 trillion. Maybe it's the other way around. Maybe the legal framework changes and the value will be captured by the major rights holders, reddit, twitter, bertelsmann, etc.

>Anthropic's S-1 filing says that they make $2.08 for every $1 of compute. In other words, once you ignore the cost of building infrastructure, AI is very profitable.

If you ignore the cost of building cars, they are also very profitable.

>Profits Can Grow, By A Lot

They can also decline by a lot, and Anthropic's S-1 suggest that is what is happening, as their losses are widening, not narrowing.

>Google Has No Moat, But Neither Does McDonald's

That's why no one is sinking several trillion dollars into a new fast food chain.

>Alphabet, Meta, and NVIDIA are all AI companies that have seen their market capitalization explode over the past few years, but all of them have stable P/E ratios in their 20s.

The "E" in their PE ratios is circular revenue that is ultimately derived from debt and equity, not real end-user demand from profitable companies. For some of these bubble companies, if you subtract the debt-fueled private stimulus money, their actual PE ratios skyrocket.

Meta, I have constructive feedback on your choice of titles with this post https://news.ycombinator.com/item?id=50415422

There are very few people in the world where when they declare that they have an opinion on it, that the declaration itself is title worthy.

The 16% yield on Coreweave bonds probably indicates otherwise.

It's more accurate to say that there's an OpenAI-Anthropic-X bubble. Financially sustainable investment in LLMs is useful and not going anywhere, as China shows. Dumping trillions of dollars into companies that make models that are 1.2x better than Chinese models at 100~1000x the cost, ehhh... good luck with that.

"If you check any online discussion about the financial situation of the AI industry, it's essentially taken for granted that the bubble exists and is going to pop any day now."

-------------

If everyone, or even the majority, believed that there is a bubble that's going to pop with near certainty, that would tank stock prices immediately. Why would anyone hold a stock they know is going to go down precipitously? If the majority of people know it's a bubble, the bubble immediately pops. AI stocks still have worth, so most people believe there is no bubble or that prices will go up before going down.

People talk about bubbles. They worry about bubbles. For the most part, though, they go on investing as though there isn't going to be a bubble. Every bubble looked like a solid investment to most people right up until it burst, or it wouldn't have been a bubble.

So, no, most people do not think AI is a bubble. That doesn't necessarily it's not though.

> More than anything, I think the supposed AI bubble has become such a large talking point because it represents the hope that things can go back to how they used to be. People are afraid of what's going to happen with AI, and rightfully so.

> So, people wishcast. They tell themselves that this is all a giant bubble, and one day soon, everything will crash down and immediately go back to how it used to be.

+1 to this. I think this is why Ed Zitron gets so many readers - people want someone to tell them things will go back to “normal” someday.

I think the biggest problem is people are conflating current AI being useful with current AI companies being financially viable. Dot com bubble had its winners and losers but the biggest thing is that many of the current AI companies are valued at prices the winners were decades after the dot com bubble. My prediction the big 3 infrastructure AMZ, MSFT, GOOG will lead openai and anthropic to a point where they owe them trillions in payments and use it to take them over.

Meta’s margins are apparently getting crushed as a result of AI investments.

The lack of a clearly profitable operating model and huge (trillions) in commitments for buildout is what concerns people.

I am not convinced by this person who is not convinced there is a bubble. The bubble, by the way, specifically refers to the valuations. Is Anthropic worth 1.2 trillion when it’s not clear they will have positive cash flow in the foreseeable future?

The discussion of the “AI bubble” often conflates two different things: (1) is AI going to justify the valuations we are seeing? and (2) are the specific AI companies we have going to justify their own valuations.

The rapid progress of multiple closed frontier models, along with the rapid progress of open models, suggests that LLMs will be like electric motors, not like social media. Are electric motors worth a huge amount of money economically? Sure. But none of the companies who invented electric motors are especially valuable today, because the technology became a commodity.

A fair critique. Even I, someone who started as a (righteous) angry doomer over it, have come around for the most part.

My viewpoint also shifted around the shape of the bubble. The technology isn't going away, obviously, but the valuations of these companies like OpenAI and Anthropic feels divorced from reality. Inference continues to go down, most folks don't need frontier models for common tasks (including coding), and local models provide a competitive edge in several domains the frontier labs cannot (namely value and privacy). Combined with demand still largely subsidized and the companies being deeply unprofitable, and I just don't see the investments in Anthropic or OpenAI or the sort actually paying off. That is the bubble I'm concerned about, not the tech itself.

...now when the debts get written off and all this compute is just sitting around idle, available for bottom-dollar prices to try and eke out any sort of ROI for whichever creditor(s) inherit the assets? That's going to be pretty cool times.

Large data centers never made sense. If an additional pc with a graphics card was put into every home, we wouldn't need power grid upgrades. Our power grid is designed around human distribution i.e. homes. Large data centers cherry pick where it may be possible to quickly connect power connections up. Data centers need to secure their power connections before the utility rate hikes on everyone else generate public opposition.

If large data centers cannot secure free power connections paid for by everyone else, they cannot make any of this profitable. The whole thing was a scam from the start. This is why cloud AI companies bought up so much pc and server hardware. Artificial scarcity was the only way to slow down local llm adoption and sell the false narrative that cloud AI has value.

Plucking a graphics card out of every home and centralizing the cards to a handful of large data centers that require a trillion dollars in power grid upgrades is an idea so dumb, we should all be laughing at it. They even have to use active cooling or evaporate drinking water instead of free air cooling. The consumer doesn't benefit in any way from this. Consumers would essentially be paying more just to be datamined.

LLMs are not a bubble, large data centers are a bubble. Look at how large data centers are now the first target in any war. A graphics card in every home, doesn't give someone a concentrated target. National security makes large data centers extremely bad.