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- Hacker News
- It won't pay off if LLMs efficiency gets good enough to make those data centers obsolete.
It's a huge gamble.
by elmer2 - Don’t worry, they’ll get bailed outby an0malous
- no - see Jevon's Paradoxby asah
- Jevon's Paradox ("As efficiency of resource use increases, usage of the resource increases") says otherwise. One things become more efficient, we can use them in lots of ways that would not have been viable before, driving up usage.
- How about we regulate private corporations so they can't take a "gamble" that's equivalent to a private company giving everyone ferraris on the idea that they will eventually all become formula 1 drivers and give back 10x the ferrari's cost?
Even better, that "gamble" will have to be rescued by taxpayer money.
by dev1ycan - I disagree in a way, part of the reason they can't really succeed at the moment is because it's way too expensive to really deploy at scale for most companies, but even for those AI companies themselves. If they can make business access subsidized/cheap the same way pro/plus/max/whatever plan are for regular users while still being profitable, this can work out. The other solution is if they do reach that "it's so super smart it's reinventing the world every day", but that one is much more of a maybe possibly one day.
What they can't do is the rug pull of pricing like Fable did, hoping for profitability while playing the "it's so super smart" card. It's very profitable, but customer will be very happy to leave for cheaper pasture and that's why the recent news about this or that cheaper chinese models make headlines.
Essentially, the rush now is "if I make it a boring profitable company I'm not worth a trillion AND i'm overshadowed that plays the singularity card even if they're bullshitting"
by nolok - We haven't even started with a lot of things were we need a lot more compute:
Your real personal agent which knows you and helps you like "good morning elmer2, your calendar invite for dinner is today, you will need to leave at 18:18 if you want to use your normal public transport route per train. I put an alarm in your phone for you"
Agents to agents
Agentic teams.
Finetuned models for everything like Java/spanish coding model.
Very long term research like multiply hours or days or weeks and plenty of these in parallel.
by Xalutiono - Or: increasing resource efficiency may encourage even more usage, as happened with coal, oil and photovoltaics.by brainwad
- Wouldn't improving LLM efficiency make them even more useful across the board, then they can enjoy the nice economies of scale?
The plan is to have LLM working completely autonomously, in that case, the more resources you have, the better. Perhaps people will use local LLM to ask questions, or coders use them for their personal projects, but that's not where the real money is.
by pingou - It would be better if you all read the article this article was referring to:
https://asia.nikkei.com/business/technology/five-us-tech-gia...
by Noaidi - But it's behind a paywall, so not that easy
- If I were nearing retirement and had a decent pension pot where I could control it in fine detail...I would be diversifying away from tech stocks and holding some cash for immediate needs. There probably won't be much time when it unravels...I wouldn't be over exposed to the Nasdaq 100, for instance. Although you could probably pick some AI safe companies out of it.
The real problem will be figuring out where all this debt is
by jimnotgym - The problem is 1) the Nasdaq 100 is where the majority of gains are coming from, and 2) it very well might be another 3+ years before anything unravels, if it unravels at all.
If you're truly at retirement, absolutely cycle out. But if you're still young and trying to maximize portfolio growth, it's not obvious that a non-tech strategy would yield better returns.
by cj - Is that why China pushing for open weight models? If these models are on par with the quality of the proprietary ones, the US stock market will go south fairly fast, imho.by andreygrehov
- For the last 20+ years i was really relaxed about tech industry - the fat cash positions maintained by the companies as a lesson from the early 2000-s crash (when companies were running out of cash and failing or severely downsizing, etc.) almost guaranteed that the tech will easily weather any trouble times - and that was clearly demonstrated in 2008 and in 2020.
Now i'm starting to get scared - these cash positions are basically gone if matched against the new debt and various creative financing taken on for the AI buildouts. That looks a lot like 2000 - very promising tech everybody is piling money in. And i'm sure that several years later it will provide several decades of tremendous success like Internet did in the last 20 years. It is just those few initial choppy years of the hockey stick trough that we may be coming upon and that many may not survive not having that fat cash position anymore, and thus those years may happen to be very painful for the tech and for the whole economy.
25 years ago there were a lot (estimates put even as high as 95%) of dark fiber left as a result of the dotcom buildout and crash. It was successfully put back into action several years later. I wonder whether we will have similar dark datacenters in a few years.
by trhway - They're obviously not taking on enough debt because I'm paying $200 per month for one AI, $100 per month for a second, a $20 "donation" to Gemini[1] paying for a service I never use just to fund its development, and yet here I am doing my own laundry, making my own damn breakfast, lunch, and dinner and manually tracking my Calories and macros, I'm putting my own damn dishes away, racking and unracking my own damn weights at home, and taking minutes to set up and record my exercise form and then take screenshots of it of key frames that I manually ask the AI's to form check (they don't consume video natively as an input) rather than have a robot do any of the above (including act as a fitness coach) because where's my household robot I can rent on a monthly payment? Can't be that expensive, servos and pressure sensors and cameras are cheap, what's missing here is that here we are and AI can't do shit for me day to day other than knowledge work and software engineering. I'd like these companies to take on as much debt as possible and rent me a robot that can do stuff for me. I have a petition for this that you can sign here if you want:
https://www.change.org/p/create-a-physical-embodiment-for-cl...
[1] I don't use Gemini for anything ever, I pay just to put my vote to them making a useful model (I know my $20 isn't much but I apply Kant'e categorical imperative - if everyone did it they'd take their AI seriously and not be in last place behind OpenAI, Anthropic, and even open-weight models).
by logicallee - You are donating money to Google, one of the richest companies in the world?
It really doesn't need your help, and it's already way too powerful. If you have money to spare, can't you give to good causes instead?
by jraph - > Meta alone has amassed around $420 billion in off-balance-sheet debt, according to Nikkei,
Isn't this an existential type of bet?
by JohnMakin - yes and no. With 82 billion in cash and 22billion profit per year, they can easily service it for a while even if AI consumption takes a downturn.by kingjimmy
- I hope soby swader999
- Would have been nice if the article had any substantive facts in itby Havoc
- I counted all 27 stories on Futurism's frontpage and every single one was "AI bad" "Elon bad" except for 1. a story about Trump's diarrhea 2. a story about lettuce at Whole Foods
Pretty much Buzzfeed level doomscroll slop
by nylonstrung - Yup, at least a table of the on-books and off-books debt of the top 5 AI-building companies would be niceby toss1
- The article is a very shallow restatement of the conclusions in this paywalled piece: https://asia.nikkei.com/business/technology/five-us-tech-gia...by sulam
- If you're talking about dodgy accounting at hyperscalers, a larger worry might be that they are overstating profits by depreciating their assets (such as datacenters and CPUs/GPUs) too slowly.
Estimates are that this could overstate profits by tens of percent. (However, this only allows earnings to be "pulled forward" - sooner or later the servers must be written off and the accounting catches up.)
See e.g. https://deepquarry.substack.com/p/depreciation-of-gpus-betwe...
https://www.ft.com/content/0dbfe94f-2136-432c-b075-4587092de...
Michael “The Big Short” Burry:
> Understating depreciation by extending useful life of assets artificially boosts earnings -one of the more common frauds of the modern era.
by FabHK - They’re talking about accounting at big tech and not hyperscalersby aphysically
- H100 rental costs are increasing.
If anything those GPUs should not be marked down at all.
Burry is wrong.
by polski-g - Are they really "trying to hide" this debt? I think it's pretty common knowledge that a lot of these companies are using debt/bonds for funding. The debt not showing up where the author wants is a reporting formality not an attempt to hide it.by chasd00
- Yeah I think it went through the press on mass eh?
And even if you look at the debt, even companies like meta make 200 billion revenue in 2025 alone.
Isn't it good that these companies with these massive massive deep pockets invest?
by Xalutiono - It's an interesting counter to the efficient market hypothesis. "Everybody" knows about this debt. It's in the most public news outlets there are, and the word has been getting around. It's about as secret as Taylor Swift's concert schedules. Any serious investor knows about this debt.
And yet... the companies do this because it works. If they held this debt on balance sheet, the sensible assumption is that their stock values would take a rather substantial hit, and they could face other sorts of scrutiny. It works like pull-in sales works. It works like channel stuffing works. It works even when everybody knows that's what's happening. It works even when everybody knows that everybody knows that's what's happening.
There's something broken here. In an era where AIs move millions upon millions of dollars around because of some blip of a headline somewhere and every AI improvement of any kind is immediately scrutinized for its ability to be used by the financial system, it is completely incredible that the system doesn't know and react to these things. I'm not sure what's broken. My first best guess would be the increasingly mindless investment via index funds in pensions and the slow-but-ever-increasing ability of financial engineering to abuse that mindless investment, but I call that a "guess" for a reason. Possibly there's still a lot of really stupid AIs hooked up to the stock market that just look at the most basic of numbers and are easily fooled by this? But who is running such a precise combination of "huge" and "stupid" on the market? I dunno. Something's weird here.
by jerf