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.
Humans living forever is inevitable. Galactic colonization, inevitable. Over a long-enough time scale.
AI is inevitable on the same time scale, sure. But can it actually survive as a sustainable business given what is needed to keep it relevant—will people pay what it costs to support said business—not clear. Or, at least in the next five years.
The second generation AI companies will be built on different assumptions and will likely be slower-growing, and that’s when you’ll see it truly become ubiquitous. That could be a decade though.
is anyone else weirded out by folks chanting this like a mantra? imagine saying this for any other emergent tech. "NFTs are inevitable", "crypto is inevitable", "excel is inevitable", etc.
Your point is a good one, but it's constructed upon the premise that AI is a single discovery or invention or even a single tech wave.
AI is bigger than the Industrial Revolution, the Internet, than computers, than literally any innovation or invention that has ever come before, combined.
Today you see AI slop and vibe coding.
Tomorrow, all of humanity will be affected, forever.
Everything about the way that we learn, that we think, and that we invent will be changed forever.
We're discussing AI in general here, not individual companies (and none of those companies have a monopoly). Nobody's arguing that AI wouldn't exist if the previous revolutions hadn't occurred.
This reads less like a bulwark against sensationalism and more like an attempt to remain ideologically safe in what appears from many angles to be an extremely steep exponential start of what we can probably agree is an S-curve.
> And today's AI, for as revolutionary as it may be, is taking just as long to mature as anything in the past.
I suspect this opinion may come across as naive for the myriad software engineers whose job has become pressing the enter key. Your point about timing is based on solid principles, but I don't think your comment contains a satisfactory argument that the timing is incorrect.
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.
The current-gen hardware is expected to have only 2-3 years of useful life. New tech, and especially new architecture is going to make inference much faster and more efficient in the near future, and the big vendors are going to be more limited by datacenter floor space and power/cooling, so that the hardware will be replaced very quickly by better models.
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!
In 2007, It was regular people who lost their homes and their leveraged investment properties. Regular people are not leveraged into AI startups today. If the AI bubble pops, regular feel people will feel the direct financial consequences significantly less than the '07 housing crisis.
> Regular people are not leveraged into AI startups today
this isn't accurate. as an example, anyone with a 401k will be affected by the stock market and the stock market is mostly tech, and tech has bet the house on ai
"Your 401k should never go down at all" is not a realistic expectation.
Hopefully, people who need to pull from their 401k's soon have wound down to less risky positions. 401k exposure is just not the same thing as your house valuation tanking.
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.
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.
The assumption here is that having "the best" model is not worth that much of a premium over a "good enough" model at a lower price. This remains to be seen, though, and people's behaviour paying for Claude Code and Codex suggests at least for now people are willing to pay.
>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.
Sorry what? There are 10x if not more Linux installation vs Windows installation in the world. Linux powers everything, including billions of smartphones, where Windows is nowhere to be seen. Same for routers. And actual proper servers.
If it's like Windows vs Linux it means open-weight models are going to be incredibly more successful and touch just about everything. All the while being cheaper and working not a bit but much better.
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.
"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 an 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.
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?
>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.
sounds pretty good. if I made 2.08 for every dollar of my spend I would make more money. Plenty of businesses operate on much much thinner margins, and thats not utility-like at all.
That’s 52% gross margin. Not much higher than the overall S&P 500. If you break it down by sector, Real Estate, Health are, Financials (and of course Tech overall) have higher gross margins at the sector level.
It's damning that out of the only two companies in the world that absolutely must dogfood Anthropic's products, one of them, the investment bank behind Anthropic's IPO (Goldman Sachs), didn't find enough of a use case for to justify its continued use by most of the bank. Now LLM use is heavily restricted to specific departments and even in those departments spend must be approved. They've also repeatedly dropped the IPO target by almost half in just 4 weeks. That's WeWork levels of adjustment right there.
It's almost as if they know something about the finances that the rest of us don't...
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.
Im in China, and scared. Everyone is broke, losing their jobs while on the other hand there are these giant datacenter campuses being build in the warmest and most remote places. if the bubble bursts (there is 1000% a bubble, its the same like mass maker and innovation, sharing bikes and now ai policies)… it will be bigger than any financial crisis before. The only shit I see coming out of ai hackathons and competitions here is ai tools for marketing (ai). The rest is ai slop microdramas.
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.
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.
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.
Well, if you buy a bunch of GPUs and don't have buildings to put them in (a very real situation right now), then you're just .... holding hardware and not making a return off it and *the building (and related power infrastructure)* becomes much more important than how many GPUs you have.
> 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 am pretty sure the biggest thing in question is if OpenAI and Anthropic are as valuable as they say they are vs any other AI labs. I guess we will see, but I still feel it doesn’t take many ex-employees from them to build something that can wrestle them, and also it’s weird seeing other players that also have comparable AI models (Alphabet, Meta, whatever company owns Grok these days, …) do not get as much in value. There is also the “Can local models disrupt this?” question (and the Chinese labs), and there is also the question of hardware availability (will some player change this?).
I feel the projected value of both OpenAI and Anthropic requires that nothing changes in a space of technology where things seems to change a lot and reasonably suddenly.
No, no one believes that. Everyone can see that AI is going to change how many industries work completely. The parent is constructing a strawman argument "the reasoning is motivated and that motivation is nostalgia (or similar)".
Yes, quite a few people believe AI is a big scam and it’s not actually good for anything.
I know this might seem crazy to software developers who handed all their dev work over to Claude 6 months ago. But most people are not software developers.
-1 to this. I think this is why Ed Zitron gets under the skin of AI evangelicals. They want everyone on this surrealist funny bus on a journey to whatever-the-fuck. Fingers crossed! Ignore the weird AF obfuscated financials. Ignore the crippled hardware market for everyone except data centre overlords. Nothing to see here!
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.
Large data centers are dramatically more efficient at utilizing both the power and the hardware.
At it's core, running a top-tier LLM means linear load of trillion+ weights from RAM for every token. The cost of this operation absolutely dwarfs the cost of doing the actual math. If you are only serving a single user, you can only amortize this over a handful of token streams, times like 2-4 for speculative decoding. If you are running in a datacenter, you can batch thousands of streams, and get correspondingly much more tokens out of the same expenditure of energy and hardware.
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.
We should call it the "AI timing bubble" because AI is inevitable.
The gambling around which companies, products, etc. is just the imperfect information and greed directing investment.
It's not malinvestment for the winners.
Timing is all that matters here.
Humans living forever is inevitable. Galactic colonization, inevitable. Over a long-enough time scale.
AI is inevitable on the same time scale, sure. But can it actually survive as a sustainable business given what is needed to keep it relevant—will people pay what it costs to support said business—not clear. Or, at least in the next five years.
The second generation AI companies will be built on different assumptions and will likely be slower-growing, and that’s when you’ll see it truly become ubiquitous. That could be a decade though.
> because AI is inevitable.
is anyone else weirded out by folks chanting this like a mantra? imagine saying this for any other emergent tech. "NFTs are inevitable", "crypto is inevitable", "excel is inevitable", etc.
inevitability != usefulness/profitability
Yes, you are not alone. It's a religious-like ferver that is downright disturbing.
NFTs and crypto had little to no use outside of their niche.
Excel was inevitable. How many trillions of hours has it saved?
AI is going to let me do your job and barely lift a finger. Therefore, inevitable.
These are thermodynamically favored technological outcomes.
Your point is a good one, but it's constructed upon the premise that AI is a single discovery or invention or even a single tech wave.
AI is bigger than the Industrial Revolution, the Internet, than computers, than literally any innovation or invention that has ever come before, combined.
Today you see AI slop and vibe coding.
Tomorrow, all of humanity will be affected, forever.
Everything about the way that we learn, that we think, and that we invent will be changed forever.
AI wouldn’t work without any of that above stuff though.
Their monopolies got broken and the profits disappear in a commodity market.
If nvidia or tsmc got split up i doubt its stock is going to stay at as a high a p/e.
We're discussing AI in general here, not individual companies (and none of those companies have a monopoly). Nobody's arguing that AI wouldn't exist if the previous revolutions hadn't occurred.
I know where you're coming from, but we probably should not be talking about AI in this way. I don't think it's helping or serving its purpose.
I think civilization will have time to react and adapt, panic leads to haphazard action, we need deliberate consistent action.
This is exactly the kind of talk that led to all the other bubbles. Amazing how infected people get.
That's a fair point, but tulips are not AI.
This reads less like a bulwark against sensationalism and more like an attempt to remain ideologically safe in what appears from many angles to be an extremely steep exponential start of what we can probably agree is an S-curve.
> And today's AI, for as revolutionary as it may be, is taking just as long to mature as anything in the past.
I suspect this opinion may come across as naive for the myriad software engineers whose job has become pressing the enter key. Your point about timing is based on solid principles, but I don't think your comment contains a satisfactory argument that the timing is incorrect.
> appears from many angles to be an extremely steep exponential start of what we can probably agree is an S-curve.
In every bubble some say this. And it could be the exact same herd behavior (mentality) that creates a bubble.
Something something than you can remain solvent
The market can remain 3.14159...
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.
So much this.
The current-gen hardware is expected to have only 2-3 years of useful life. New tech, and especially new architecture is going to make inference much faster and more efficient in the near future, and the big vendors are going to be more limited by datacenter floor space and power/cooling, so that the hardware will be replaced very quickly by better models.
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?
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!
indeed, very happy to see scientifically minded folks running for office.
The usability and potential profits of housing were there in 2007 and 2008, too.
In 2007, It was regular people who lost their homes and their leveraged investment properties. Regular people are not leveraged into AI startups today. If the AI bubble pops, regular feel people will feel the direct financial consequences significantly less than the '07 housing crisis.
> Regular people are not leveraged into AI startups today
this isn't accurate. as an example, anyone with a 401k will be affected by the stock market and the stock market is mostly tech, and tech has bet the house on ai
"Your 401k should never go down at all" is not a realistic expectation.
Hopefully, people who need to pull from their 401k's soon have wound down to less risky positions. 401k exposure is just not the same thing as your house valuation tanking.
And the valuations made no sense in 10 yea....oh.
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.
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.
The assumption here is that having "the best" model is not worth that much of a premium over a "good enough" model at a lower price. This remains to be seen, though, and people's behaviour paying for Claude Code and Codex suggests at least for now people are willing to pay.
>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.
I mention this in the article...
> You might argue it's like Windows vs Linux ...
Sorry what? There are 10x if not more Linux installation vs Windows installation in the world. Linux powers everything, including billions of smartphones, where Windows is nowhere to be seen. Same for routers. And actual proper servers.
If it's like Windows vs Linux it means open-weight models are going to be incredibly more successful and touch just about everything. All the while being cheaper and working not a bit but much better.
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.
"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 an 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.
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?
>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.
> $2.08 for every $1 of compute.
sounds pretty good. if I made 2.08 for every dollar of my spend I would make more money. Plenty of businesses operate on much much thinner margins, and thats not utility-like at all.
That $1 of compute is not taking into account R&D spending, infrastructure, etc.
And that's their only revenue stream
That’s 52% gross margin. Not much higher than the overall S&P 500. If you break it down by sector, Real Estate, Health are, Financials (and of course Tech overall) have higher gross margins at the sector level.
It's damning that out of the only two companies in the world that absolutely must dogfood Anthropic's products, one of them, the investment bank behind Anthropic's IPO (Goldman Sachs), didn't find enough of a use case for to justify its continued use by most of the bank. Now LLM use is heavily restricted to specific departments and even in those departments spend must be approved. They've also repeatedly dropped the IPO target by almost half in just 4 weeks. That's WeWork levels of adjustment right there.
It's almost as if they know something about the finances that the rest of us don't...
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.
Yeah, this "just my opinion" humbragging style is an unfortunate antipattern.
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.
Im in China, and scared. Everyone is broke, losing their jobs while on the other hand there are these giant datacenter campuses being build in the warmest and most remote places. if the bubble bursts (there is 1000% a bubble, its the same like mass maker and innovation, sharing bikes and now ai policies)… it will be bigger than any financial crisis before. The only shit I see coming out of ai hackathons and competitions here is ai tools for marketing (ai). The rest is ai slop microdramas.
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.
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.
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.
Well, if you buy a bunch of GPUs and don't have buildings to put them in (a very real situation right now), then you're just .... holding hardware and not making a return off it and *the building (and related power infrastructure)* becomes much more important than how many GPUs you have.
> 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.
Do people believe that? If AI is indeed a giant bubble and indeed the bubble pops, do people believe that AI will just... disappear from society?
I am pretty sure the biggest thing in question is if OpenAI and Anthropic are as valuable as they say they are vs any other AI labs. I guess we will see, but I still feel it doesn’t take many ex-employees from them to build something that can wrestle them, and also it’s weird seeing other players that also have comparable AI models (Alphabet, Meta, whatever company owns Grok these days, …) do not get as much in value. There is also the “Can local models disrupt this?” question (and the Chinese labs), and there is also the question of hardware availability (will some player change this?).
I feel the projected value of both OpenAI and Anthropic requires that nothing changes in a space of technology where things seems to change a lot and reasonably suddenly.
No, no one believes that. Everyone can see that AI is going to change how many industries work completely. The parent is constructing a strawman argument "the reasoning is motivated and that motivation is nostalgia (or similar)".
Even Ed Zitron rarely talks about AI outside financials. I have no idea what OP is talking about.
I guess they mean as far as AI being this utopian cure all for the ills of the world that some might have us believe is coming, its BS?
Yes, quite a few people believe AI is a big scam and it’s not actually good for anything.
I know this might seem crazy to software developers who handed all their dev work over to Claude 6 months ago. But most people are not software developers.
-1 to this. I think this is why Ed Zitron gets under the skin of AI evangelicals. They want everyone on this surrealist funny bus on a journey to whatever-the-fuck. Fingers crossed! Ignore the weird AF obfuscated financials. Ignore the crippled hardware market for everyone except data centre overlords. Nothing to see here!
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.
Large data centers are dramatically more efficient at utilizing both the power and the hardware.
At it's core, running a top-tier LLM means linear load of trillion+ weights from RAM for every token. The cost of this operation absolutely dwarfs the cost of doing the actual math. If you are only serving a single user, you can only amortize this over a handful of token streams, times like 2-4 for speculative decoding. If you are running in a datacenter, you can batch thousands of streams, and get correspondingly much more tokens out of the same expenditure of energy and hardware.