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AI's $344B 'language model' bet looks fragile
- TNDnow 1y agoFiat money in a credit based inflationary environment is free. Oil money is free, it literally comes from the ground. There's no "losses".
- wffurr 1y agoNot sure what this has to do with the article. Oil isn't "free" anyway, it takes energy to make energy, and EROEI has been going down for some time as the easy oil is extracted.
- redwood 1y agoOracle's mega moves in the market (cpl hundred $B in market cap),due to their claim that OpenAI was doing a multi-year commit to move much of their workloads to their cloud ... likely a heavy revenue play rather than profit... with an aspiration to push as much CapEx deprecation to out years as possible (btw Oracle where is all the capex?) AKA Financial aengineering... just shows how overly leveraged this bubble has become. The Economist recently featured a piece pointing out that it's no longer risk that drives the market but a balance of fear of loss and fear of missing out (https://www.economist.com/finance-and-economics/2025/08/06/want-better-returns-forget-risk-focus-on-fear https://www.economist.com/finance-and-economics/2025/08/06/w...). FOMO is out of control right now
- jakeinspace 1y agoThis Oracle surge and revenue predictions really feels like jumping the shark. I mean, it's Oracle.... I've never felt confident enough to bet against a company, but a short position on Oracle may well be too tempting for me.
- brookst 1y agoI lost money betting against Oracle. It taught me to never underestimate the power of a sales and marketing organization, even if the product they’re selling is technically backwards.
- andsoitis 1y agoYou probably saw in the news yesterday that Oracle stock shot up because they are scoring large AI deals: https://www.wsj.com/business/earnings/oracle-stock-orcl-ai-deals-047216cd https://www.wsj.com/business/earnings/oracle-stock-orcl-ai-d...
- fidotron 1y ago> FOMO is out of control right now Exactly. The whole stock market is currently behaving like the crypto bubbles.
- amelius 1y agohttps://archive.is/2rFK4 https://archive.is/2rFK4
- redwood 1y agoThis technology demos incredibly well and you can just see how everyone gets giddy with excitement around using it. I watch my colleagues and executives proud to show what they could do or make endless jokes about it. It reminds me of when people first got their phones and couldn't stop showing everyone how cool they were. This leads to an over rotation in the perceived value.. the value is significant just as the mobile phone was, but not going to live up to the hype in the near term. It's definitely interesting how in anonymous forums there's a lot more people pointing out that they think this is hype whereas when we wear our professional hats many of us join in. It's like we all want you to party going no we all know what's going to happen
- wffurr 1y ago>> in anonymous forums there's a lot more people pointing out that they think this is hype whereas when we wear our professional hats many of us join in When your boss is hyping it up and demanding all hands on deck full steam ahead on the Good Ship AI, lots of people join in out of fear, particularly in the currently awful job market which is partly being ruined by AI itself. Some of us just stay quiet, keep our heads down, and plug away using tools actually fit for purpose, like LSPs and refactoring tools. Very few have the courage to stand up in a professional setting and say the emperor has no clothes.
- brookst 1y agoThis is true, but it is also true that traditionally, people whose jobs are most likely to be affected by technological change are not the most dispassionate, objective judges of the technology.
- geon 1y agoNo developer job has yet been lost to AI. We are in a huge recession, and companies like to have an excuse to fire people that can be spun as a positive.
- hobs 1y agoAt my company at least four developer jobs were lost because of AI tooling, but keep spouting off about the entire economy at once.
- lherron 1y agoThis “article” is clickbait. Controversial title with no substance, asking “why are companies investing heavily in a technology that works for some (limited but valuable) use cases, when they could invest in pure R&D for something that might be better someday”.
- Mizza 1y agoWhat's the path to recouping that money? Even if every major company in the US spends $100,000 a year on subscriptions and every household spends $20/month, it still doesn't seem like enough return on investment when you factor in inference costs and all the other overhead. New medical discoveries, maybe? I saw OpenAI's announcement about gpt-bio and iPSCs which was pretty amazing, but there's a very long gap between that and commercialization. I'm just wondering what the plan is.
- HWR_14 1y agoIf LLMs could double the efficiency of white collar workers, major companies would be asked for far more than $100,000 a year. If could cut their expensive workforce in half and then paid even 25% of their savings it could easily generate enough revenue to make that valuation look cheap.
- frfl 1y agoWasn't the plan AGI, not ROI on offering services based on current gen AI models. AGI was the winner takes all holy grail, so all this money was just buying lottery tickets in hopes of striking AGI first. At least that how I remember it, but AGI dreams may have been hampered by lack of exponential improvement in last year.
- weego 1y agoI think what we have right now is an excellent interface for low-friction, non-specialised interaction by humans (work or personal use) with a vast array of highly specialised and highly-complex systems. What it isn't is the actual final "thing" itself. It's just the thin veneer right now. I'm not convinced that that revolution was worth whatever trillions we'll end up spending, but fortunately that's not on my shoulders to be worried about.
- shoo 1y agoHow big is $344B? Apparently the total market capitalisation of the US stock market is $62.8 trillion. Shiller's CAPE ratio for the S & P index is currently about 38 -- CAPE is defined as current price / (earnings, averaged over the trailing 10 years) That suggests that over the last 10 years, the average earnings of the US stock market is about $1.7 trillion annually. So $344B of spending is about 1/5 of the average earnings of the total US stock market. Still hard to interpret that, but 1/5 is an easier number to think about.
- brookst 1y agoBut the $344B figure is not annualized, it’s cumulative.
- deleted 1y ago[deleted]
- shoo 1y agothe two nested bloomberg articles say > This year the world’s four largest tech firms will spend $344 billion on AI > Altogether, the four companies are expected to spend more than $344 billion for the year, with much of it going to the data centers necessarily to run AI models. so both articles frame that $344B as estimates of capex within 1 year.
- ghm2199 1y agoThese days am looking at managing my own portfolio. I go off expected returns(using gdp as a component) plus dividend and adjust it for risk to compute which country/region has good expected returns. This i adjust a couple of times a year. If one would assume it's nearly all a bubble, How would you correct earnings for the US? I am interested in applying it to any investment that tracks AI heavy companies in the US.
- shoo 1y agoIf you believe in long term mean reversion of CAPE ratio for US stocks, you'd expect price/earning multiples to contract by a factor of 2, over some hard to predict time frame, where CAPE reduces from 38 back to about 20. If we arbitrarily guess that contraction happens over 10 years, that'd be -6.7% / yr for 10 years, from 0.5^(1/10). Then add the return components you mentioned from dividends and earnings growth. One approach I've seen a few folks do is to fit a regression model of annualized real stock market returns over the next 10 years as some function of CAPE or 1/CAPE or log(CAPE). It doesn't give a very good fit on training data, R^2 in the range of 0.2-0.3, i.e. it cannot "explain" most of the variation in 10 year returns. CAPE based regression models like that have said the US stock market has been overpriced for the last decade! But investors in the US stock market have done pretty well over that period, with really good returns. Maybe these models are accurate but we've just gotten lucky? Maybe these models aren't very good. Hard to tell. Elm capital publish estimates of expected returns of a few asset classes quarterly: https://elmwealth.com/capital-market-assumptions/ https://elmwealth.com/capital-market-assumptions/
- thiago_fm 1y agoThey MUST. It doesn't matter if it looks fragile or how much money it is. LLMs risk most of those companies business, they can't afford to not be ahead. If they aren't ahead, there's a risk that the entire US's economy would be in a terrible shape. American Big Tech companies that make plenty of INTERNATIONAL revenue from Ads (Meta, Google), can quickly become a shell of its former self. How? Countries and economic blocks could quickly substitute their American products counterparts if they have nothing to offer and could roll out their own. The US's economy has become very dependant on FAANG cashflow, it's what gets other parts of the economy moving. No wonder they had a dinner with Trump. If this fades away, US will look very weak and with a terrible economic outlook.
- kingkawn 1y agoIn the same way people thought the train would hit them when cinema first debuted so too do we believe the machine is thinking
- gsky 1y agoMost of us believed that crypto currencies were trash. Look how valuable its now . LLMs are a million times better than Crypto currencies.
- Gigachad 1y agoCrypto never ended up filing those original goals of being an actual currency and smart contracts actually doing things. Blockchains and NFTs were never used to solve any of the problems they claimed to. It’s just none of that had any baring on the value of the coins.
- bjacobel 1y agoThere is a distinction between "vehicle for a large volume of speculation" and "valuable". Cryptocurrency has not created any "value".
- lm28469 1y agoPokemon cards are also super valuable these days, it says more about some people having way too much money for their own good than anything
- ninkendo 1y ago"LLM's are the next crypto!" isn't the glowing endorsement you seem to think it is.
- gsky 1y agoSuch a world we are in. Nothing can be predicted with certainty. LLMs will be a million times more valuable than crypto shit in my opinion.
- impossiblefork 1y agoIt's obviously a lot of money, and of course it's too much money, but I think we can still get LLMs much further and I think they're probably the currently most interesting approach. I don't even care about multimodality etc. I think pure text models are a very appealing idea.
- rsynnott 1y ago> Hallucinations haven’t gone away, muddying the path to adoption for companies in healthcare or legal analysis ... I mean, of course they haven't. They are a natural consequence of how the things work!
- pmdr 1y agoOne can call into question the paucity of AI-critical posts & comments here on HN. Not much is being said about the economics, everybody's living off the hope that "they'll figure it out." And AGI is just a few hundred-billion-dollar loans away, so why quit while we're ahead? If they do "figure it out" (both AGI and a viable business model), a lot of people here will likely be out of a job. If they don't, the whole thing will come crashing down, taking our invested savings with it. The comparison to crypto keeps coming up. Not everyone's savings went into crypto, but a lot of people's savings and retirement funds are being invested in funds tied to the stock market. And right now its growth depending on pumping cash into the AI bubble.
- simianwords 1y agoThe answer is so easy to solve. Do I find value in paying 20 dollars a month for ChatGPT? Yes. Do others? As far as I can see, yes. Most people are happy with the value. Are AI companies profitable if they stop R&D? Yes. Where’s the skepticism coming from?
- pmdr 1y agoI'd actually be content knowing $20 a month covers inference and makes them a decent profit, but I have my doubts. If there's proof out there that it does, I haven't found it yet. > Are AI companies profitable if they stop R&D? Yes. By what metrics? Where's the data?
- simianwords 1y agoWe're profitable on inference. If we didn't pay for training, we'd be a very profitable company - Sam Altman
- pmdr 1y agoThis statement is probably all we're going to get out of a private company that's a long way from making a profit. Personally, I'd like to see data, because I don't really trust whatever twisted definition of "profitable" Altman prefers. Until then I'll take advantage of the $20 price tag, but remain skeptical about its sustainability.
- deleted 1y ago[deleted]
- ankit219 1y agothere is clearly overhype. Given the influx of people building here (and i am not aware if it happened previously too), in a bid to differentiate from other startups building the same thing, many just stripped the nuance out of any technical idea, and made it a simple marketing term. As an exec where ten startups are promising you "training on your data" to provide the best chatbot, it's hard to tell the difference between who would be actually training and who would be just tweaking prompts. This has happened to other concepts too (anecdotally, most famous is how everyone is offering deep research). yes, it helps growth, but comes at the cost of trust. There is this startup which promised "experience based learning" when all they were doing is adding memory to the prompt to get it to perform better. (you can look it up, recenty raised series A). This does not mean ideas are not working. I personally think pretraining has done its job. We did not know what the job previously was, but now we do given the way RL works. Pretraining and test time compute enables models to develop a generalized prior they can use to solve any given problem (much like how humans solve such problems). Sometimes priors are lacking so you need to train more using RLVR, and still early days, but directionally I think we have another scaling curve here.