14 ms·

How the AI Bubble Bursts

372 points by martinvol 6mo ago

deleted 6mo ago
[deleted]
256BitChris 6mo ago
I could see OpenAI hitting financial issues which triggers some media induced panic and for people to claim the AI bubble has popped. However, the core utility of the best AI (read: Anthropic's ATM, by miles), will still exist and be leveraged by those who have learned to use it well. I could also see the exponentially declining power requirements offsetting the exponential-but-slower rate of AI compute demand, which then renders a lot of unused capacity in these massive data centers. I think of it like the old mainframes in the 70s which would take an entire city block to run, and now we have the equivalent of millions, if not billions of them in our pockets.
- eieje 6mo ago
  It’s pretty much undeniable at this point that the sentiment has changed. About 2 months ago this place was unbearable - filled with doom and hype AI posts. I welcome the calming and eventual slow release of the bubble.
- baq 6mo ago
  Anthropic isn’t the best by any reasonable measure. They’re the best in some areas and get pwned in others. In general AI is very much like human intelligence in the regard that no two models are the same just like no two people are the same. IOW if you are a single model shop you might even not have any idea that you’re falling behind.
- cmrdporcupine 6mo ago
  The coming months are the reckoning in which the poor quality of the tooling and the safeguards around them become evident and hopefully eventually rectified. By which I mean the competent organizations are the ones that will come up with cultural and technical solutions to manage the quantity and quality of the code better. Others will suffer severe quality issues. Not because the "AI"s produce inherently inferior code but because the volume of the code is too high to manage review of, and to have good internal organizational knowledge of to manage the pages in the middle of the night when servers go down because of code nobody really understood. I produce masses of independent project work all day long in my spare time using these tools and they blow me away. But in the context of professional work on teams of other coworkers the results are difficult to reason about and often impossible to competently review and it's not clear the results are superior. ' IMHO companies that drink too deep from the well without caution could be burned badly. Aside: I hate to say it, but there is no sense in which Anthropic has the clearly better product than OpenAI at this point. I know Claude caught developer's hearts through the fall, but GPT5.4 is a more powerful, careful, and competent model for coding and Codex is a far less buggy and more performant TUI. For the last 3 months I've gone back and forth between the two and I always run anything written by Claude Opus 4.6 by myself and my coworkers through Codex for review and it is constantly finding severe correctness issues to the point where I simply won't subscribe to Anthropic's product anymore. On top of that, OpenAI provides far higher token limits. Even their $20 plan goes quite far. If I was just building crud websites, probably Claude Code would be fine, and it does indeed show more "initiative" and "imagination" but I've seen it build way too many race conditions and correctness issues to trust it or the work my coworkers make with it.
- _puk 6mo ago
  A lot of anthropic's recent improvements are coming from the task focus and improved orchestration around the models, not purely massive changes in the models themselves. This bodes well for us being at a point that even if the bubble burst, we'd still have usable AI going forward.
- jqpabc123 6mo ago
  I think of it like the old mainframes in the 70s I think this is a good comparison to current AI. billions of them in our pockets. AI in your pocket (but first on the desktop) is a real possibility.
monegator 6mo ago
> How this affects you? > checks list ... nope, nothing will either directly or indirectly affect me. Let it happen sooner, rather than later, and unleash the mobs at the tech bros that set the world on course to make everybody's life more miserable. We'll still be here to get the scrapped RAM and GPUs to train and infere local models thank you very much.
- coffeebeqn 6mo ago
  The current best models are already very capable of disrupting the job of millions of people. I don’t think a scenario where we just go back to pre-Claude Code exists and I’m sure the same models can be tuned for much of other white collar work at similar capability
  - eieje 6mo ago
    People keep saying this but nothing of the sort has happened. People continue to work, some proportion of the those working use LLM’s regularly. Enough time has passed that subjective statements about the future don’t pass muster. Look at the numbers - there has been no large scale lay offs since correcting for over hiring. Has hiring slowed down? Sure. However I’d wager most firms are finding it pretty difficult to think of projects to take that will generate positive NPV. If that’s the case why would they hire? Moreover the focus has returned to cash flows - not product based growth metrics. Which again re-inforces the point about project selection. Efficiency generated growth does not continue on forever - it’s short lived.
  - monegator 6mo ago
    might be: there is too much busy work as it is, but we need people to work in order to make money in order to spend it in order to keep the circus from going under. It's the circle of life Let me remind you that you are not paying the full price for the service and all the value of those company is out of thin air. More or less the premise of the article. *when* you will be asked the real price, we'll see if the company will prefer a human or a bot it can't pass blame to
general_reveal 6mo ago
HN is no longer a reliable place for the truth. Quite frankly, unless you are utterly self educated, you are terribly vulnerable to this place. At this rate, I’d almost prefer to talk on a private mailing list with vetted resumes.
- myspy 6mo ago
  Why?
  - general_reveal 6mo ago
    You have to be uneducated to even read an “AI is bubble article”. Anyone working this stuff knows how much more compute we need.
    - myspy 6mo ago
      Thanks for clearing this up, as I don't work in that area. Personally I'd say that it's a problem that prices of consumer goods go up that far to satisfy this part of the market. We could need a more sensible way to advance the technology.
      - user34283 6mo ago
        That problem seems to mostly impact teenage gamers who need more than 16 GB of memory and can't afford the extra $300. In my opinion this is incomparable to what we are seeing with agentic AI that is rapidly replacing handwriting code. I figure chances are AI is not going to stop here.
    - A_D_E_P_T 6mo ago
      Two things can be true at the same time: - AI is a genuinely transformative technology on par with the internet and on track to probably surpass the smartphone - The inflated valuations, the circular flows of money (or "money"), and the financial cup-shell game mean that the players of the game are all a few bad weeks away from catastrophe. This is, of course, nothing new for SV -- but the scale this time is new. Some believe it will soon collapse -- "bubble," thus.
elorant 6mo ago
I feel that even if the bubble bursts hardware prices will still take years to normalize. So no clear benefit for the average consumer here.
- baggachipz 6mo ago
  Consumers and retail investors will bear most of the brunt from this bubble. Even taxpayers, as the government will most likely bail out the "too big to fail" ai companies in the "race against China". All based on bullshit, hype, and greed.
jqpabc123 6mo ago
Another possibility not really addressed here --- local LLMs. AI on hardware you own and control --- instead of a metered service provider. In other words, a repeat of the "personal computing" revolution but this time focused on AI. TurboQuant could be a key step in this direction.
- netdevphoenix 6mo ago
  Local LLMs don't sound profitable at all for those building them. If you really wanted a SOTA model, you would be paying eye watering amounts to own it unless you got an open sourced one.
  - jqpabc123 6mo ago
    unless you got an open sourced one. Ding, ding, ding --- we have a winner. https://techstartups.com/2026/03/26/nvidia-backed-ai-startup-reflection-eyes-2-5b-round-at-25b-valuation-to-challenge-deepseek-meta-and-mistral/ https://techstartups.com/2026/03/26/nvidia-backed-ai-startup... https://tiiny.ai/ https://tiiny.ai/
- schnitzelstoat 6mo ago
  Yeah, I don't think local LLM's will keep up with what the massive corporations put out. But they might get to a level of performance where it just doesn't matter for most users. And people would prefer to run a model locally for 'free' (not counting the energy cost) rather than paying for an LLM subscription.
- zozbot234 6mo ago
  TurboQuant helps KV quantization which is not very relevant to local LLMs, since context size becomes most relevant when you run inference with large batches. For small-scale inference, weights dominate. (Even if you stream weights from SSD, you'll want to cache a sizeable fraction to get workable throughput, and that dominates your memory usage.)
franze 6mo ago
.... so what? the technology exists, the models exist. Even when the bubble bursts things will not go to the state "before AI". Even if model development would stop today (not the worst thing to happen) it would still be the most impactful invention since the printing press
- hk__2 6mo ago
  Yes, that’s what the author wrote in the second sentence of the post: "AI is here to stay."
- irusensei 6mo ago
  I guess the point is that without the hype subsiding it enshitification will ensue.
positron26 6mo ago
When will this concern farm end? Internet is ant-milling harder than a model gone psychotic on synthetic data. Call me when it's over. Back to the mines. The Vulkan only writes itself when prompted with well-conditioned problem statements.
nopinsight 6mo ago
> nobody is sure if even their metered pricing is profitable This is most likely wrong. Lab executives insist that serving tokens is profitable. It's the cost of training next-gen models that requires them to keep raising ever larger rounds. More importantly, many independent providers price tokens of open-weight models at a fraction of Anthropic's prices.
- sunaurus 6mo ago
  The point is that you can’t just serve tokens without also training the next models. It’s an inseparable part of your costs, so naturally you can’t be profitable unless the price you are charging ALSO covers training.
  - dash2 6mo ago
    Is that right? I think that you can serve tokens without training the next models. It would be bad strategy, but it would work. So it's an important question, are they covering their operating expenditure? If they are the business has legs (and it will be worth spending a lot to train the next models). If not, maybe not.
    - camdenreslink 6mo ago
      If a major model provider were to just halt progress on developing new and improved models, the open weight alternatives would catch up in a couple years. They would have a period of great margin, followed by possibly zero margin as enterprises move to free options. They would have to come up with a lot of great products around the inferior models to justify charging at that point.
      - leoc 6mo ago
        Also, an out-of-date model which doesn't know about last year's world events, hit songs and new JS libraries is a depreciating asset even before you consider low-cost competitors catching up. So you'd presumably have to do some training just to keep the model up to date at the current quality level (unless you completely give up and just sweat the assets). And on the other side of that coin: over the next few years, do the latest, biggest models continue to generate user-perceived real-world improvements sufficient to keep users wanting the latest and greatest?
syntheticmind 6mo ago
[flagged]
qoez 6mo ago
History doesn't have to repeat. There's barely anything else going on in terms of innovation, and AI is a real step function technology. We might be overspending but there's no way we're getting another AI winter like last time (remember last time investment in 90s AI had to compete for resources with the internet boom).
- hk__2 6mo ago
  Isn’t that covered at the top of the post? > AI is here to stay. If used right, chances are it will make us all more productive. That, on the other hand, does not mean it will be a good investment.
- lionkor 6mo ago
  > History doesn't have to repeat This is high up there on the list of things people say before, you know, it does
- joefourier 6mo ago
  The dotcom bubble burst and 26 years later we’re all hopelessly addicted to the internet and the top companies on the stock market are almost all what would have been called “dotcoms” then. The railroad bubble burst in 1846 not because trains were a dead end - passenger number would increase more than 10x in the UK in the following 50 years.
Chance-Device 6mo ago
From the beginning of this I’ve wondered the same question: how do these companies justify spending such massive amounts now (and 3 or 4 years ago) when software and hardware efficiencies will bring down the cost dramatically fairly soon? They basically decided that scaling at any cost was the way to go. This only works as a strategy if efficiency can’t work, not if you simply haven’t tried. Otherwise, a few breakthroughs and order of magnitude improvements and people are running equivalent models on their desktops, then their laptops, then their phones. Arguably the costs involved means that our existing hardware and software is simply non viable for what they were and are trying to do, and a few iterations later the money will simply have been wasted. If you consider funnelling everything to nvidia shareholders wasting it, which I do.
- mrob 6mo ago
  Because whoever wins the AI race (assuming they don't overshoot and trigger the hard takeoff scenario) becomes a living god. Everybody else becomes their slave, to be killed or exploited as they please. It's a risky gamble, but in the eyes of the participants the upside justifies it. If they don't go all in they're still exposed to all the downside risk but have no chance of winning. I don't expect hardware prices to go down unless the third option (economic collapse) happens before somebody triggers the dystopia/extinction option.
  - WarmWash 6mo ago
    Just to add some slight nuance but is an important distinction, They aren't all necessarily racing to be "god", some are racing to make sure someone else is not "god". If it weren't for Altman releasing ChatGPT, it's very likely that we would have markedly less powerful LLMs at our disposal right now. Deepmind and Anthropic were taking incredibly safe and conservative approaches towards transformers, but OAI broke the silent truce and forced a race.
- phito 6mo ago
  I think their current goal is to capture as much market as they can while they still have the best models, their only moat. Look at Anthropic, they are clearly trying to lock their users in their ecosystem by refusing to follow conventions (AGENT.md etc) and restricting their tools exclusively to their own services.
shubhamjain 6mo ago
> OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them with the more profitable corporate customers and software engineers. Their shopping feature flopped and they shut down Sora, both supposed to be revenue drivers. I don't think Sora ever thought of as a "revenue driver" considering how notoriously expensive and unpredictable video generation via inference is. OpenAI is just a repeat of Uber—minus the scandals—in a different decade. Uber got itself into tons of businesses related to transportation on the assumption that it would all be viable "one day." Same stuff that OpenAI is going. I would say, once the bubble bursts—which is likely, considering the geopolitical environment—OpenAI, Anthropic, and Alphabet are likely to be the winners, with a lot of small players at the tail end. Anthropic won over programmers and OpenAI on everyone else. For millions of people, AI = ChatGPT, so I would bet that OpenAI can still become profitable, once they cut down their expenses.
- JohnTHaller 6mo ago
  > minus the scandals Given the tech bros involved, we just don't know about them yet. Also was this comment generated using AI? Look at all the em dashes.
schnitzelstoat 6mo ago
It's a winner-takes-all market and everyone wants to be the next Google and not the next Lycos or AskJeeves etc. It'd be interesting to see what they spend all the money on though as we seem to be hitting diminishing returns and I'm not sure if the typical enterprise user really cares about small improvements on benchmarks. It seems like it'd probably be better to spend all that on marketing, free trials, exclusivity/bundle deals etc. ChatGPT already has a strong advantage there as it has so much brand recognition. I've seen lay people refer to all LLM's as ChatGPT like my grandparents did with Nintendo and all video game consoles.
- delecti 6mo ago
  I don't think it's winner-takes-all. Google is Google in 2026 because Lycos and AskJeeves were bad in comparison. The average user doesn't care whose LLM they're using because they're all close enough. It's hard to see past the bubble bursting, but I expect most people will use multiple of them depending on context (Copilot via the integration in windows, Gemini via Siri on their phone, etc), likely without paying.
- H8crilA 6mo ago
  Where to go next? I don't think anyone has gotten close to automating everyday PC usage, likely via screen capture and raw keyboard+mouse inputs. Imagine how much bigger would that market be than vibecoding.
  - wavemode 6mo ago
    tbh I don't think this use case is going to be as big as people seem to think there are a lot of reasons, but in brief - I think AI desktop use is a product that the average person isn't going to get much value out of. to make an analogy - the creators of Segway thought people would buy them in large numbers, but it turned out most people don't mind walking manually (or at least, don't mind it enough to spend money on a scooter). I think makers of AI Desktop Use products are going to find out the same thing as it relates to everyday tasks like checking email and shopping.
    - 6mo ago
infecto 6mo ago
It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the picture. I am not that pessimistic on this front either though. For the data center build outs, demand for tokens is still exceeding supply. On the R&D front, well most of us here on HN have benefited from decades of overinflated engineering salaries being paid by often companies that were not profitable and not only unprofitable, usually without a plan for success. In this current rush, companies cannot keep up with supply, it’s a much easier math problem when you have something that people want (tokens) and you need to figure out profitability when including R&D.
- nickphx 6mo ago
  step change? how? profitable? where did you read that? people want tokens? really? who are these people?
  - elzbardico 6mo ago
    Yeah, if we just ignore R&D, fixed costs, depreciation, and the fact that there's a high likelyhood investor were expecting a return, yeah, ignoring all of that, and trusting their number we may say inference turns a profit. In accounting, almost anything you want can be true, at least for some time.
- boriskourt 6mo ago
  > The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. > For the data center build outs, demand for tokens is still exceeding supply. Can you provide any numbers for this?
  - bob1029 6mo ago
    https://www.cerebras.ai/blog/cerebras-cs-3-vs-nvidia-dgx-b200-blackwell https://www.cerebras.ai/blog/cerebras-cs-3-vs-nvidia-dgx-b20...
piker 6mo ago
> They lose a big customer for their cloud services. Even worse considering that now, using the AI they helped fund, everyone can compete with their sub-par products. GitHub is a good candidate for disruption, and that’d be just the start. Look, I'm a Microsoft hater like the rest of us, but calling Microsoft's products sub-par discredits the author a good bit. I invite anyone who thinks this to try and compete with them. Go after something like Word, for example. Then prepare to be awed by what some of the most brilliant programming minds ever can produce after grinding for four decades.
- Aperocky 6mo ago
  Sub par is not the right word, the right word is feature creep. markdown have much less of that brilliance and thankfully I also needed none of it. Last time I authored a word document is probably 2 years ago for a government interaction.
- karolist 6mo ago
  You can have an opinion about a tool as a user, without ever having ability to create such a tool yourself, that's literally what every tech and auto reviewer does.
  - piker 6mo ago
    Sure, and the less you understand about the tool’s fundamental capabilities, the less useful your opinion is. The best reviewers have deep knowledge.
    - hbn 6mo ago
      You can use this logic to say all products are perfect and any criticisms of them by users are moot because their creator knows them best.
    - deleted 6mo ago
      [deleted]
- curtisblaine 6mo ago
EternalFury 6mo ago
If somehow recovering the capex expenditure is not counted, if somehow the cost of developing future models is not counted, then yes, inference costs of current leading models allow a profit. But those things are tied together. Even xAI, that now has a reasonably competitive model, is struggling to achieve PMF. Meta is in shambles because their models have underperformed for years now.
joshstrange 6mo ago
> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fact this article links there with text "RAM prices are crashing" throws the entire rest of the article into doubt for me. RAM prices are most certainly not crashing (yet) and treating it as a forgone conclusion because _one_ lab found gains could be made and hasn't even reported on the efficiency of their method is just irresponsible. It's almost as bad as when LLMs link things to prove their point, you visit the link, and find it says nothing of the sort or even the opposite. [0] https://pcpartpicker.com/trends/price/memory/ https://pcpartpicker.com/trends/price/memory/ [1] https://tech.sportskeeda.com/gaming-news/how-google-s-new-turboquant-ai-might-end-current-ram-price-hike-crisis https://tech.sportskeeda.com/gaming-news/how-google-s-new-tu...
- faangguyindia 6mo ago
  If the gains are real why the limits are so bad? Google can barely serve Anti-gravity.
  - owlmirror 6mo ago
    Isn't that at the moment still a free product? Of course they will not prioritize serving those requests. That tells you nothing.
    - butlike 6mo ago
      It tells you there's no clear path to monetization.
      - adventured 6mo ago
        They've all avoided loading up their LLMs with ads to this point. That is going to change dramatically over the next 2-3 years. All of them will be loaded with ads, and Google will partake as expected given their ad network & capabilities in that realm. They'll match GPT's ad roll-out.
damotiansheng 6mo ago
[dead]
Havoc 6mo ago
Gov bailout seems like the only way out.
Aurornis 6mo ago
This article tries to build upon a lot of half-truths or incorrect facts, like this: > OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new. The discussion about being unprofitable also repeats the reductionist view that these companies are losing money and therefore the business model doesn’t work. This happens with every VC cycle where writers don’t understand that funded companies are supposed to lose money while they grow. That’s what the investment money is for. We have very strong indicators that inference is not a money loser for these companies and is likely very profitable. They should be spending large amounts of money on R&D to get ahead and try new things while they’re serving up tokens. The “but they’re losing money” argument never seems to be brought out against competitors that literally give away their models for free and for which we can calculate the cost of serving 400B-1T parameter open weight models.
- throwaway27448 6mo ago
  > We have very strong indicators that inference is not a money loser for these companies and is likely very profitable. Why is OpenAI specifically losing money hand over fist then?
  - aurareturn 6mo ago
    Training. But training costs are a smaller and smaller percentage of revenue as inference revenue grows faster than training costs.
    - ainch 6mo ago
      Do you have any evidence that inference revenue is growing faster than training costs? RLVR is significantly less compute-efficient than token-prediction pretraining - especially as labs are trying to train models to achieve agentic tasks which take tens of minutes per rollout.
      - 6mo ago
richard___ 6mo ago
Complete bs.
- martinvol 6mo ago
  great feedback
  - dist-epoch 6mo ago
    excellent comment
agentultra 6mo ago
It sounds like most of the data centers promised in 2025 and 2026 are not even built yet and most of the GPUs bought haven't even been installed. If it does all go down in flames, even floor value is not going to be that valuable. I can't predict the future but it's smelling a lot like a recession already under way that is bigger than the sub-prime crash.
thebeardredis 6mo ago
Hopefully soon. My new unwords are f.e. "agentic".
beepbooptheory 6mo ago
Just checked and my API bill for this stuff is about $2.50 this month. Am I really the minority here? I know there is a lot of kids into the openclaw and paying for subscriptions and stuff, but after that literally no one I know (who isn't a developer) is paying for it, and seemingly would never dream of paying for it. It would be like paying for Gmail to them I think. I just dont understand why it justifies so much spending!
nickcageinacage 6mo ago
AI is shit. I just want this to be over. Can we move on
aurareturn 6mo ago
This is an awful article. I don't know how it reached #1 on HN. Bottom line is that H100 prices are near 3 year highs, A100s are still profitable to run, B200 prices are increasing, no one has enough compute. Google, OpenAI, Anthropic, Meta, AWS, Azure are all compute constrained. Every single one of them said so publicly. Neo clouds are telling customers they're all sold out now and you even have to book compute in advance if you're an AI company. OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them with the more profitable corporate customers and software engineers. AI bubble is bursting because OpenAI is trying to monetize free users on ChatGPT with ads but Anthropic is kicking butt in AI. What kind of logic is that? So it seems like AI can be monetized as Anthropic shows. Is AI going to burst because OpenAI can't monetize but Anthropic can? I wouldn’t be surprised at all if in the next couple of quarters we see OpenAI looking for an exit. It will be interesting because the sizes are now so big that we will probably know all the details. The most likely buyer is Microsoft, they already own a lot of it, and because of that, they are the most interested in showing a win. I'll take the opposite stance. I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I think Anthropic and OpenAI are going to run laps around current big tech except maybe Google. For example, in a few years, I think AI agents could completely replace Microsoft Office, Microsoft's cash cow. Independent reports state that Claude metered models are priced 5x more expensive than their subscribers pay Already dispelled. It isn't 5x more expensive than their subscribers pay. Inference has a gross margin of 50%+. It's been repeated over and over again by Anthropic CEO, OpenAI CEO, and just about anyone who's done deep analysis on token profitability. If you don't believe OpenAI and Anthropic CEOs, just look at inference providers on Openrouter. They don't have VCs backing them selling tokens at a loss. They should be making margins on every token in order to keep the lights on.
- HackerThemAll 6mo ago
  > I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I am yet to see how a one-legged business model with just a single product (that is not crude oil), without a plan and money is going to become sustainable. Oh yeah, maybe they'll finally make money on those autonomous lethal weapons. That sounds the easiest.
HackerThemAll 6mo ago
Excellent reading to realize how the rich greedy investment monkeys with no plan other than "let's build a data center" will ultimately drag the market and the economy down. This time it may not explode as abruptly as in dotcom era, but will slowly sink as the stupid US data center boom proves unprofitable. Billions burned for nothing more than a run for the money.
hnthrow0287345 6mo ago
I don't see this bubble really popping as-in sinking the economy. Some circular investing and enough write offs will happen to avoid the largest recession indicators from informing the general population that there's actually a recession. You also have a government willing to do shady shit for their own benefit at the expense of responsible governing and ethics, and we have already seen the business leaders of the biggest tech companies cozy up to the administration. My guess is that cloud companies will scoop up the data centers for pennies on the dollar and the GPUs get written off or fire-sold to enthusiasts still wanting to run local models. Then they can offer exceptionally low initial prices to new customers and get more people to be locked in. Or maybe we see a couple of new cloud companies start up but that would likely need lower interest rates.
- lstodd 6mo ago
  DC infra will be scooped up by cloud guys, that's a given. As for GPUs.. well low-precision tflops have other uses besides inference. You can run Doom for example.
ajay-b 6mo ago
I would be very sad to lose services like ChatGPT. It has significantly improved my workflow by digesting and analyzing huge documents, and helping me to synthesize and respond better. May be I am part of a minority.
- raincole 6mo ago
  Don't worry lol. It's not going anywhere. The article is just ragebaitng. Verbatim: > Anthropic is already in a push to reduce costs and increase revenue Yeah, it's totally a bad sign when a company tries to... reduce costs and increase revenue.
  - mattmanser 6mo ago
    Their point is it is a bad sign at this stage in the game, there's a lot of competition still. Usually in a land grab like this you spend, spend, spend. Uber was still paying to subsidize customer's rides until fairly recently to kill off the competition.
    - raincole 6mo ago
      When AI companies spend a lot: a sign of bubble bursting. When AI companies look to cut cost: a sign of bubble bursting. When RAM price goes up: a sign of bubble bursting. When RAM price goes down: a sign of bubble bursting.
- coder68 6mo ago
  The good news is local models have significantly improved. If it all goes down today, you can still run e.g. Qwen 3.5 at home, and it's "good enough" for most workloads. With a gaming GPU you can run Qwen3.5-35B-A3B. I use 122B-A10B on my local rig (1x6000 Pro), and 397B-A17B on my 2x6000 Pro server (some spillover into CPU/RAM). It's pricey now but probably within a few years it'll become very affordable.
Lerc 6mo ago
A lot of this make me imagine an Aeroplane flown by a mad pilot, overloaded and running out of fuel. The passengers are all blaming the guy sitting in the back knitting a parachute and telling him that the chute will never work because the wool is the wrong colour. The tragedy is when it's all over one of the surviving passengers will go "See! I knew we were going to crash because of that knitter"
nexos 6mo ago
I think ultimately the AI bubble is bound to burst solely based on the fact that no AI company has turned a profit. A business model consisting of pure speculation on profitability when profit has not come in for 4 years now indicates that the tech industry is over-betting on AI. That plus consumer backlash at the way AI is jacking up consumer prices on RAM and etc means that the bubble is bound to burst. To paraphrase Linus Torvalds, AI is a helpful tool but I look forward to the day it’s a regular part of life and the hype cycle ends
KaiserPro 6mo ago
The problem with these kind of posts is that "How" is almost useless, I can tell you how the bubble pops: The value of these AI companies crash and take out a lots of other stuff with it. The interesting questions are: "What triggers it" and "what also goes tits up"? The issue with high/international finance is that a good percentage of it (if not more) is fraudulent or semi fraudulent bollocks. "Here is a startup that is worth x million because y" Both of those statements are bollocks. However its in the interest of most people to agree with that bollocks to get money. If enough money is given there is a chance that the startup will make money. If we look a few year back, NFTs fulfil that niche quite nicely. It was obviously bollocks, but a very convenient way to launder money, or run a series of rugpull operations. The problem we have to contend with now is that the sheer amount money that has been invested all disappearing at once would require 2007/8 levels of coordination to unfuck. The US government does not have the requisite number of admins to pull that off again, and no political will to ever have that expertise again. So if AI does go pop, and it takes a lot of money with it, I would put a guess on china doing the money lubrication and extracting a subtle but richly ironic level of control in exchange Also, its no guarantee that AI will trigger the next bubble popping, my money is on Private Equity.
- martinvol 6mo ago
  > The problem with these kind of posts is that "How" is almost useless, I can tell you how the bubble pops: The value of these AI companies crash and take out a lots of other stuff with it. That's like saying "I know exactly how you're going to die, your heart will stop"
NickNaraghi 6mo ago
> Taking this into account, Google is extremely well positioned to weather the storm. When they announce capex expenditure, they don’t spend it overnight. They can simply deploy month by month until their competitors struggle to raise and get forced to capitulate. At that point they can just ramp down the spending and declare victory in a cornered market. They don’t need capex, they just need to make it very clear for everyone that nobody can outspend them. Have you tried Gemini 3.1 lately? It is not even close to Opus 4.6 never mind Claude 5. This post, like many pessimistic takes, seriously discounts innovation and the exponential takeoff of recursive self-improvement.
- endymion-light 6mo ago
  Exponential take-off is great until it stops- genuinely, what are the signals showing any of the large models are performing exponential takeoff and recursive self-improvement? Currently a lot of that appears to be marketing hype to drive up usage. Is it exponential, or are the labs spending exponentially more for smaller and smaller gains from LLMs?
- bogzz 6mo ago
  What recursive self-improvement?
  - ratrace 6mo ago
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titzer 6mo ago
The article says "...and RAM prices are crashing because new models won’t need as much," and I went and read the link. The link was a puff piece for a very specific compression mechanism that...no one is using? I do hope that RAM prices come down but this was just wishful thinking.
skeeter2020 6mo ago
>> Building a datacenter is supposed to be a “safe” investment in normal times, so banks give private credit and mortgages to finance them. Except the investment is more like a railway or utility. It generates like 3% return, which is definitely not good enough for the people providing the money, or (in the case of the profitable companies) anywhere near the double-digit returns they make on their technology products. I won't be surprised when we see consolidation of marginal players and abandonment of the losers, just like you can find rail lines to nowhere, and fiber that's never been used.
vicchenai 6mo ago
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hyperpape 6mo ago
> Magnificent 7 companies are increasing capex to their biggest ever to differentiate their tech from each other and the big AI labs, but the key realization is that they don’t have to spend it to win. It’s a defensive move for them, if they commit $50B, OpenAI and Anthropic need to go raise $100B each to stay competitive, which makes them reliant on investors’ money. Stay competitive how? If the Magnificent 7 aren't spending the money, then how could it possibly hurt OpenAI/Anthropic to not raise equal amounts of money? Maybe you can pull together an explanation, but this author didn't even try to do so. This piece seems poorly thought-out, but well designed to get shared. Promote writers who will actually explain their claims carefully.
- martinvol 6mo ago
  they have to fight to stay competitive because mag7 can outspend them, but my hypothesis is that they wont need to ultimately.
lnfromx 6mo ago
Okay lets suppose all those companies are profitable if training would stop today. What if token demand is shrinking ? I think big parts of the current demand is artificially build by e.g. FOMO and marketing without real value generated by them. There is no indication in economic data about some productivity boom resulting from AI usage. Next thing is Energy costs - that will soon eat into profitability too. I don't see how this bubble can't burst.
- martinvol 6mo ago
  I don't think token demand will shrink because we're still just learning how to use it, demand will skyrocket. The problem is what price we'll be willing to pay for it, specially if competition keeps soaring.
  - deleted 6mo ago
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  - lnfromx 6mo ago
    But are we really still learning ? I feel like we already converge to a set of use cases. Also I am always wondering if LLMs are what they promise to be, why is it so difficult to find sources of real (measurable) value ? Wouldn't a disillusion of those overpromises trigger a reduction in demand ?
    - martinvol 6mo ago
      if they have the capital they can't risk but keep training, if someone comes up with a marginally better model than them then everyone will migrate and their business crashes down. Only big tech is in a position to take that risk.
post-it 6mo ago
Cheaper hardware, discounts on stocks, and we keep AI itself? My flavour of hopium, sign me up.
babaliauskas 6mo ago
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lancetheai 6mo ago
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LarsDu88 6mo ago
The world has seen this play out before. Launch a service, sell it at a loss to achieve hypergrowth, raise prices add ads and enshittify. The thing that is difference is the scale and the hardware. When Britain underwent its rail building boom in the 1850s, the bubble bursting left the kingdom with 150 years worth of infrastructure. Unless we invest in energy buildouts, we will be left with billions in rapidly depreciating GPUs
HardCodedBias 6mo ago
In general: Cynicism makes you sound smart. Optimism makes you successful. The cynicism around this technology is everywhere, even though it clearly has real power to solve problems. It is a technology which enables so many use cases that were impossible before, that makes it very highly hyped/expected. And that is causing an immune (over) reaction by natural skeptics, that's an error. People need to take a measured, reality based, view of how the technology is being used today, the adoption curve, and the increase in capabilities over time. It's clearly being used strongly, and may even be revolutionary. Bubbles burst when there's no 'there' there. AI has an undeniable 'there'—the only question is the timing of the ROI.
- martinvol 6mo ago
  bubbles are created by people investing more than reasonable in something, independent of the actual value it will generate for society.
logravia 6mo ago
The thing I am struggling with is where is the impact of LLM tools, especially given the massive increase in token consumption from 2025 to now and the saturated presence of LLMs everywhere. Naively speaking, I have so many expectations for the impact of this tech. I'd expect a noticeable uptick in applications published on Google, Apple and Microsoft app stores. I'd also expect an uptick of games published to Steam. I'd expect an uptick in Github repos and libraries on PyPi. I'd also expect some impact on the GDP ⸻ a non-negligible part of running a business is communication, planning, ads. Naively, I'd expect that LLMs should be able to both speed some of these things up and lubricate others. I'd also expect that large corpos like Microsoft and Apple would have more resources to spare on the essential details of their OS like having a functioning taskbar or a predictable, consistent GUI. I'd expect increased SAT scores or improved PISA results. Maybe even improved mental health, let's go wild. It's strikes me as a reasonably useful tool, personally. Yet, where are the goods in the aggregate?
- atomicnumber3 6mo ago
  Programming is a necessary but not sufficient condition for software products to exist. So while the programming has to be good, so too do many other things, like product vision, product management, project management, and of course there still needs to be feedback between all of the above so that engineering isn't implementing a misunderstood version of the product and that product isn't asking for 5 years and a PhD research team. And on and on and on. Typing the code is like 2-10% of actually ending up with a software project and it's more toward the 2% for a software business. So while AI made coding maybe 110% faster, it has also made literally every other person in the process lose their gd minds and they're wanting to break or skip everything else in the process to just shit out code faster.
  - d2ssa 6mo ago
    Going faster only works WHEN you know EXACTLY (or close to it) what you want. Going faster when experimenting? Nah you actually need a mix of slow and fast, and mostly slow stuff up-front. There's a fundamental misunderstanding of how people actually do stuff imo - its akin to force fitting a square peg in a round hole. Im sure many are hoping its just a 'your organisation is designed wrong' problem. I doubt it though.
imta71770 6mo ago
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maxothex 6mo ago
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jarek83 6mo ago
I wonder if AI labs could be bailed out - like banks. See, they kind of became a national asset and letting it go down, will leave USA watching China taking the lead for a very long time ahead. It just can't happen - right? So we'll just all fund it in taxes.
ethagnawl 6mo ago
> If investor money dries up, they will be forced to cut their losses and pass the true costs to their users. I do not see this talked about often enough whilst everyone is in the process of introducing hard dependencies on these services into their workflows.
- senordevnyc 6mo ago
  Really? Virtually every AI thread on HN has multiple people promising doom and gloom once the labs start passing the "true costs" onto the users. This very post has multiple deep comment chains arguing about this!
tracker1 6mo ago
Datacenters themselves are really weird... most of the announced 2024 data centers are nowhere near completion, most of NVidia's production is taking longer to deploy than to produce and will be upwards of 2+ years behind on deployments sometime in the next year. That doesn't even begin to cover the lack of actual electricity to power the data centers. We have more "dark silicon" sitting in boxes that aren't close to being deployed, while a lot of actual people can't manage to buy consumer products for anythign resembling reasonable... it's kind of insane to say the least.
relation_al 6mo ago
RAM's dropping? Woohoo!
m12k 6mo ago
Remember, having the dot com bubble burst did not prevent the internet from being integrated more and more in society over the next couple decades. What it did was stop the headless investment where money was thrown at anything that tangentially could be called "online". We went from "nobody knows what this is, but everyone wants a piece of it" to "we know what it is, and we sure did pursue a lot of bad ideas when we didn't". Expect something similar to happen with AI - having the bubble burst will not stop it in its tracks, but it will change what gets invested in.
mvdtnz 6mo ago
> And independent of whether Microsoft makes money or not in their OpenAI endeavor, it kills the story: they were betting the whole growth story on AI, and if that doesn’t work out, then what’s left to justify a high stock price? Microsoft's stock price today is the same as it was in late 2021 before anyone cared about AI. What would happen? Nothing. I don't think it's a significant revenue driver today. Microsoft, like everyone else, is speculating that AI will drive profits in the future. If it all fell apart there will certainly be losers but I don't see why it would bring down Microsoft.
poopiokaka 6mo ago
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yubanonbo 6mo ago
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panavinsingh 6mo ago
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syntheticmind 6mo ago
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372 points by martinvol 6mo ago

deleted 6mo ago

[deleted]

I could see OpenAI hitting financial issues which triggers some media induced panic and for people to claim the AI bubble has popped. However, the core utility of the best AI (read: Anthropic's ATM, by miles), will still exist and be leveraged by those who have learned to use it well. I could also see the exponentially declining power requirements offsetting the exponential-but-slower rate of AI compute demand, which then renders a lot of unused capacity in these massive data centers. I think of it like the old mainframes in the 70s which would take an entire city block to run, and now we have the equivalent of millions, if not billions of them in our pockets.

eieje 6mo ago
It’s pretty much undeniable at this point that the sentiment has changed. About 2 months ago this place was unbearable - filled with doom and hype AI posts. I welcome the calming and eventual slow release of the bubble.
baq 6mo ago
Anthropic isn’t the best by any reasonable measure. They’re the best in some areas and get pwned in others. In general AI is very much like human intelligence in the regard that no two models are the same just like no two people are the same. IOW if you are a single model shop you might even not have any idea that you’re falling behind.
cmrdporcupine 6mo ago
The coming months are the reckoning in which the poor quality of the tooling and the safeguards around them become evident and hopefully eventually rectified. By which I mean the competent organizations are the ones that will come up with cultural and technical solutions to manage the quantity and quality of the code better. Others will suffer severe quality issues. Not because the "AI"s produce inherently inferior code but because the volume of the code is too high to manage review of, and to have good internal organizational knowledge of to manage the pages in the middle of the night when servers go down because of code nobody really understood. I produce masses of independent project work all day long in my spare time using these tools and they blow me away. But in the context of professional work on teams of other coworkers the results are difficult to reason about and often impossible to competently review and it's not clear the results are superior. ' IMHO companies that drink too deep from the well without caution could be burned badly. Aside: I hate to say it, but there is no sense in which Anthropic has the clearly better product than OpenAI at this point. I know Claude caught developer's hearts through the fall, but GPT5.4 is a more powerful, careful, and competent model for coding and Codex is a far less buggy and more performant TUI. For the last 3 months I've gone back and forth between the two and I always run anything written by Claude Opus 4.6 by myself and my coworkers through Codex for review and it is constantly finding severe correctness issues to the point where I simply won't subscribe to Anthropic's product anymore. On top of that, OpenAI provides far higher token limits. Even their $20 plan goes quite far. If I was just building crud websites, probably Claude Code would be fine, and it does indeed show more "initiative" and "imagination" but I've seen it build way too many race conditions and correctness issues to trust it or the work my coworkers make with it.
_puk 6mo ago
A lot of anthropic's recent improvements are coming from the task focus and improved orchestration around the models, not purely massive changes in the models themselves. This bodes well for us being at a point that even if the bubble burst, we'd still have usable AI going forward.
jqpabc123 6mo ago
I think of it like the old mainframes in the 70s I think this is a good comparison to current AI. billions of them in our pockets. AI in your pocket (but first on the desktop) is a real possibility.

monegator 6mo ago

> How this affects you? > checks list ... nope, nothing will either directly or indirectly affect me. Let it happen sooner, rather than later, and unleash the mobs at the tech bros that set the world on course to make everybody's life more miserable. We'll still be here to get the scrapped RAM and GPUs to train and infere local models thank you very much.

coffeebeqn 6mo ago
The current best models are already very capable of disrupting the job of millions of people. I don’t think a scenario where we just go back to pre-Claude Code exists and I’m sure the same models can be tuned for much of other white collar work at similar capability
- eieje 6mo ago
  People keep saying this but nothing of the sort has happened. People continue to work, some proportion of the those working use LLM’s regularly. Enough time has passed that subjective statements about the future don’t pass muster. Look at the numbers - there has been no large scale lay offs since correcting for over hiring. Has hiring slowed down? Sure. However I’d wager most firms are finding it pretty difficult to think of projects to take that will generate positive NPV. If that’s the case why would they hire? Moreover the focus has returned to cash flows - not product based growth metrics. Which again re-inforces the point about project selection. Efficiency generated growth does not continue on forever - it’s short lived.
- monegator 6mo ago
  might be: there is too much busy work as it is, but we need people to work in order to make money in order to spend it in order to keep the circus from going under. It's the circle of life Let me remind you that you are not paying the full price for the service and all the value of those company is out of thin air. More or less the premise of the article. *when* you will be asked the real price, we'll see if the company will prefer a human or a bot it can't pass blame to

general_reveal 6mo ago

HN is no longer a reliable place for the truth. Quite frankly, unless you are utterly self educated, you are terribly vulnerable to this place. At this rate, I’d almost prefer to talk on a private mailing list with vetted resumes.

myspy 6mo ago
Why?
- general_reveal 6mo ago
  You have to be uneducated to even read an “AI is bubble article”. Anyone working this stuff knows how much more compute we need.
  - myspy 6mo ago
    Thanks for clearing this up, as I don't work in that area. Personally I'd say that it's a problem that prices of consumer goods go up that far to satisfy this part of the market. We could need a more sensible way to advance the technology.
    - user34283 6mo ago
      That problem seems to mostly impact teenage gamers who need more than 16 GB of memory and can't afford the extra $300. In my opinion this is incomparable to what we are seeing with agentic AI that is rapidly replacing handwriting code. I figure chances are AI is not going to stop here.
  - A_D_E_P_T 6mo ago
    Two things can be true at the same time: - AI is a genuinely transformative technology on par with the internet and on track to probably surpass the smartphone - The inflated valuations, the circular flows of money (or "money"), and the financial cup-shell game mean that the players of the game are all a few bad weeks away from catastrophe. This is, of course, nothing new for SV -- but the scale this time is new. Some believe it will soon collapse -- "bubble," thus.

elorant 6mo ago

I feel that even if the bubble bursts hardware prices will still take years to normalize. So no clear benefit for the average consumer here.

baggachipz 6mo ago
Consumers and retail investors will bear most of the brunt from this bubble. Even taxpayers, as the government will most likely bail out the "too big to fail" ai companies in the "race against China". All based on bullshit, hype, and greed.

jqpabc123 6mo ago

Another possibility not really addressed here --- local LLMs. AI on hardware you own and control --- instead of a metered service provider. In other words, a repeat of the "personal computing" revolution but this time focused on AI. TurboQuant could be a key step in this direction.

netdevphoenix 6mo ago
Local LLMs don't sound profitable at all for those building them. If you really wanted a SOTA model, you would be paying eye watering amounts to own it unless you got an open sourced one.
- jqpabc123 6mo ago
  unless you got an open sourced one. Ding, ding, ding --- we have a winner. https://techstartups.com/2026/03/26/nvidia-backed-ai-startup-reflection-eyes-2-5b-round-at-25b-valuation-to-challenge-deepseek-meta-and-mistral/ https://techstartups.com/2026/03/26/nvidia-backed-ai-startup... https://tiiny.ai/ https://tiiny.ai/
schnitzelstoat 6mo ago
Yeah, I don't think local LLM's will keep up with what the massive corporations put out. But they might get to a level of performance where it just doesn't matter for most users. And people would prefer to run a model locally for 'free' (not counting the energy cost) rather than paying for an LLM subscription.
zozbot234 6mo ago
TurboQuant helps KV quantization which is not very relevant to local LLMs, since context size becomes most relevant when you run inference with large batches. For small-scale inference, weights dominate. (Even if you stream weights from SSD, you'll want to cache a sizeable fraction to get workable throughput, and that dominates your memory usage.)

franze 6mo ago

.... so what? the technology exists, the models exist. Even when the bubble bursts things will not go to the state "before AI". Even if model development would stop today (not the worst thing to happen) it would still be the most impactful invention since the printing press

hk__2 6mo ago
Yes, that’s what the author wrote in the second sentence of the post: "AI is here to stay."
irusensei 6mo ago
I guess the point is that without the hype subsiding it enshitification will ensue.

positron26 6mo ago

When will this concern farm end? Internet is ant-milling harder than a model gone psychotic on synthetic data. Call me when it's over. Back to the mines. The Vulkan only writes itself when prompted with well-conditioned problem statements.

nopinsight 6mo ago

> nobody is sure if even their metered pricing is profitable This is most likely wrong. Lab executives insist that serving tokens is profitable. It's the cost of training next-gen models that requires them to keep raising ever larger rounds. More importantly, many independent providers price tokens of open-weight models at a fraction of Anthropic's prices.

sunaurus 6mo ago
The point is that you can’t just serve tokens without also training the next models. It’s an inseparable part of your costs, so naturally you can’t be profitable unless the price you are charging ALSO covers training.
- dash2 6mo ago
  Is that right? I think that you can serve tokens without training the next models. It would be bad strategy, but it would work. So it's an important question, are they covering their operating expenditure? If they are the business has legs (and it will be worth spending a lot to train the next models). If not, maybe not.
  - camdenreslink 6mo ago
    If a major model provider were to just halt progress on developing new and improved models, the open weight alternatives would catch up in a couple years. They would have a period of great margin, followed by possibly zero margin as enterprises move to free options. They would have to come up with a lot of great products around the inferior models to justify charging at that point.
    - leoc 6mo ago
      Also, an out-of-date model which doesn't know about last year's world events, hit songs and new JS libraries is a depreciating asset even before you consider low-cost competitors catching up. So you'd presumably have to do some training just to keep the model up to date at the current quality level (unless you completely give up and just sweat the assets). And on the other side of that coin: over the next few years, do the latest, biggest models continue to generate user-perceived real-world improvements sufficient to keep users wanting the latest and greatest?

syntheticmind 6mo ago

[flagged]

qoez 6mo ago

History doesn't have to repeat. There's barely anything else going on in terms of innovation, and AI is a real step function technology. We might be overspending but there's no way we're getting another AI winter like last time (remember last time investment in 90s AI had to compete for resources with the internet boom).

hk__2 6mo ago
Isn’t that covered at the top of the post? > AI is here to stay. If used right, chances are it will make us all more productive. That, on the other hand, does not mean it will be a good investment.
lionkor 6mo ago
> History doesn't have to repeat This is high up there on the list of things people say before, you know, it does
joefourier 6mo ago
The dotcom bubble burst and 26 years later we’re all hopelessly addicted to the internet and the top companies on the stock market are almost all what would have been called “dotcoms” then. The railroad bubble burst in 1846 not because trains were a dead end - passenger number would increase more than 10x in the UK in the following 50 years.

Chance-Device 6mo ago

From the beginning of this I’ve wondered the same question: how do these companies justify spending such massive amounts now (and 3 or 4 years ago) when software and hardware efficiencies will bring down the cost dramatically fairly soon? They basically decided that scaling at any cost was the way to go. This only works as a strategy if efficiency can’t work, not if you simply haven’t tried. Otherwise, a few breakthroughs and order of magnitude improvements and people are running equivalent models on their desktops, then their laptops, then their phones. Arguably the costs involved means that our existing hardware and software is simply non viable for what they were and are trying to do, and a few iterations later the money will simply have been wasted. If you consider funnelling everything to nvidia shareholders wasting it, which I do.

mrob 6mo ago
Because whoever wins the AI race (assuming they don't overshoot and trigger the hard takeoff scenario) becomes a living god. Everybody else becomes their slave, to be killed or exploited as they please. It's a risky gamble, but in the eyes of the participants the upside justifies it. If they don't go all in they're still exposed to all the downside risk but have no chance of winning. I don't expect hardware prices to go down unless the third option (economic collapse) happens before somebody triggers the dystopia/extinction option.
- WarmWash 6mo ago
  Just to add some slight nuance but is an important distinction, They aren't all necessarily racing to be "god", some are racing to make sure someone else is not "god". If it weren't for Altman releasing ChatGPT, it's very likely that we would have markedly less powerful LLMs at our disposal right now. Deepmind and Anthropic were taking incredibly safe and conservative approaches towards transformers, but OAI broke the silent truce and forced a race.
phito 6mo ago
I think their current goal is to capture as much market as they can while they still have the best models, their only moat. Look at Anthropic, they are clearly trying to lock their users in their ecosystem by refusing to follow conventions (AGENT.md etc) and restricting their tools exclusively to their own services.

shubhamjain 6mo ago

> OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them with the more profitable corporate customers and software engineers. Their shopping feature flopped and they shut down Sora, both supposed to be revenue drivers. I don't think Sora ever thought of as a "revenue driver" considering how notoriously expensive and unpredictable video generation via inference is. OpenAI is just a repeat of Uber—minus the scandals—in a different decade. Uber got itself into tons of businesses related to transportation on the assumption that it would all be viable "one day." Same stuff that OpenAI is going. I would say, once the bubble bursts—which is likely, considering the geopolitical environment—OpenAI, Anthropic, and Alphabet are likely to be the winners, with a lot of small players at the tail end. Anthropic won over programmers and OpenAI on everyone else. For millions of people, AI = ChatGPT, so I would bet that OpenAI can still become profitable, once they cut down their expenses.

JohnTHaller 6mo ago
> minus the scandals Given the tech bros involved, we just don't know about them yet. Also was this comment generated using AI? Look at all the em dashes.

schnitzelstoat 6mo ago

It's a winner-takes-all market and everyone wants to be the next Google and not the next Lycos or AskJeeves etc. It'd be interesting to see what they spend all the money on though as we seem to be hitting diminishing returns and I'm not sure if the typical enterprise user really cares about small improvements on benchmarks. It seems like it'd probably be better to spend all that on marketing, free trials, exclusivity/bundle deals etc. ChatGPT already has a strong advantage there as it has so much brand recognition. I've seen lay people refer to all LLM's as ChatGPT like my grandparents did with Nintendo and all video game consoles.

delecti 6mo ago
I don't think it's winner-takes-all. Google is Google in 2026 because Lycos and AskJeeves were bad in comparison. The average user doesn't care whose LLM they're using because they're all close enough. It's hard to see past the bubble bursting, but I expect most people will use multiple of them depending on context (Copilot via the integration in windows, Gemini via Siri on their phone, etc), likely without paying.
H8crilA 6mo ago
Where to go next? I don't think anyone has gotten close to automating everyday PC usage, likely via screen capture and raw keyboard+mouse inputs. Imagine how much bigger would that market be than vibecoding.
- wavemode 6mo ago
  tbh I don't think this use case is going to be as big as people seem to think there are a lot of reasons, but in brief - I think AI desktop use is a product that the average person isn't going to get much value out of. to make an analogy - the creators of Segway thought people would buy them in large numbers, but it turned out most people don't mind walking manually (or at least, don't mind it enough to spend money on a scooter). I think makers of AI Desktop Use products are going to find out the same thing as it relates to everyday tasks like checking email and shopping.
  - 6mo ago

infecto 6mo ago

It’s incredible how polarizing the AI rush is. I keep the perspective that the technology is an absolute step change but I have no idea where the cards will fall. I take a lot of issue with these style of articles. I get a sense that the authors are being overly defensive. The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. What’s unclear is how R&D and capex fit into the picture. I am not that pessimistic on this front either though. For the data center build outs, demand for tokens is still exceeding supply. On the R&D front, well most of us here on HN have benefited from decades of overinflated engineering salaries being paid by often companies that were not profitable and not only unprofitable, usually without a plan for success. In this current rush, companies cannot keep up with supply, it’s a much easier math problem when you have something that people want (tokens) and you need to figure out profitability when including R&D.

nickphx 6mo ago
step change? how? profitable? where did you read that? people want tokens? really? who are these people?
- elzbardico 6mo ago
  Yeah, if we just ignore R&D, fixed costs, depreciation, and the fact that there's a high likelyhood investor were expecting a return, yeah, ignoring all of that, and trusting their number we may say inference turns a profit. In accounting, almost anything you want can be true, at least for some time.
boriskourt 6mo ago
> The cost to serve tokens is absolutely profitable today and that’s been true for at least a year. > For the data center build outs, demand for tokens is still exceeding supply. Can you provide any numbers for this?
- bob1029 6mo ago
  https://www.cerebras.ai/blog/cerebras-cs-3-vs-nvidia-dgx-b200-blackwell https://www.cerebras.ai/blog/cerebras-cs-3-vs-nvidia-dgx-b20...

piker 6mo ago

> They lose a big customer for their cloud services. Even worse considering that now, using the AI they helped fund, everyone can compete with their sub-par products. GitHub is a good candidate for disruption, and that’d be just the start. Look, I'm a Microsoft hater like the rest of us, but calling Microsoft's products sub-par discredits the author a good bit. I invite anyone who thinks this to try and compete with them. Go after something like Word, for example. Then prepare to be awed by what some of the most brilliant programming minds ever can produce after grinding for four decades.

Aperocky 6mo ago
Sub par is not the right word, the right word is feature creep. markdown have much less of that brilliance and thankfully I also needed none of it. Last time I authored a word document is probably 2 years ago for a government interaction.
karolist 6mo ago
You can have an opinion about a tool as a user, without ever having ability to create such a tool yourself, that's literally what every tech and auto reviewer does.
- piker 6mo ago
  Sure, and the less you understand about the tool’s fundamental capabilities, the less useful your opinion is. The best reviewers have deep knowledge.
  - hbn 6mo ago
    You can use this logic to say all products are perfect and any criticisms of them by users are moot because their creator knows them best.
  - deleted 6mo ago
    [deleted]
curtisblaine 6mo ago

EternalFury 6mo ago

If somehow recovering the capex expenditure is not counted, if somehow the cost of developing future models is not counted, then yes, inference costs of current leading models allow a profit. But those things are tied together. Even xAI, that now has a reasonably competitive model, is struggling to achieve PMF. Meta is in shambles because their models have underperformed for years now.

joshstrange 6mo ago

> RAM prices are crashing because new models won’t need as much Reality begs to differ [0] and following the link for that text goes to an article [1] where they talk about Google's TurboQuant which supposedly will lower the RAM requirements. Now if that means RAM prices come down (as speculated, not reported on, in the link) or the AI companies just do more things with their extra ram is yet to be determined. The fact this article links there with text "RAM prices are crashing" throws the entire rest of the article into doubt for me. RAM prices are most certainly not crashing (yet) and treating it as a forgone conclusion because _one_ lab found gains could be made and hasn't even reported on the efficiency of their method is just irresponsible. It's almost as bad as when LLMs link things to prove their point, you visit the link, and find it says nothing of the sort or even the opposite. [0] https://pcpartpicker.com/trends/price/memory/ https://pcpartpicker.com/trends/price/memory/ [1] https://tech.sportskeeda.com/gaming-news/how-google-s-new-turboquant-ai-might-end-current-ram-price-hike-crisis https://tech.sportskeeda.com/gaming-news/how-google-s-new-tu...

faangguyindia 6mo ago
If the gains are real why the limits are so bad? Google can barely serve Anti-gravity.
- owlmirror 6mo ago
  Isn't that at the moment still a free product? Of course they will not prioritize serving those requests. That tells you nothing.
  - butlike 6mo ago
    It tells you there's no clear path to monetization.
    - adventured 6mo ago
      They've all avoided loading up their LLMs with ads to this point. That is going to change dramatically over the next 2-3 years. All of them will be loaded with ads, and Google will partake as expected given their ad network & capabilities in that realm. They'll match GPT's ad roll-out.

damotiansheng 6mo ago

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Havoc 6mo ago

Gov bailout seems like the only way out.

Aurornis 6mo ago

This article tries to build upon a lot of half-truths or incorrect facts, like this: > OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new. The discussion about being unprofitable also repeats the reductionist view that these companies are losing money and therefore the business model doesn’t work. This happens with every VC cycle where writers don’t understand that funded companies are supposed to lose money while they grow. That’s what the investment money is for. We have very strong indicators that inference is not a money loser for these companies and is likely very profitable. They should be spending large amounts of money on R&D to get ahead and try new things while they’re serving up tokens. The “but they’re losing money” argument never seems to be brought out against competitors that literally give away their models for free and for which we can calculate the cost of serving 400B-1T parameter open weight models.

throwaway27448 6mo ago
> We have very strong indicators that inference is not a money loser for these companies and is likely very profitable. Why is OpenAI specifically losing money hand over fist then?
- aurareturn 6mo ago
  Training. But training costs are a smaller and smaller percentage of revenue as inference revenue grows faster than training costs.
  - ainch 6mo ago
    Do you have any evidence that inference revenue is growing faster than training costs? RLVR is significantly less compute-efficient than token-prediction pretraining - especially as labs are trying to train models to achieve agentic tasks which take tens of minutes per rollout.
    - 6mo ago

richard___ 6mo ago

Complete bs.

martinvol 6mo ago
great feedback
- dist-epoch 6mo ago
  excellent comment

agentultra 6mo ago

It sounds like most of the data centers promised in 2025 and 2026 are not even built yet and most of the GPUs bought haven't even been installed. If it does all go down in flames, even floor value is not going to be that valuable. I can't predict the future but it's smelling a lot like a recession already under way that is bigger than the sub-prime crash.

thebeardredis 6mo ago

Hopefully soon. My new unwords are f.e. "agentic".

beepbooptheory 6mo ago

Just checked and my API bill for this stuff is about $2.50 this month. Am I really the minority here? I know there is a lot of kids into the openclaw and paying for subscriptions and stuff, but after that literally no one I know (who isn't a developer) is paying for it, and seemingly would never dream of paying for it. It would be like paying for Gmail to them I think. I just dont understand why it justifies so much spending!

nickcageinacage 6mo ago

AI is shit. I just want this to be over. Can we move on

aurareturn 6mo ago

This is an awful article. I don't know how it reached #1 on HN. Bottom line is that H100 prices are near 3 year highs, A100s are still profitable to run, B200 prices are increasing, no one has enough compute. Google, OpenAI, Anthropic, Meta, AWS, Azure are all compute constrained. Every single one of them said so publicly. Neo clouds are telling customers they're all sold out now and you even have to book compute in advance if you're an AI company. OpenAI is struggling to monetize. They turned to showing ads in ChatGPT, something Sam Altman once called a “last resort”, while Anthropic is crushing them with the more profitable corporate customers and software engineers. AI bubble is bursting because OpenAI is trying to monetize free users on ChatGPT with ads but Anthropic is kicking butt in AI. What kind of logic is that? So it seems like AI can be monetized as Anthropic shows. Is AI going to burst because OpenAI can't monetize but Anthropic can? I wouldn’t be surprised at all if in the next couple of quarters we see OpenAI looking for an exit. It will be interesting because the sizes are now so big that we will probably know all the details. The most likely buyer is Microsoft, they already own a lot of it, and because of that, they are the most interested in showing a win. I'll take the opposite stance. I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I think Anthropic and OpenAI are going to run laps around current big tech except maybe Google. For example, in a few years, I think AI agents could completely replace Microsoft Office, Microsoft's cash cow. Independent reports state that Claude metered models are priced 5x more expensive than their subscribers pay Already dispelled. It isn't 5x more expensive than their subscribers pay. Inference has a gross margin of 50%+. It's been repeated over and over again by Anthropic CEO, OpenAI CEO, and just about anyone who's done deep analysis on token profitability. If you don't believe OpenAI and Anthropic CEOs, just look at inference providers on Openrouter. They don't have VCs backing them selling tokens at a loss. They should be making margins on every token in order to keep the lights on.

HackerThemAll 6mo ago
> I think OpenAI is going to be bigger than Microsoft in market cap within the next 3 years. I am yet to see how a one-legged business model with just a single product (that is not crude oil), without a plan and money is going to become sustainable. Oh yeah, maybe they'll finally make money on those autonomous lethal weapons. That sounds the easiest.

HackerThemAll 6mo ago

Excellent reading to realize how the rich greedy investment monkeys with no plan other than "let's build a data center" will ultimately drag the market and the economy down. This time it may not explode as abruptly as in dotcom era, but will slowly sink as the stupid US data center boom proves unprofitable. Billions burned for nothing more than a run for the money.

hnthrow0287345 6mo ago

I don't see this bubble really popping as-in sinking the economy. Some circular investing and enough write offs will happen to avoid the largest recession indicators from informing the general population that there's actually a recession. You also have a government willing to do shady shit for their own benefit at the expense of responsible governing and ethics, and we have already seen the business leaders of the biggest tech companies cozy up to the administration. My guess is that cloud companies will scoop up the data centers for pennies on the dollar and the GPUs get written off or fire-sold to enthusiasts still wanting to run local models. Then they can offer exceptionally low initial prices to new customers and get more people to be locked in. Or maybe we see a couple of new cloud companies start up but that would likely need lower interest rates.

lstodd 6mo ago
DC infra will be scooped up by cloud guys, that's a given. As for GPUs.. well low-precision tflops have other uses besides inference. You can run Doom for example.

ajay-b 6mo ago

I would be very sad to lose services like ChatGPT. It has significantly improved my workflow by digesting and analyzing huge documents, and helping me to synthesize and respond better. May be I am part of a minority.

raincole 6mo ago
Don't worry lol. It's not going anywhere. The article is just ragebaitng. Verbatim: > Anthropic is already in a push to reduce costs and increase revenue Yeah, it's totally a bad sign when a company tries to... reduce costs and increase revenue.
- mattmanser 6mo ago
  Their point is it is a bad sign at this stage in the game, there's a lot of competition still. Usually in a land grab like this you spend, spend, spend. Uber was still paying to subsidize customer's rides until fairly recently to kill off the competition.
  - raincole 6mo ago
    When AI companies spend a lot: a sign of bubble bursting. When AI companies look to cut cost: a sign of bubble bursting. When RAM price goes up: a sign of bubble bursting. When RAM price goes down: a sign of bubble bursting.
coder68 6mo ago
The good news is local models have significantly improved. If it all goes down today, you can still run e.g. Qwen 3.5 at home, and it's "good enough" for most workloads. With a gaming GPU you can run Qwen3.5-35B-A3B. I use 122B-A10B on my local rig (1x6000 Pro), and 397B-A17B on my 2x6000 Pro server (some spillover into CPU/RAM). It's pricey now but probably within a few years it'll become very affordable.

Lerc 6mo ago

A lot of this make me imagine an Aeroplane flown by a mad pilot, overloaded and running out of fuel. The passengers are all blaming the guy sitting in the back knitting a parachute and telling him that the chute will never work because the wool is the wrong colour. The tragedy is when it's all over one of the surviving passengers will go "See! I knew we were going to crash because of that knitter"

nexos 6mo ago

I think ultimately the AI bubble is bound to burst solely based on the fact that no AI company has turned a profit. A business model consisting of pure speculation on profitability when profit has not come in for 4 years now indicates that the tech industry is over-betting on AI. That plus consumer backlash at the way AI is jacking up consumer prices on RAM and etc means that the bubble is bound to burst. To paraphrase Linus Torvalds, AI is a helpful tool but I look forward to the day it’s a regular part of life and the hype cycle ends

KaiserPro 6mo ago

The problem with these kind of posts is that "How" is almost useless, I can tell you how the bubble pops: The value of these AI companies crash and take out a lots of other stuff with it. The interesting questions are: "What triggers it" and "what also goes tits up"? The issue with high/international finance is that a good percentage of it (if not more) is fraudulent or semi fraudulent bollocks. "Here is a startup that is worth x million because y" Both of those statements are bollocks. However its in the interest of most people to agree with that bollocks to get money. If enough money is given there is a chance that the startup will make money. If we look a few year back, NFTs fulfil that niche quite nicely. It was obviously bollocks, but a very convenient way to launder money, or run a series of rugpull operations. The problem we have to contend with now is that the sheer amount money that has been invested all disappearing at once would require 2007/8 levels of coordination to unfuck. The US government does not have the requisite number of admins to pull that off again, and no political will to ever have that expertise again. So if AI does go pop, and it takes a lot of money with it, I would put a guess on china doing the money lubrication and extracting a subtle but richly ironic level of control in exchange Also, its no guarantee that AI will trigger the next bubble popping, my money is on Private Equity.

martinvol 6mo ago
> The problem with these kind of posts is that "How" is almost useless, I can tell you how the bubble pops: The value of these AI companies crash and take out a lots of other stuff with it. That's like saying "I know exactly how you're going to die, your heart will stop"

NickNaraghi 6mo ago

> Taking this into account, Google is extremely well positioned to weather the storm. When they announce capex expenditure, they don’t spend it overnight. They can simply deploy month by month until their competitors struggle to raise and get forced to capitulate. At that point they can just ramp down the spending and declare victory in a cornered market. They don’t need capex, they just need to make it very clear for everyone that nobody can outspend them. Have you tried Gemini 3.1 lately? It is not even close to Opus 4.6 never mind Claude 5. This post, like many pessimistic takes, seriously discounts innovation and the exponential takeoff of recursive self-improvement.

endymion-light 6mo ago
Exponential take-off is great until it stops- genuinely, what are the signals showing any of the large models are performing exponential takeoff and recursive self-improvement? Currently a lot of that appears to be marketing hype to drive up usage. Is it exponential, or are the labs spending exponentially more for smaller and smaller gains from LLMs?
bogzz 6mo ago
What recursive self-improvement?
- ratrace 6mo ago
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titzer 6mo ago

The article says "...and RAM prices are crashing because new models won’t need as much," and I went and read the link. The link was a puff piece for a very specific compression mechanism that...no one is using? I do hope that RAM prices come down but this was just wishful thinking.

skeeter2020 6mo ago

>> Building a datacenter is supposed to be a “safe” investment in normal times, so banks give private credit and mortgages to finance them. Except the investment is more like a railway or utility. It generates like 3% return, which is definitely not good enough for the people providing the money, or (in the case of the profitable companies) anywhere near the double-digit returns they make on their technology products. I won't be surprised when we see consolidation of marginal players and abandonment of the losers, just like you can find rail lines to nowhere, and fiber that's never been used.

vicchenai 6mo ago

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hyperpape 6mo ago

> Magnificent 7 companies are increasing capex to their biggest ever to differentiate their tech from each other and the big AI labs, but the key realization is that they don’t have to spend it to win. It’s a defensive move for them, if they commit $50B, OpenAI and Anthropic need to go raise $100B each to stay competitive, which makes them reliant on investors’ money. Stay competitive how? If the Magnificent 7 aren't spending the money, then how could it possibly hurt OpenAI/Anthropic to not raise equal amounts of money? Maybe you can pull together an explanation, but this author didn't even try to do so. This piece seems poorly thought-out, but well designed to get shared. Promote writers who will actually explain their claims carefully.

martinvol 6mo ago
they have to fight to stay competitive because mag7 can outspend them, but my hypothesis is that they wont need to ultimately.

lnfromx 6mo ago

Okay lets suppose all those companies are profitable if training would stop today. What if token demand is shrinking ? I think big parts of the current demand is artificially build by e.g. FOMO and marketing without real value generated by them. There is no indication in economic data about some productivity boom resulting from AI usage. Next thing is Energy costs - that will soon eat into profitability too. I don't see how this bubble can't burst.

martinvol 6mo ago
I don't think token demand will shrink because we're still just learning how to use it, demand will skyrocket. The problem is what price we'll be willing to pay for it, specially if competition keeps soaring.
- deleted 6mo ago
  [deleted]
- lnfromx 6mo ago
  But are we really still learning ? I feel like we already converge to a set of use cases. Also I am always wondering if LLMs are what they promise to be, why is it so difficult to find sources of real (measurable) value ? Wouldn't a disillusion of those overpromises trigger a reduction in demand ?
  - martinvol 6mo ago
    if they have the capital they can't risk but keep training, if someone comes up with a marginally better model than them then everyone will migrate and their business crashes down. Only big tech is in a position to take that risk.

post-it 6mo ago

Cheaper hardware, discounts on stocks, and we keep AI itself? My flavour of hopium, sign me up.

babaliauskas 6mo ago

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lancetheai 6mo ago

[flagged]

LarsDu88 6mo ago

The world has seen this play out before. Launch a service, sell it at a loss to achieve hypergrowth, raise prices add ads and enshittify. The thing that is difference is the scale and the hardware. When Britain underwent its rail building boom in the 1850s, the bubble bursting left the kingdom with 150 years worth of infrastructure. Unless we invest in energy buildouts, we will be left with billions in rapidly depreciating GPUs

HardCodedBias 6mo ago

In general: Cynicism makes you sound smart. Optimism makes you successful. The cynicism around this technology is everywhere, even though it clearly has real power to solve problems. It is a technology which enables so many use cases that were impossible before, that makes it very highly hyped/expected. And that is causing an immune (over) reaction by natural skeptics, that's an error. People need to take a measured, reality based, view of how the technology is being used today, the adoption curve, and the increase in capabilities over time. It's clearly being used strongly, and may even be revolutionary. Bubbles burst when there's no 'there' there. AI has an undeniable 'there'—the only question is the timing of the ROI.

martinvol 6mo ago
bubbles are created by people investing more than reasonable in something, independent of the actual value it will generate for society.

logravia 6mo ago

The thing I am struggling with is where is the impact of LLM tools, especially given the massive increase in token consumption from 2025 to now and the saturated presence of LLMs everywhere. Naively speaking, I have so many expectations for the impact of this tech. I'd expect a noticeable uptick in applications published on Google, Apple and Microsoft app stores. I'd also expect an uptick of games published to Steam. I'd expect an uptick in Github repos and libraries on PyPi. I'd also expect some impact on the GDP ⸻ a non-negligible part of running a business is communication, planning, ads. Naively, I'd expect that LLMs should be able to both speed some of these things up and lubricate others. I'd also expect that large corpos like Microsoft and Apple would have more resources to spare on the essential details of their OS like having a functioning taskbar or a predictable, consistent GUI. I'd expect increased SAT scores or improved PISA results. Maybe even improved mental health, let's go wild. It's strikes me as a reasonably useful tool, personally. Yet, where are the goods in the aggregate?

atomicnumber3 6mo ago
Programming is a necessary but not sufficient condition for software products to exist. So while the programming has to be good, so too do many other things, like product vision, product management, project management, and of course there still needs to be feedback between all of the above so that engineering isn't implementing a misunderstood version of the product and that product isn't asking for 5 years and a PhD research team. And on and on and on. Typing the code is like 2-10% of actually ending up with a software project and it's more toward the 2% for a software business. So while AI made coding maybe 110% faster, it has also made literally every other person in the process lose their gd minds and they're wanting to break or skip everything else in the process to just shit out code faster.
- d2ssa 6mo ago
  Going faster only works WHEN you know EXACTLY (or close to it) what you want. Going faster when experimenting? Nah you actually need a mix of slow and fast, and mostly slow stuff up-front. There's a fundamental misunderstanding of how people actually do stuff imo - its akin to force fitting a square peg in a round hole. Im sure many are hoping its just a 'your organisation is designed wrong' problem. I doubt it though.

imta71770 6mo ago

[flagged]

maxothex 6mo ago

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jarek83 6mo ago

I wonder if AI labs could be bailed out - like banks. See, they kind of became a national asset and letting it go down, will leave USA watching China taking the lead for a very long time ahead. It just can't happen - right? So we'll just all fund it in taxes.

ethagnawl 6mo ago

> If investor money dries up, they will be forced to cut their losses and pass the true costs to their users. I do not see this talked about often enough whilst everyone is in the process of introducing hard dependencies on these services into their workflows.

senordevnyc 6mo ago
Really? Virtually every AI thread on HN has multiple people promising doom and gloom once the labs start passing the "true costs" onto the users. This very post has multiple deep comment chains arguing about this!

tracker1 6mo ago

Datacenters themselves are really weird... most of the announced 2024 data centers are nowhere near completion, most of NVidia's production is taking longer to deploy than to produce and will be upwards of 2+ years behind on deployments sometime in the next year. That doesn't even begin to cover the lack of actual electricity to power the data centers. We have more "dark silicon" sitting in boxes that aren't close to being deployed, while a lot of actual people can't manage to buy consumer products for anythign resembling reasonable... it's kind of insane to say the least.

relation_al 6mo ago

RAM's dropping? Woohoo!

m12k 6mo ago

Remember, having the dot com bubble burst did not prevent the internet from being integrated more and more in society over the next couple decades. What it did was stop the headless investment where money was thrown at anything that tangentially could be called "online". We went from "nobody knows what this is, but everyone wants a piece of it" to "we know what it is, and we sure did pursue a lot of bad ideas when we didn't". Expect something similar to happen with AI - having the bubble burst will not stop it in its tracks, but it will change what gets invested in.

mvdtnz 6mo ago

> And independent of whether Microsoft makes money or not in their OpenAI endeavor, it kills the story: they were betting the whole growth story on AI, and if that doesn’t work out, then what’s left to justify a high stock price? Microsoft's stock price today is the same as it was in late 2021 before anyone cared about AI. What would happen? Nothing. I don't think it's a significant revenue driver today. Microsoft, like everyone else, is speculating that AI will drive profits in the future. If it all fell apart there will certainly be losers but I don't see why it would bring down Microsoft.

poopiokaka 6mo ago

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