Considering the insane debt spending that really kicked off since the Great Recession when global debt totaled around $22T and now stands around $300T if not more.
With the AI market apparently being very close in operation to the dot com bubble it's got problems. Especially with other sectors having issues like commercial real estate and private equity. Investors in AI who happen to hold CRE & PE are going to expect returns to cover losses. And from my understanding actually getting returns in becoming a bigger and bigger sticking point for investors in AI.
PC is mostly fine, funny enough I think very few people are aware that the general scare in PC that drove redemptions wasn’t AI risks, it was that AI would be too successful. A small handful of PC funds have noteworthy exposure to SAAS entities with strong cashflows and great outlooks, but the advent of AI created significant fear that said SAAS entities would meet near term demise because of AI.
This made it’s way to media, media ran articles, redemptions started coming in, more articles on redemptions, gates get put in place, more redemptions, more articles, etc.
If AI fails to live up to its promises, then the SAASpocalyse never comes, and PC continues to have great cashflows. If AI lives up to all of it’s promises, then maybe some SAAS companies fail and a few funds (mostly blue owl and Bcred) have some losses, so investors lose money.
PE on the other hand, a lot more going on there, raised costs of capital is continuing to be a burden for a number of PE startups that frankly wouldn’t have existed absent the free money era from 2020-2022. You’ll see a few more lesser capitalized companies fold, you’ve already seen a bit of it here or there, but these things are a lot more isolated than one might think.
I work with PC and a number of other offerings, not directly in the industry but am in regular contact with the reps on these teams. My group has exposure of around ~3B split across Gcred, Blue Owl, and Bcred, although none of their software specific sleeves as concentration risk made little sense for our goals.
Would you care to elaborate on what your thoughts are, or are you just trying to sound authoritative without doing the difficult work of specifying what your concern is?
Those with something to add typically do so in their response, and those that don’t typically reply the way you did - objecting but avoiding actually articulating specifics.
You are increasingly vague for someone who’s attempting to present themselves as authoritative on the topic.
Yes, there have always been “concerns” with PC, you can look at any point in time and find some rando talking about how the sky is falling. The actual redemption surge, which is what matters, is directly tied to SAAS related concerns stemming from AI development, as outlined in my above links.
> Leila kunimoto wrote extensively
Are we being serious? I didn’t know who that was and had to google, this person? https://www.accreditedinsight.com/about
A podcaster, who “has a background in finance” and “started investing in public markets in 2000 and private markets in 2020”
This is a person running a podcast with zero industry insight lol. “Investing in public markets” Ie buying stocks, yeah me too, been doing it since I was 14, I should put that on my resume lol.
Also, holy lack of (yet again) an actual link lol.
Be serious my man, it’s becoming clear you have nothing substantive to say here and just wanted to object because you didn’t like the information.
This isn’t stress, default activity in aggregate remained static here. Again, the actual redemption surge, which was in question, was driven by the SAAS concerns with AI. The fund that kicked off the redemption trend was Blue Owl’s SAAS heavy fund, which is a higher quality tech lending fund, not a general distressed debt fund as your prior links are showing concern over.
I think it’s become clear you have nothing substantive to add, despite your show of confidence you’re sitting here referencing a podcaster and linking a random article on a few defaults. Defaults happen all the time here.
Next time, if you’re going to try and hop in one of these conversations maybe try to come prepared? Have a good one.
I can’t possibly see how this might be relevant given how absurdly vague every job title is in this industry, but it’s “Partner | Private Wealth Manager”.
I only have Reddit on my laptop and plan to be headed out soon, so rather than trying to change topics, I’ll ask again - was there something of note that you had to add? As it stands you’ve only objected but provided no substantive reasoning behind the objection. This sort of thing shouldn’t take multiple comments to articulate - which makes one wonder why you’re stalling/deflecting rather than simply articulating what your disagreement is.
I mostly operate in the mid tier uhnw space, my specific niche being constructing pension solutions for moderate sized (~10-30 owner) professional corporations, as well as other tax solutions for some members.
Oh I'm your target client - 8 figure ex-swe. I have a lot of doctor friends who probably use your services for the cash benefit plans or similar. Although they do get pitched what we joking call "dumb doctor deals" on a too frequent basis. So you charge aum based fee on these plans or flat fee?
AI sparked it, but it’s not the underlying issue that people were truly concerned about.
Post-GFC, there was a desire to move high risk lending away from the banks to protect the economy from a repeat of the GFC due to a collapse in the banking system caused by incredibly risky assets doing what they do. The solution was to offload this lending onto investors instead, which is what effectively caused PC to take off. The concern with PC is that the fundamental issues still exist, they’ve just been shifted away into less regulated and less liquid providers. People were already having major concerns regarding asset quality leading up to the AI scare (namely due to the same accounting tricks and off book deals used by PE), their illiquid nature making it hard to pull cash out from them, and whether they’d actually serve their purpose when stressed (ie not cause a repeat of the GFC).
The AI scare is just what tipped it over the edge, people were nervous and wanting to sell, but also didn’t want to redeem their positions when it was still generating high returns. The advent of AI then changed the calculus and made them all expect traditional SaaS companies (whether directly or via the PE funds that own them) to start defaulting on their debt (which wasn’t helped by people already questioning the true value of the assets they owned), which led to them all redeeming their positions immediately. That then triggered the concerns regarding illiquidity, which every knew would happen due to the nature of these funds. Suddenly, every concern was more of less ticked off and people were all sitting and waiting to see if they’d actually serve their purpose. It was the first time the PC system was put under real stress since it grew into a larger component of the financial ecosystem. It ended up holding well, but no one knew that at the time. Hence why so many people were watching and why it was being reported so much. The attention/concerns had very little to do with the AI scare, even though that was the trigger that set it off.
Private equity , Ai debt spending without real revenue, and much higher refinacing of debt plus a return of the "new" rules change for another go at 2006 guarantee a failure of the stock market
Your global debt numbers are off by an order of magnitude. It was already well over $100 trillion around 2008, not $22T so you're conflating global debt with something much narrower.
The dot com comparison also misses who's allocating capital. 1999 was retail speculators piling into zero revenue vaporware IPOs. Today it's trillion dollar mega caps with real earnings building infrastructure.
I'll give you the financing point, because it's the one part worth taking seriously. Hyperscalers have shifted toward debt and Oracle in particular is running capex at roughly twice its cash flow. So there's a real leverage question for specific issuers. But "some companies are taking on debt" isn't speculative mania, and it definitely isn't "CRE and PE investors will demand AI returns to cover their losses." That's not how portfolio management works. Asset classes are priced on their own earnings, not cross subsidized because a fund's office space is underwater.
And on returns: we're in the build out phase (laying the tracks) and the hardware and cloud providers are posting some of the most tangible revenue growth in the market.
You're doing a lot of motivated reasoning here. You obviously have a conclusion and you're reaching for whatever supports it.
The US AI industry is speedrunning government protection and IPO because at the end of the day, there isn't anything special about OpenAI and Anthropic because Transformers are public knowledge and there is no moat. The returns aren't there for businesses and anyone who says they are is in cope mode and in direct contradiction to the studies and data.
The returns aren't there for software companies because we're still in the build-out phase. Returns are everywhere for hardware companies. Does it make sense to think railroads aren't profitable because they're not showing returns while they're still laying down tracks? Once we get past that phase, then we can start debating about returns. All you're doing is speculating, which is fine.And those studies, while conducted by reputable institutions with rigorous methods, are analyzing the data we have now and projecting possible outcomes. I'm not saying you may be right or wrong.It's way too early to start saying this is all a farce and isn't going to work. We're four years into the next phase of AI technology.
E-commerce for example. Wildly unprofitable and expensive at first. Look where's it at now and how long it took to get here.
It's not a farce but the diminishing returns you experience as models scale up are becoming more apparent. The reason why LLMs had such a jump in the past few months is the harness which fixes your input and the output from the LLM, sometimes trying multiple times to get the right format (this is why people are confused they are burning so many tokens). The industry isn't worth the trillion dollar valuation because open source is simply a better format as LLMs are a piss poor product to scale (they cost magnitudes more to run than standard SaaS apps), but a FANTASTIC tool in the right hands.
Also, I am not speculating, these flaws are inherent to Transformer models but sorry for adding Machine Learning experience to an econ forum LMAO.
You're right, from what I have seen. The open source models are so much cheaper, that their minimal disadvantages in terms of output are easily offset by the costs being orders of magnitude lower. Some (I'm using Qwen on my phone) can run locally on surprisingly low end hardware, while outputting 90-95% of what the highest end models are achieving.
The future of LLMs is open source, and the only people who can't seem to see it are the ones who have sunk hundreds of billions of dollars into building the already obsolete data center size models.
There is no moat, and most of those investments will never return a fraction of what was spent.
Anthropic makes $20 billion compared to Walmart's $800 billion annually, and the two companies are valued the same on the markets. There will be a reckoning.
Exactly. The one thing you notice about all of the AI boosters is that they will handwave away all of the flaws of the architecture and the insane costs to train the models. The tech people obsessed with AI are all in a bubble, while those working at F500s and large businesses are pulling their hair out because everything needs to have an AI feature even if it makes no fucking sense. There still isn't a viable use case for the large firms, it's not a good product to sell.
We're being Elon Musked by the AI giants and it's annoying as fuck, and that's being kind. You just know we're going to have to bail these assholes out. This is why open AI offered the trump admin a stake. I'm personally livid.
You have enough ML experience to see the gears, but you’re missing the macroeconomic picture. Calling the new agentic wrappers a hack misreads what is actually happening. That "harness" is deliberate inference time scaling. It's shifting AI from fast guessing to slow, self-correcting reasoning. It burns tokens, sure, but paying two dollars in compute to autonomously finish a complex task beats paying a human forty dollars an hour every single day. The market buys outcomes, not token efficiency.
Why are you comparing LLM margins to traditional SaaS? That's a total categorical error. Traditional apps just move data between databases. LLMs sell cognitive labor replacement. A neural network obviously costs more to run than a standard SQL database, but its target market is the global service economy, not traditional software budgets. Even with lower gross margins, capturing a fraction of global labor spend easily justifies a trillion dollar valuation.
Blaming the inherent flaws of transformers assumes the tech is frozen in time. Vanilla architectures are already being phased out for mixture of experts and state space models to engineer away the quadratic cost bottleneck. You’re right that brute-force pre-training is hitting a wall, but you are dead wrong that the engineering solutions devalue the boom. They are the exact reasons it will survive. Nice try though.
The tech isn't frozen in time, throwing endless amounts of money into diminishing returns on a chatbot duct taped onto a language translation model is what will end. this is why Apple is staying an arms length away. OpenAI and Anthropic do not have a business model at their scale.
I like AI, the community creates fantastic tools and discoveries new cool shit every day. I'm against the tech bros scamming a government run and IPO.
Again, you're only focusing on chat bots to back into your argument. I don't know why you neglect to account for the whole pie. It doesn't sound like you're willing to reach beyond that so we'll never see eye-to-eye. It sounds like you are suffering from developer myopia.
Apple does not step into spaces it knows it can't be first or second. If they thought they could be first or second, they would have jumped in. They also have zero exposure to enterprise which is where all the money is. Apple staying away from this is a very Apple-thing to do. That's why they don't screw around with search despite having the most dominant phone brand on the planet.
Anthropic does have a business model. Based on the reporting we have right now, they had their first quarterly profit in May and expect to turn their first full year profit around 2028. Additionally, they're sales revenue is growing faster than Zoom during the pandemic, and Google and Facebook in the run-up to their IPO. They're actually doing it right by not going overboard. OpenAI is a different story because we don't really have any hard data on their financials. I'm not going to speculate on their financials.
Because they were given compute resources by xAI for a few months, and were seen as "the good guys" while the govt was attacking them. I don't know why it's so hard for y'all to comprehend how ridiculously unprofitable these companies are, and that their product in a corporate environment is not very good. It's given shitty developers the ability to look like they are actually doing work, instead of building mountains of tech debt because of the fatigue within corporations to push at 10x.
> It was already well over $100 trillion around 2008, not $22T so you're conflating global debt with something much narrower.
I had the same gripe and decided to just leave it be, but I think they meant to write 220 trillion.
Still, global debt hasn’t really grown much faster than GDP. The figures are all over the place as some use private and some only sovereign, but overall the increase in global debt/gdp has been fairly modest across the last ~20 years. It’s happened for sure, but not some crazy surge like OP suggested.
It wouldn’t have been 22T in any capacity, I think ~220 is about the right figure for the timeframe you’re referencing.
But yeah, there’s no direct official stat on this so you’ve got to sorta peace meal it, and doing that leads you to different people using different composition at different times.
In '08 the US national debt stood at around 10T, and it doesn't really pass the sniff test to me that in '08 the USA alone accounted for ~half the total national debt of every country combined.
That’s difference is largely due to economic growth. You’re better off looking at debt to GDP, which back then was $4.7tn in today’s money and is currently $121tn. We’re not quite 3x now, but back then we were around 5x. Still concerning, but it’s not worse than it was then, let alone much worse like you’re perhaps accidentally implying.
We are basically watching a new .com bubble - assuming this LLM method actually pays off. Most of these early movers will get buried in debt trying to take the lead. But as all the first/second generation attempts face plant, later companies learning the lessons and not overly leveraging themselves will take the reigns down the road.
Pets.com failed in 2000 - but today we have Chewy. In 2000 we had Kozmo that failed - now we have like 20 instant delivery services.
I think the smart players are carefully in the game now and waiting to push hard until profitable models and pathways become apparent. The overly leveraged first movers will mostly fall away.
There is always a success or two with early players (Google, etc in dot com bubble) - but many won't make the cut. Gonna be a crazy next 15 or 20 years and I wish I cpuld see how it plays out.
LLMs are helping, sometimes a lot, but in weird ways (that might backfire later). My worry is more that if will destroy the job market because HR and CEOs will stop hiring toi early.
What? Do you realize the companies behind LLM already make billions of dollars in revenue? Do you understand that LLMs is already used extensively by all f500 companies?
People disagree on the VALUATION of AI to the economy and in particular the FUTURE value of AI but there is absolutely no doubt that this is already a multinbillion dollars business in 2026.
I wouldnt bet against Anthropic, they are so far ahead of the competition that if any one company could quadruple their price and still retain customers, it very well could be them and them alone.
So very few companies open their books (If any) but I would be willing to bet a HUGE portion of the expenses are capex expenses to continue the arms race of staying ahead. (Training new models)
Older already trained models could very well already be profitable. Anthropic likely could just stop training their new models, or dramatically slow the pace, and milk Opus, Fabel, and Mythos for at the very least revenue neutral.
While I agree that a LARGE majority of AI companies are doomed, Anthropic specifically, I am betting will be one that survives the culling and comes out on top.
Google seems to have been investing a lot of time in effort in making training more efficient. They announced earlier this year a new algorithm to optimize RAM use in model training. I would hope all the major players are looking for similar efficiencies to reduce their hardware expense.
I do think there is one major difference between what we see with AI today, and the dot com bubble. People and companies thought the dotcombubble was the new norm brought about by this great new tech revolution, and that it was there to stay. Im very certain AI companies know they are on borrowed time, they say it all the time.
Lol they are purposely unprofitable because a) investment costs upfront are huge b) they are fighting for a market share. This is the same playbook every single tech company has played in the last 30 yrs.
You think LLMs are here to stay but the two leaders in the field are somehow going to fold? Yea, don’t bet on it.
That is exactly what the dot com companies were saying.
And yes, Google and Amazon got through it. Amazon was particularly unprofitable. But they also pivoted and tried a whole different approach to other retail companies online by building their own logistics system.
Oracle is taking out bonds so fast right now if there is an AI hiccup their junk rating will be the stuff of legends.
The AI bubble is not just the out front LLM guys. It is also everyone behind them hoping this architecture works ar the scale they are hoping it will.
Because the people hyping LLMs are in full cope mode that corporations aren't seeing a return for their investments into AI. the token based pricing change was a wake up call, now the hype idiots and bots need to double down to defend the sunk cost fallacy.
The .com companies did not even generate revenue. There were few customers and little demand. Pets generated something like 100m in sales their last year before the crash.
I would not be surprised if OpenAI loses out, but Anthropic is the one AI company I would be surprised to see die off (doesn’t mean it’s not overvalued). They are already profitable and finding many ways to provide genuine value as well. The rest are focusing on building better LLMs, and while Anthropic is still doing this, they are more focused on making the models actually useful. It’s why enterprises and individuals are willing to pay them a lot of money to use their services, but not other AI providers, which is ultimately how they are profitable.
Microsoft and Google is also tackling it from a smarter position too, instead of focusing on building an LLM at all, they’re leveraging OpenAI’s and Anthropic’s models to add more value to their existing products. Companies that are focusing on using LLMs to add value are likely going to end up in a strong position, and Anthropic is currently not only leading that race, but they also have a lot influence over every other company doing this. Then there’s Amazon, Nvidia’s, and SpaceX’s strategy which is focused more on the infrastructure side of it (something Google is also involved heavily in), and effectively being the ones selling the shovels to the gold miners. They’ll make a lot of money off of this in the short term, but eventually this will die down. They won’t disappear, but they are likely at their peak already.
The bigger concern for Anthropic is how healthy they are when they come out of this. They will likely come out with a lot of debt, and that will significantly hamper any further development that they can do. Depending on how big their advantage is, you may find another company can somewhat easily rebuild their technology without all of the debt by leveraging Amazon’s and Google’s data centres. If they can get to a roughly similar level without the debt, that better financial position will lead to them quickly overtaking Anthropic in the future. It all depends on a) how easily replicable Anthropic’s technology is, b) how much debt Anthropic ends up taking on, c) how profitable they end up being once the development race cools down, and d) how much development costs come down. These things can go either way and will likely decide Anthropic’s future.
Ai isn't making money. We can disagree on valuation all day, but the fact of the matter is that AI costs more to run than it can charge to make up that difference. It's already bankrupt, and all but the smartest players have poured terminally critical amounts of money into it.
These companies can't cut their losses without losing their businesses, and they can't get that money back without going for broke. The ai market is failing, and the only way to survive the crash is to hope and cope.
AI may or may not fail, who knows, it kinda really doesn’t matter. Anthropic and OpenAI are just IP shells being funded by big tech, so all the actual financial burden goes on big tech, right?
AI infrastructure spending last year was ~320B, this year it’s anticipated to be ~480B. That sounds like a lot of money.
Facebook, Google, Amazon, and Microsoft have combined cash on hand of ~550 billion, and combined annual operating cash flows of 430 billion. That’s a trillion dollars of literal just cash spending power across one year. Moving forward, that operating cashflows is another half trillion dollars every year.
If AI has massive returns over time then fantastic, all of these companies will be rolling in cash, if AI ends up being equivalent to lighting cash on fire then congratulations, all of these companies will still be rolling in cash.
Everyone looks at the liability side, everyone seems to be ignoring the balance sheet and cashflows.
I've learned to respect your takes so I'm curious what yours is on how they get profitable?
Yes they're burning money to try and get the infrastructure in place and what not and they can afford to do so with the money they make elsewhere in their businesses. However, from my understanding every new model they create becomes more expensive to run than the last one, not less. Requiring ever larger and newer data centers, (3-5 year life span from what I've been told) Even now the current models are too expensive to offload the true cost onto the consumers so the AI companies are running at a loss. The new models are not going to be cheaper, they're going to be more expensive, so where is the consumer going to get the money to pay for the even more expensive model that may eventually deliver on the productivity promises that so far with the insane spend and drive to utilize it have failed to deliver?
Unless your idea is that they just permanently subsidize AI in perpetuity they need to figure out a way to make money with it or the spending bubble holding up the industry will pop. Every person outside of the AI space, business leader or not, that I've talked to about it's productivity promises says it's just not delivering.
I was using Chatgpt for work and I've been burnt a couple times by hallucinations, even when I gave it a document to pull it's info from it still got it wrong. I've cancelled my subscription because I have to double check everything it gives me anyway.
So I think when people are describing it as a bubble they're not strictly speaking of a debt bubble to pop, although that's still possible for some of the companies in the space, what I think they're talking about is the spending relative to return on investment bubble that will pop. AI spend doesn't increase productivity at even a 1:1 ratio.
For every dollar spent on AI build out we're not seeing a dollar in increased productivity and I don't see a path for that to change. We have a mountain of shovels for a gold rush that doesn't exist.
Yeah, I mean to be honest I’m not sold on the idea that AI will be some massive return on investment for these guys, it might turn out that a lot of them ended up burning through a lot of cash for what amounts to some pretty mediocre ROI.
I’ll be honest, I don’t know enough about the tech progression of AI to have good input on what those costs would look like over time. I’ve heard from some authorities in that world whom I respect that the costs should subside as models are fully trained, but I’ve also heard the opposite, I think it’s a lot of guesswork tbh. I also think a lot of the very confident people commenting on where those costs will trend are presenting speculation as expertise (even those in that industry).
I doubt it’s permanent subsidy, but it’s quite possible that you end up with a few big winners, and a company or two that’s burned through half a trillion dollars with not a lot to show for it, those companies will be fine, but certainly not very happy about burning through said cash for nothing.
As far as AI and it’s workplace uses, it’s a mixed bag, part of the reason why tech bros are so enamored with AI is because it’s like genuinely very very good at doing their job. Its coding ability is fantastic, Claude can build you a whole website in a short period of time with very little necessary in terms of revisions - so tech bros see a model doing the thing that made them in to a billionaire with ease and (incorrectly) assume this model can do all sorts of highly intelligent work. But at the same time, asking Claude to schedule a dinner with two coworkers has it flailing wildly, it can’t fill a fucking PDF, and it’s about as good at researching a given topic as an unpaid intern.
And to your point, the hallucinations are never really going to go away, they can’t, hallucinations are inherently part of how AI works. This is a really really dumbed down summary, but all it’s doing is being a big statistical word generation engine. That inherently has hallucinations, it can’t not.
I think the future use cases for AI will be heavy in tech, but also heavy in replacing the sort of mindless busy work that everyone hates - data entry, transposing info from place A to place B, summarization and analysis of specific documents, automation of task generation, etc. That’s valuable, but it’s not going to render humans obsolete or anything.
Between here and there a lot of companies are certainly gonna waste money on AI, either through investment or through tokens that don’t result in increased productivity, but all of that doesn’t really need to amount to crash type dynamics. It’s buying the expensive car you don’t need, not mortgaging your house for a business that fails.
> And to your point, the hallucinations are never really going to go away, they can’t, hallucinations are inherently part of how AI works.
Minor quibble, but this is inherently part of how generative AI works. One of the great casualties of the recent boom is conflating AI, which we've had in various forms for many years and does great work in many domains, with LLMs.
It’s not just generative AI. Hallucinations are caused by non-determinism which isn’t an uncommon feature in neural networks. There are a lot of AI models that are deterministic and won’t hallucinate though, just like there’s plenty that are.
> Its coding ability is fantastic, Claude can build you a whole website in a short period of time with very little necessary in terms of revisions
It's very good at filling in the blanks in a way that plausibly seems to work, and if you know what you're doing you can have it iterate until it even passes tests, and if your tests are any good you may just ship adequate products. What it is terrible at doing is architecting good solutions and generating an efficient, reasonably readable amount of code. Someone who really understands architecture and trade-offs and knows where they're trying to go - someone experienced - can use these tools very well. Newbies can't use them for shit in any practical way once a project grows above "tiny" because they don't know how and they can't audit the results, and if it plausibly works they just move along, leaving behind something entirely unmaintainable. The real magic is not vendor lock-in per se but tool-class lock-in; the only feasible way to maintain LLM-written codebases of any size is to keep paying for LLM tokens. And like you said, a lot of companies are going to waste enormous sums of money finding this out the hard way.
I generally expect the explosion of LLM usage to be like the explosion of computer usage: Some jobs go away due to being too easy to automate; the automation means a lot of tasks become affordable enough that new industries are suddenly feasible, and they staff up. A lot of churn, but overall I suspect it's not going to cut white-collar employment in general.
This is the take that most aligns with what I’ve seen and read as well. In general it’s a weird discussion to try to have - either someone is convinced it’s a total sham and the market is going to crash to a point of people jumping out of buildings, OR AI is the most amazing thing that can do literally every single job and we humans will soon be obsolete. When the answer lies somewhere in the middle.
In general with most things the answer lies somewhere in the middle, unfortunately as forums grow there tends to be a decline in technicality and an increase in binary thinking - so more and more topics are boiled down to the extreme binary, and most participants interpret any discussion of that vast middle ground to be someone taking the opposing end of the binary.
LLMs are definitely useful, but we're now at the point where there are literally 10s of thousands of open source models out there that can be implemented on varying levels of hardware, depending on your needs, very easily and cheaply.
Nvidia is already building enterprise hardware (machines that cost in excess of $100k) that companies can use to drive internal LLMs at scale, using whatever model.
As hardware continues to be oriented towards and optimized for LLMs, I think you're going to see them prevalent as plugins and tools for specific use cases. They'll be ubiquitous and cheap, and there will be no need for the likes of the companies that first brought these to market.
I'm a bit fuzzy on specifics of how we got here, but my understanding is that LLMs were reverse engineered, and as a result, they're basically a dime a dozen at this point. On the open source models, you see near parity at the higher end of things as compared to what the LLM companies offer.
Remember the panic when DeepSeek first arrived on the scene? That's the direction things have been rapidly heading.
The next big innovation in this space is going to be automation, where you can give an LLM instructions and it just does whatever you ask autonomously. This already exists, but it's not widespread or without many hurdles.
I've been tooling around in the open source space. When I first understood exactly what these things are, what they do, how they work, and how they use resources, my sentiment shifted very negatively - at least towards the specific hype from the sector.
I agree with what you said about usefulness in certain areas, like programming. I don't think this translates to the value they're trying to sell the public. In case it needs to be said, this stuff isn't actually AI, and it never will be. This is why I was careful to only use the term LLM. We're dealing with what is the equivalent of a very sophisticated, internet enabled T9 model, which was the genesis of the LLM, ironically (or perhaps not).
So basically your saying that even if it is a bubble (debt not involved) and they're never going to get anything close to an ROI of 1:1 that it's fine economically if these companies spend an insane amount of money on it and get nothing back?
Like yes I understand that AI isn't going anywhere and I'm grateful I don't have to spend an extra 5 minutes formatting my spreadsheet and emails (it's not even worth it for that with what it costs now but I whatever), but how does pouring a trillion dollars into something that doesn't work, mean it's not a bubble, and when the real value / cost becomes apparent there will be no negative economic effects downstream?
I understand that the global financial crisis of 2008 was bad because it hit banks and banks are a pillar of the economy but in this case because it'll only affect the balance sheets of the AI companies it doesn't matter? Is that your position?
Profitability of the models isn't a fully economic issue, but a Machine Learning one as well. Models get prohibitively (EXPONENTIALLY) more expensive to train as you increase the parameter count, this is a trait of all Transformer models, including LLMs. Those who are tunnel vision econ brained don't understand this, so the industry has been able to bait crypto / block chain idiots into a brainless cult, over a technology they don't understand.
Essentially, the money furnace is going to shovel more and more dollars into it to the tune of multibillions per model, and China will continue to devalue the ketamine coke heads in the Valley.
It’s always funny seeing SWEs and CSs “correcting” economists on their economic insights on the basis of them not understanding technology, all while demonstrating that SWEs and CSs don’t understand economics. A lot of SMEs need to learn to stay in their field (a common problem for expects in every field), just because you’re an expert in 1 field doesn’t mean you’re an expert in every other field.
AI/ML/statistics, the internet, software, computers, etc aren’t the only technology that exists or was developed by people. They’re also not the only technology that gets exponentially more expensive to develop either. In fact, nearly everything becomes exponentially more expensive to develop. It’s not a unique issue with AI, and it’s certainly not a new issue faced by economists either. The result, from an economic standpoint, is always the same. There is an equilibrium point between how much you spend vs how much you get in return. As the costs become exponentially more expensive, eventually every $1 you spend generates under $1. With new technology, it takes firms some time to find this equilibrium point, and those who overshoot it will make a loss. But it will eventually be discovered and firms will not spend beyond that because it’s economically prohibitive to do so. The initial development costs are also always the most expensive, eventually development (and hence spending) will slow down as a result of this nature. This is all well understood, and ML isn’t any different. Yes, it gets exponentially more expensive to improve, but they won’t spend beyond what’s economically feasible.
Also, it’s very easy to underestimate how much economists actually understand this technology. Not only do they have a very strong understanding of how technology in general impacts the economy, but ML is one technology that they have a particularly good understanding of. If you’re talking about the internet or software, most would have 0 clue about the actual technology. However, economists have been using ML for decades, and are one of the fields that have significantly contributed to its development. There is a whole field of economics, econometrics, that has specifically been looking at the intersect of ML and economics for decades. Most major economists have studied econometrics to some extent, and every economists is not only aware of it, but will rely on it for their insights. They mightn’t have as strong of an understanding as mathematicians, physicists, data scientists, etc but they do still have a good understanding of it. More so than any other technology. Your argument still wouldn’t apply to a technology they’re clueless about such as software, it still follows the same rules as any other technology. However, it’s particularly naive to criticise them for not understanding this technology because it is one that they have a strong understanding of.
imho, there is only 2 near term threats - rise of alternate algorithms that are not heavy on compute/memory, chinese or any open weights models that corporates are willing to bring to private cloud.
Having exposure for my retirement - this cash level you mention above and revenue (aka token annuity) is what I need to pay attention. Maybe Q1 '27 is something to plan for
Pets also wasn’t the cause of the dot com collapse. It was overbuilding of infrastructure (fiber, bandwidth, etc) which led to a price collapse on those services (no profit to be made) which caused the whole thing to implode. They missed the entire plot.
The problem is most of the people on this site are nearly financially illiterate - so they translate their sentiment regarding AI’s viability as a product directly to their understanding of financial outcomes, and that’s just a bad take.
All of this whole “dotcom bubble 2.0” stuff comes from people unable to read a balance sheet. If all of the collective debt accumulated by these major tech firms comes due tomorrow with precisely zero corresponding revenue attached not a single one of them would flinch.
Here’s a quick example, Microsoft, who has been positively burning through cash on AI commitments, has spent ~80B in 2025 on AI build outs, much of that actually being future capex commitments and not immediate spending. They currently have 78B of cash on hand. Their annualized FCF (after AI spending) over the last 12 months was 72B.
Presuming their AI spending has an ROI of 0%, they will at worst just not raise dividends for a few years.
Amazon has the largest capex on AI of anyone, currently at around ~200B. (Forward commitments). Amazon currently has ~143B of cash on hand, and has operating cashflows of 148B/yr.
You can do this same excercise for all of the other big players here - Meta, Alphabet, Oracle, whomever.
All of the sentiment you see on Reddit is easily proven naive by simply referencing two figures for each company - operating cashflows and cash on hand.
Imagine a guy who makes a million dollars a year spending 200k/yr on hookers and blow. Waste of money? Maybe. Will they go bankrupt? lol be serious.
But that’s where the money is coming from. Look at Anthropic’s funding partners, they’re in series H now (which is hilarious), and the list is basically major cash flush PE like Altimeter and Sequoia or Amazon, Microsoft, Google, NVIDIA.
Same with Open AI, Microsoft is the largest single backer, with SoftBank, amazon, etc behind that.
Sure, they’re the names, but the cash flow backing is the balance sheets of these big tech companies that are just printing cash left and right.
If you look at the actual data center buildouts, it’s almost always something like a holding entity that borrows 50B to build a data center, that data center is leased by Meta, and Meta is going to lease that computing power to Anthropic, Meta signs something like a 50 year lease covering the costs plus their exit agreement guarantees full buy out of any financial losses should Meta exit the lease early - so basically it’s Meta’s liability, and backed by their balance sheet and FCF.
The problem with these conversations on Reddit is that people are unable to differentiate their sentiment towards the success of AI as a product set and their understanding of financial risk. AI may prove to be completely useless, who knows, the balance sheet risk here is still minimal with almost all exposure matched by current cash on hand or at worst cash on hand + one year of FCF.
For most of these build outs it’s something like a company with 100B of cash and 100B of FCF committing 200b across a decade moving forward. Waste of money? Time will tell. Dotcom bubble? Be serious lol.
Great insight btw, based on what you’re saying would they be able to keep spending on AI infrastructure regardless of whether demand for the compute power ever materializes? The reasoning being the financials being undergirded by things unaffected by AI demand and not just a circlejerk of Nvidia being cash flush from the demand and cash injecting to keep the music playing.
> based on what you’re saying would they be able to keep spending on AI infrastructure regardless of whether demand for the compute power ever materializes?
As in do they have the financial capacity to do so? Yes.
Microsoft, Amazon, Facebook, and Google combined have operating cashflows of 556 billion dollars. Combined they have current cash on hand of 430 billion dollars. That’s effectively a trillion dollars of cash available across the next 12 months, then another half trillion every year after that.
In 2025 global AI infrastructure spending was something like 318B.
Now Oracle is having it’s own problems, as mentioned in the article and as observed in their financial statements, they’re still very stable but generally betting a lot trying to keep up.
But yeah, is it a good business move? IDK, time will tell but ultimately I’m not super confident that this will be a great ROI. But low ROI is leagues away from dotcom bubble territory. Everyone in this sub seems to be just intentionally ignoring the massive financial strength in tech right now.
Basically, this isn’t your neighbor drowning in credit card debt that they can never pay back, it’s your wealthy neighbor buying a Porsche that might sit in their garage and never get used, but won’t stop them from having the biggest Christmas party every year moving forward anyway.
Basically yes - almost everyone who is ranting about a bubble is only looking at liabilities and revenue for the AI companies directly, they’re not looking at where those liabilities sit and what cashflows back them.
Might it be a gigantic waste of money? Sure. But people need to decouple their thoughts around the viability of AI from their understanding of big tech’s ability to literally just light cash on fire and be fine.
Basically, if you see someone on here talking about AI bubbles or whatever and their post has zero mention of cashflows, cash on hand, etc then it’s very safe to assume they don’t really know what they’re talking about. Can’t discuss liabilities and ignore assets and income.
Like he says at the end, some will fall and some will continue, and it’s impossible to predict who will continue at this point. But I sincerely hope the government does not bail any of the failing companies out. I know it’s not too likely at this point, but it is extremely concerning if Trump is going to bail Oracle out.
I fundamentally don’t think companies should ever be bailed out by the government. We need to let the natural selection of firms work. Poor management should lead to the demise of those firms.
Oh yea, that was definitely odd, but was it a bailout?
I would not put it past Trump to try and give Ellison billions of taxpayer dollars, but I don't think the government (when Trump isn't at the wheel) does the bailout thing all that often.
The more present money you take, the more future money you better make. That's the crux of AIs problem is not that it's not nifty, it's that the scope of future expected profits are so massive. The bigger the market share, the more variables and ways it can go wrong.
Social Security is absolutely running on borrowed money. The payroll taxes that fund it directly can't cover the benefits we're paying out, which is why the Social Security trust funds are being rapidly depleted.
Those trust funds bought into US Treasury bonds back when there was a payroll tax surplus, and the Treasury pays out on those bonds by selling even more bonds.
The fact of the matter is that this is not a problem we can solve without the middle class sacrificing a whole lot of their purchasing power. Social Security is funded by payroll taxes, not income taxes. You can raise the wage cap to help stave off the inevitable, which will directly impact highly paid, upper-middle class professionals like doctors and lawyers and engineers, but it will not "fix" the system. We have an increasing number of beneficiaries, and a dwindling number of wage-based workers to support them. We will have to raise payroll taxes across the board to avoid insolvency, and that's a tough pill for Jack and Jane Mainstreet to swallow.
All money is borrowed money. This has been well understood for a long time in history. Of course forgotten, remembered, and attacked, but it has been known.
There is a reason that all of the biggest players are trying to IPO at the same time. They haven’t found a path to profitability. Ed Zitron, David Gerard, Eli the Tech Guy, and many other tech centric folks have been echoing this for over 2 years. They are out of VC money, and the banks are not willing to cut them any more lines of credit. Even SoftBank couldn’t get additional loans to cover OpenAI’s attempted IPO valuation.
Now they are doing what tech always does when they realize they have a dud; they are dumping their failed investments onto retail investors, packaging up their mistakes as ”opportunities” and using the public as exit liquidity.
Ed's point that I thought was salient is that tech has no plan B. If they did, there would be something in the hopper besides AI. Because no one has any other good ideas, they are all chasing the same rabbit. Metaverse, Apple glasses, self driving, yada yada, they really don't have any true game changers that can actually function.
This is fine! The problem is that techs mode of operations is that they always exponential grow and scale. If the product is good, exponential is a money printer. If the product is not, it's very very destructive.
At some point everything that was tech turns into legacy. John Deere and Railroads and Radio used to be tech and then they transitioned out.
You have to understand that a lot of these tech moguls truly believe that the only "future" we have is to build a perfect AI robot species to replace us, since we cannot functionally explore space in our fleshy pink bodies evolved to be suited on earth's environment.
So they literally do not care how much they destroy now to achieve this AGI that will take over the world. They think that this is the only future possible, the only future that matters, and they will kill billions to make it come to fruition.
They are in a cult. The only cult worse than believing that you know god is this AI cult where they think they can build a god from scratch. That's the ultimate act of hubris a human can commit.
Anyway look into TESCREALism and in particular Peter Theil and why he doesn't think it matters if humans go extinct, be he plans on replacing us all anyway. They want to dictate where our future is headed and that's why they don't have another plan in the wings. They're all in on this gamble because they truly believe they already know what's best for the future of humanity. It's part of why they want the US to collapse so they can buy it up and run "Network States." Look up Network States too while you're looking up TESCREAL.
I think something else that is worth pointing out is that technology went from solving problems to fabricating their solutions.
NFTs were supposed to solve digital ownership; they didn’t. AI is supposed to be cutting employee costs; it doesn’t, and in fact, it is more expensive as token prices rise. WeWork was supposed to solve expensive commercial real estate, AirBnB was supposed to solve overpriced hotels, Cryptocurrency was supposed to replace banking, etc etc. All of these things promise the world, but over time, just actually become shittier, less viable versions of existing systems.
And so to piggyback off your point about ”No plan B”, I think it is less that there are no interesting problems to solve, and more that tech is no longer interested in solving problems. Instead, it has become entirely about how to make as much money as possible only, regardless of outcome and with the least liability. There are so, so many problems worth solving; tech just has no interest in doing so.
WeWork was in no way technology, it was just real estate with a fancy website. The absolute brilliance of the guy was he managed to fool a bunch of people into thinking they would get tech-company returns investing in shared office real estate.
And there's nothing wrong with shared office space, tons of small businesses rent shared office space. They don't need or want to lease a larger space, they want like 3 offices and a combo printer copier fax machine that usually works. Making that process simpler and more standardized is totally reasonable, and solves a problem, but the hype surrounding wework solves no problems other than the relative poverty of a founder and maybe a few execs.
"Plan B" is ... keep iterating and getting incremental improvements, while working on various ideas that may or may not pay off. For some that means iterating by adding more ads and trackers into web traffic, for others it means making new products that are somewhat better than old products. None of that would stop if these bets don't pan out, except the ones who wasted all their money and ruined their engineering culture.
We shouldn’t take people’s opinions seriously because they aren’t willing to lose money betting against billion dollar movements, backed by the banks, the government, the oligarchs, and Wall Street? What kind of hare-brained take is that?
They are 3 ordinary people speaking out against the media machine that is serving as a megaphone for the very oligarchs that have a vested interest in their message being believed.
I guess we just shouldn’t listen to people unless they are wealthy.
These people are grifters. I don't believe they are genuine and I am using their unwillingness to put their money where their mouth is as an example. And I am not saying they ought to bet large sums of money. I'm sure Ed makes quite a lot of money on his blog and speaking gigs, so him putting up a public $1,000 bet would show that he's serious.
They'll tell their audiences that these AI companies are collapsing imminently. They make grandiose claims about how Anthropic and OpenAI are doomed. They also maintain that AI isn't improving over these past few years, but newer models continue to prove them wrong. Not that they will ever acknowledge this in any way.
It always cracks me up when someone makes a bad point, and then just immediately turns to ad-hominem and MAGA accusations. Just blocking your stupid ass; not worth engaging with bad faith comments.
Is it getting tiring watching people wake up to the bullshit that Altman and Dario are pulling? Everyone including you clowns are noticing the money warnings start to pile up. If you really need to jerk off to an LLM, the smaller local models are free and don't put a multibillion dollar hole in the economy.
The entire world runs on borrowed money. Since the 1600’s and the rise of central banking, the world has leveraged itself for exponential growth. From 5000 bc to the 1600’s our world advanced, but slowly.
The exponential arc of advancement in the last 500 years has only been made possible through debt financing and fractional reserve lending. The fact people don’t tie those two things together is pretty crazy to me. Our world requires debt. It’s not the boogeyman. It’s necessary to leverage for advancement. Historically, our growth has exceeded our debt. That’s the idea.
Yes, but normally you go through a rigorous process with the banks to buy a house, etc. And you borrow against your future income.
In this case...... a helluva lot of money have been thrown into a pit with some sort of prospect there will be great income at some point.... an income that will never come.
And now we're being forced by companies/financial institutions to use it, in a way to save the card house....
That’s not the point of the article. The article is pointing out the unique role debt is playing in the current AI investment cycle, particularly the way it is becoming central to firms that historically have financed their CapEx with cash flow or equity and the larger risks this poses to the economy. And as the article gestures, AI revenue growth is not keeping pacing with spending growth. It’s not even close. The hyperscalers and AI labs are losing money with AI.
I’ll repeat what I said, it’s a conversation of relativity. Big today doesn’t have to equal big 25 years from now.
Same cycle repeated over and over again. The only difference is the relative scale.
If you read the article beyond the headline you’ll likely see that there are levels of debt that are low risk and that enable rapid growth as well as levels of much riskier debt that are more likely to lead to financial crises.
That’s a conversation of relativity. The debt spending of the 90’s and early 2000’s led to crash and financial crisis, but 25 years later that technology has completely transformed the world we live in.
Zoom out and you’ll see from a large scale macro perspective this is exactly as it’s designed to happen.
When this bubble does pop, we'll see consolidation in the AI space to only a couple of major players who manage to scoop up as much AI tech and R&D as they can. THAT is when we will see AI truly start to displace human workers, once its scalable at cost.
Butane9000 | a day ago
Considering the insane debt spending that really kicked off since the Great Recession when global debt totaled around $22T and now stands around $300T if not more.
With the AI market apparently being very close in operation to the dot com bubble it's got problems. Especially with other sectors having issues like commercial real estate and private equity. Investors in AI who happen to hold CRE & PE are going to expect returns to cover losses. And from my understanding actually getting returns in becoming a bigger and bigger sticking point for investors in AI.
ND7020 | a day ago
And the PE and private credit industries are simultaneously having their own rumbling warning signs
RIP_Soulja_Slim | a day ago
PC is mostly fine, funny enough I think very few people are aware that the general scare in PC that drove redemptions wasn’t AI risks, it was that AI would be too successful. A small handful of PC funds have noteworthy exposure to SAAS entities with strong cashflows and great outlooks, but the advent of AI created significant fear that said SAAS entities would meet near term demise because of AI.
This made it’s way to media, media ran articles, redemptions started coming in, more articles on redemptions, gates get put in place, more redemptions, more articles, etc.
If AI fails to live up to its promises, then the SAASpocalyse never comes, and PC continues to have great cashflows. If AI lives up to all of it’s promises, then maybe some SAAS companies fail and a few funds (mostly blue owl and Bcred) have some losses, so investors lose money.
PE on the other hand, a lot more going on there, raised costs of capital is continuing to be a burden for a number of PE startups that frankly wouldn’t have existed absent the free money era from 2020-2022. You’ll see a few more lesser capitalized companies fold, you’ve already seen a bit of it here or there, but these things are a lot more isolated than one might think.
Cool-Truth211 | a day ago
That’s not what drove redemptions, do you even work in PC
HowdyDiarrhea | a day ago
He's a full time Reddit commenter
RIP_Soulja_Slim | a day ago
I work with PC and a number of other offerings, not directly in the industry but am in regular contact with the reps on these teams. My group has exposure of around ~3B split across Gcred, Blue Owl, and Bcred, although none of their software specific sleeves as concentration risk made little sense for our goals.
Would you care to elaborate on what your thoughts are, or are you just trying to sound authoritative without doing the difficult work of specifying what your concern is?
https://www.bloomberg.com/opinion/articles/2025-11-24/ai-private-credit-blue-owl-is-the-sum-of-all-investor-fears
https://www.wsj.com/articles/software-fears-drive-redemption-requests-for-blue-owl-tech-focused-bdc-492496ab
Those with something to add typically do so in their response, and those that don’t typically reply the way you did - objecting but avoiding actually articulating specifics.
Cool-Truth211 | a day ago
There were concerns about PC long before SaaS-pocalypse, Leila kunimoto wrote extensively
RIP_Soulja_Slim | a day ago
You are increasingly vague for someone who’s attempting to present themselves as authoritative on the topic.
Yes, there have always been “concerns” with PC, you can look at any point in time and find some rando talking about how the sky is falling. The actual redemption surge, which is what matters, is directly tied to SAAS related concerns stemming from AI development, as outlined in my above links.
> Leila kunimoto wrote extensively
Are we being serious? I didn’t know who that was and had to google, this person? https://www.accreditedinsight.com/about
A podcaster, who “has a background in finance” and “started investing in public markets in 2000 and private markets in 2020”
This is a person running a podcast with zero industry insight lol. “Investing in public markets” Ie buying stocks, yeah me too, been doing it since I was 14, I should put that on my resume lol.
Also, holy lack of (yet again) an actual link lol.
Be serious my man, it’s becoming clear you have nothing substantive to say here and just wanted to object because you didn’t like the information.
Cool-Truth211 | a day ago
https://www.lincolninternational.com/perspectives/articles/silent-defaults-in-private-credit-the-unspoken-struggle/
Stress started full year before SaaS-pocalypse. The answer is asset quality
RIP_Soulja_Slim | a day ago
This isn’t stress, default activity in aggregate remained static here. Again, the actual redemption surge, which was in question, was driven by the SAAS concerns with AI. The fund that kicked off the redemption trend was Blue Owl’s SAAS heavy fund, which is a higher quality tech lending fund, not a general distressed debt fund as your prior links are showing concern over.
I think it’s become clear you have nothing substantive to add, despite your show of confidence you’re sitting here referencing a podcaster and linking a random article on a few defaults. Defaults happen all the time here.
Next time, if you’re going to try and hop in one of these conversations maybe try to come prepared? Have a good one.
Cool-Truth211 | a day ago
Your entire agenda is to try and shoehorn PC default and PIK as a result of one bad egg
It’s the whole industry
Calm_Situation_1131 | a day ago
What is your job title?
RIP_Soulja_Slim | a day ago
I can’t possibly see how this might be relevant given how absurdly vague every job title is in this industry, but it’s “Partner | Private Wealth Manager”.
I only have Reddit on my laptop and plan to be headed out soon, so rather than trying to change topics, I’ll ask again - was there something of note that you had to add? As it stands you’ve only objected but provided no substantive reasoning behind the objection. This sort of thing shouldn’t take multiple comments to articulate - which makes one wonder why you’re stalling/deflecting rather than simply articulating what your disagreement is.
Calm_Situation_1131 | a day ago
Oh I'm not part of whatever argument you are having up above, I just see you name dropping in every post and was wondering what you did.
Which client tier do you specialize in? UHNW, MFO, wirehouse, brokerage, or other?
RIP_Soulja_Slim | a day ago
I mostly operate in the mid tier uhnw space, my specific niche being constructing pension solutions for moderate sized (~10-30 owner) professional corporations, as well as other tax solutions for some members.
Calm_Situation_1131 | a day ago
Oh I'm your target client - 8 figure ex-swe. I have a lot of doctor friends who probably use your services for the cash benefit plans or similar. Although they do get pitched what we joking call "dumb doctor deals" on a too frequent basis. So you charge aum based fee on these plans or flat fee?
realhousewivesofISIS | a day ago
Jtfo at lil bro starting with doubting they profession like he a big swinging dick then turns out bro just listened to a podcast.
Absolutely cackling, yall wild
Cool-Truth211 | 22 hours ago
It’s actually in depth reporting
realhousewivesofISIS | 22 hours ago
Sure Jan
BobaLives01925 | 7 hours ago
First sentence is a great point
big_cock_lach | 18 hours ago
AI sparked it, but it’s not the underlying issue that people were truly concerned about.
Post-GFC, there was a desire to move high risk lending away from the banks to protect the economy from a repeat of the GFC due to a collapse in the banking system caused by incredibly risky assets doing what they do. The solution was to offload this lending onto investors instead, which is what effectively caused PC to take off. The concern with PC is that the fundamental issues still exist, they’ve just been shifted away into less regulated and less liquid providers. People were already having major concerns regarding asset quality leading up to the AI scare (namely due to the same accounting tricks and off book deals used by PE), their illiquid nature making it hard to pull cash out from them, and whether they’d actually serve their purpose when stressed (ie not cause a repeat of the GFC).
The AI scare is just what tipped it over the edge, people were nervous and wanting to sell, but also didn’t want to redeem their positions when it was still generating high returns. The advent of AI then changed the calculus and made them all expect traditional SaaS companies (whether directly or via the PE funds that own them) to start defaulting on their debt (which wasn’t helped by people already questioning the true value of the assets they owned), which led to them all redeeming their positions immediately. That then triggered the concerns regarding illiquidity, which every knew would happen due to the nature of these funds. Suddenly, every concern was more of less ticked off and people were all sitting and waiting to see if they’d actually serve their purpose. It was the first time the PC system was put under real stress since it grew into a larger component of the financial ecosystem. It ended up holding well, but no one knew that at the time. Hence why so many people were watching and why it was being reported so much. The attention/concerns had very little to do with the AI scare, even though that was the trigger that set it off.
Apprehensive-Ad9523 | a day ago
Private equity , Ai debt spending without real revenue, and much higher refinacing of debt plus a return of the "new" rules change for another go at 2006 guarantee a failure of the stock market
Fresh-Quantity-7554 | a day ago
Your global debt numbers are off by an order of magnitude. It was already well over $100 trillion around 2008, not $22T so you're conflating global debt with something much narrower.
The dot com comparison also misses who's allocating capital. 1999 was retail speculators piling into zero revenue vaporware IPOs. Today it's trillion dollar mega caps with real earnings building infrastructure.
I'll give you the financing point, because it's the one part worth taking seriously. Hyperscalers have shifted toward debt and Oracle in particular is running capex at roughly twice its cash flow. So there's a real leverage question for specific issuers. But "some companies are taking on debt" isn't speculative mania, and it definitely isn't "CRE and PE investors will demand AI returns to cover their losses." That's not how portfolio management works. Asset classes are priced on their own earnings, not cross subsidized because a fund's office space is underwater.
And on returns: we're in the build out phase (laying the tracks) and the hardware and cloud providers are posting some of the most tangible revenue growth in the market.
You're doing a lot of motivated reasoning here. You obviously have a conclusion and you're reaching for whatever supports it.
Olangotang | a day ago
The US AI industry is speedrunning government protection and IPO because at the end of the day, there isn't anything special about OpenAI and Anthropic because Transformers are public knowledge and there is no moat. The returns aren't there for businesses and anyone who says they are is in cope mode and in direct contradiction to the studies and data.
HowdyDiarrhea | a day ago
This 1000%. Very accurate description in a nutshell.
Fresh-Quantity-7554 | a day ago
The returns aren't there for software companies because we're still in the build-out phase. Returns are everywhere for hardware companies. Does it make sense to think railroads aren't profitable because they're not showing returns while they're still laying down tracks? Once we get past that phase, then we can start debating about returns. All you're doing is speculating, which is fine.And those studies, while conducted by reputable institutions with rigorous methods, are analyzing the data we have now and projecting possible outcomes. I'm not saying you may be right or wrong.It's way too early to start saying this is all a farce and isn't going to work. We're four years into the next phase of AI technology.
E-commerce for example. Wildly unprofitable and expensive at first. Look where's it at now and how long it took to get here.
Olangotang | a day ago
It's not a farce but the diminishing returns you experience as models scale up are becoming more apparent. The reason why LLMs had such a jump in the past few months is the harness which fixes your input and the output from the LLM, sometimes trying multiple times to get the right format (this is why people are confused they are burning so many tokens). The industry isn't worth the trillion dollar valuation because open source is simply a better format as LLMs are a piss poor product to scale (they cost magnitudes more to run than standard SaaS apps), but a FANTASTIC tool in the right hands.
Also, I am not speculating, these flaws are inherent to Transformer models but sorry for adding Machine Learning experience to an econ forum LMAO.
KevinGreeneSolar | a day ago
You're right, from what I have seen. The open source models are so much cheaper, that their minimal disadvantages in terms of output are easily offset by the costs being orders of magnitude lower. Some (I'm using Qwen on my phone) can run locally on surprisingly low end hardware, while outputting 90-95% of what the highest end models are achieving.
The future of LLMs is open source, and the only people who can't seem to see it are the ones who have sunk hundreds of billions of dollars into building the already obsolete data center size models.
There is no moat, and most of those investments will never return a fraction of what was spent.
Anthropic makes $20 billion compared to Walmart's $800 billion annually, and the two companies are valued the same on the markets. There will be a reckoning.
Olangotang | a day ago
Exactly. The one thing you notice about all of the AI boosters is that they will handwave away all of the flaws of the architecture and the insane costs to train the models. The tech people obsessed with AI are all in a bubble, while those working at F500s and large businesses are pulling their hair out because everything needs to have an AI feature even if it makes no fucking sense. There still isn't a viable use case for the large firms, it's not a good product to sell.
HowdyDiarrhea | a day ago
We're being Elon Musked by the AI giants and it's annoying as fuck, and that's being kind. You just know we're going to have to bail these assholes out. This is why open AI offered the trump admin a stake. I'm personally livid.
Fresh-Quantity-7554 | a day ago
You have enough ML experience to see the gears, but you’re missing the macroeconomic picture. Calling the new agentic wrappers a hack misreads what is actually happening. That "harness" is deliberate inference time scaling. It's shifting AI from fast guessing to slow, self-correcting reasoning. It burns tokens, sure, but paying two dollars in compute to autonomously finish a complex task beats paying a human forty dollars an hour every single day. The market buys outcomes, not token efficiency.
Why are you comparing LLM margins to traditional SaaS? That's a total categorical error. Traditional apps just move data between databases. LLMs sell cognitive labor replacement. A neural network obviously costs more to run than a standard SQL database, but its target market is the global service economy, not traditional software budgets. Even with lower gross margins, capturing a fraction of global labor spend easily justifies a trillion dollar valuation.
Blaming the inherent flaws of transformers assumes the tech is frozen in time. Vanilla architectures are already being phased out for mixture of experts and state space models to engineer away the quadratic cost bottleneck. You’re right that brute-force pre-training is hitting a wall, but you are dead wrong that the engineering solutions devalue the boom. They are the exact reasons it will survive. Nice try though.
Olangotang | a day ago
The tech isn't frozen in time, throwing endless amounts of money into diminishing returns on a chatbot duct taped onto a language translation model is what will end. this is why Apple is staying an arms length away. OpenAI and Anthropic do not have a business model at their scale.
I like AI, the community creates fantastic tools and discoveries new cool shit every day. I'm against the tech bros scamming a government run and IPO.
Fresh-Quantity-7554 | a day ago
Again, you're only focusing on chat bots to back into your argument. I don't know why you neglect to account for the whole pie. It doesn't sound like you're willing to reach beyond that so we'll never see eye-to-eye. It sounds like you are suffering from developer myopia.
Apple does not step into spaces it knows it can't be first or second. If they thought they could be first or second, they would have jumped in. They also have zero exposure to enterprise which is where all the money is. Apple staying away from this is a very Apple-thing to do. That's why they don't screw around with search despite having the most dominant phone brand on the planet.
Anthropic does have a business model. Based on the reporting we have right now, they had their first quarterly profit in May and expect to turn their first full year profit around 2028. Additionally, they're sales revenue is growing faster than Zoom during the pandemic, and Google and Facebook in the run-up to their IPO. They're actually doing it right by not going overboard. OpenAI is a different story because we don't really have any hard data on their financials. I'm not going to speculate on their financials.
Olangotang | a day ago
> they had their first quarterly profit in May
Because they were given compute resources by xAI for a few months, and were seen as "the good guys" while the govt was attacking them. I don't know why it's so hard for y'all to comprehend how ridiculously unprofitable these companies are, and that their product in a corporate environment is not very good. It's given shitty developers the ability to look like they are actually doing work, instead of building mountains of tech debt because of the fatigue within corporations to push at 10x.
Fresh-Quantity-7554 | a day ago
>It's given shitty developers the ability to look like they are actually doing work...
How do you make a confession without making a confession? Thanks for the layup.
RIP_Soulja_Slim | a day ago
> It was already well over $100 trillion around 2008, not $22T so you're conflating global debt with something much narrower.
I had the same gripe and decided to just leave it be, but I think they meant to write 220 trillion.
Still, global debt hasn’t really grown much faster than GDP. The figures are all over the place as some use private and some only sovereign, but overall the increase in global debt/gdp has been fairly modest across the last ~20 years. It’s happened for sure, but not some crazy surge like OP suggested.
Butane9000 | a day ago
I believe I'm referencing global sovereign debt (held by nation states) not total debt which is why it's so much lower which is my mistake.
RIP_Soulja_Slim | a day ago
It wouldn’t have been 22T in any capacity, I think ~220 is about the right figure for the timeframe you’re referencing.
But yeah, there’s no direct official stat on this so you’ve got to sorta peace meal it, and doing that leads you to different people using different composition at different times.
gimpwiz | a day ago
https://www.investopedia.com/us-national-debt-by-year-7499291
In '08 the US national debt stood at around 10T, and it doesn't really pass the sniff test to me that in '08 the USA alone accounted for ~half the total national debt of every country combined.
CallMePyro | 10 hours ago
This reads like Claude :) either Opus or Fable but my money is on Fable.
Fresh-Quantity-7554 | 10 hours ago
Spoken exactly like someone who has absolutely nothing of value to contribute.
CallMePyro | 6 hours ago
Whoa, haha. Yeesh!
Observations of non-apparent equivalences are not adding nothing to a conversation. Good day!
Fresh-Quantity-7554 | 5 hours ago
If you're going to do a hit and run on Reddit, at least make it a good one.
big_cock_lach | 18 hours ago
That’s difference is largely due to economic growth. You’re better off looking at debt to GDP, which back then was $4.7tn in today’s money and is currently $121tn. We’re not quite 3x now, but back then we were around 5x. Still concerning, but it’s not worse than it was then, let alone much worse like you’re perhaps accidentally implying.
oregon_coastal | a day ago
We are basically watching a new .com bubble - assuming this LLM method actually pays off. Most of these early movers will get buried in debt trying to take the lead. But as all the first/second generation attempts face plant, later companies learning the lessons and not overly leveraging themselves will take the reigns down the road.
Pets.com failed in 2000 - but today we have Chewy. In 2000 we had Kozmo that failed - now we have like 20 instant delivery services.
I think the smart players are carefully in the game now and waiting to push hard until profitable models and pathways become apparent. The overly leveraged first movers will mostly fall away.
There is always a success or two with early players (Google, etc in dot com bubble) - but many won't make the cut. Gonna be a crazy next 15 or 20 years and I wish I cpuld see how it plays out.
agumonkey | 14 hours ago
LLMs are helping, sometimes a lot, but in weird ways (that might backfire later). My worry is more that if will destroy the job market because HR and CEOs will stop hiring toi early.
wathappen | a day ago
What? Do you realize the companies behind LLM already make billions of dollars in revenue? Do you understand that LLMs is already used extensively by all f500 companies?
People disagree on the VALUATION of AI to the economy and in particular the FUTURE value of AI but there is absolutely no doubt that this is already a multinbillion dollars business in 2026.
It’s nothing like .com bubble.
Traum77 | a day ago
Revenue is not profit. And they have signed up to pay for literally hundreds of billions of compute power they will need to magically make profitable.
LLMs are here to stay. Companies like OpenAI and Anthropic are probably not. At least not in their current form.
beached89 | a day ago
I wouldnt bet against Anthropic, they are so far ahead of the competition that if any one company could quadruple their price and still retain customers, it very well could be them and them alone.
So very few companies open their books (If any) but I would be willing to bet a HUGE portion of the expenses are capex expenses to continue the arms race of staying ahead. (Training new models)
Older already trained models could very well already be profitable. Anthropic likely could just stop training their new models, or dramatically slow the pace, and milk Opus, Fabel, and Mythos for at the very least revenue neutral.
While I agree that a LARGE majority of AI companies are doomed, Anthropic specifically, I am betting will be one that survives the culling and comes out on top.
Google seems to have been investing a lot of time in effort in making training more efficient. They announced earlier this year a new algorithm to optimize RAM use in model training. I would hope all the major players are looking for similar efficiencies to reduce their hardware expense.
I do think there is one major difference between what we see with AI today, and the dot com bubble. People and companies thought the dotcombubble was the new norm brought about by this great new tech revolution, and that it was there to stay. Im very certain AI companies know they are on borrowed time, they say it all the time.
wathappen | a day ago
Lol they are purposely unprofitable because a) investment costs upfront are huge b) they are fighting for a market share. This is the same playbook every single tech company has played in the last 30 yrs.
You think LLMs are here to stay but the two leaders in the field are somehow going to fold? Yea, don’t bet on it.
oregon_coastal | a day ago
That is exactly what the dot com companies were saying.
And yes, Google and Amazon got through it. Amazon was particularly unprofitable. But they also pivoted and tried a whole different approach to other retail companies online by building their own logistics system.
Oracle is taking out bonds so fast right now if there is an AI hiccup their junk rating will be the stuff of legends.
The AI bubble is not just the out front LLM guys. It is also everyone behind them hoping this architecture works ar the scale they are hoping it will.
Stinkycheese8001 | a day ago
It’s really weird to see them try to make that point like it’s a gotcha.
Olangotang | a day ago
Because the people hyping LLMs are in full cope mode that corporations aren't seeing a return for their investments into AI. the token based pricing change was a wake up call, now the hype idiots and bots need to double down to defend the sunk cost fallacy.
wathappen | a day ago
The .com companies did not even generate revenue. There were few customers and little demand. Pets generated something like 100m in sales their last year before the crash.
BroughtBagLunchSmart | a day ago
Yea but people need dog food. No one needs a white supremacist chatbot that can add big honkin double Ds to a picture of the muppet babies.
big_cock_lach | 17 hours ago
I would not be surprised if OpenAI loses out, but Anthropic is the one AI company I would be surprised to see die off (doesn’t mean it’s not overvalued). They are already profitable and finding many ways to provide genuine value as well. The rest are focusing on building better LLMs, and while Anthropic is still doing this, they are more focused on making the models actually useful. It’s why enterprises and individuals are willing to pay them a lot of money to use their services, but not other AI providers, which is ultimately how they are profitable.
Microsoft and Google is also tackling it from a smarter position too, instead of focusing on building an LLM at all, they’re leveraging OpenAI’s and Anthropic’s models to add more value to their existing products. Companies that are focusing on using LLMs to add value are likely going to end up in a strong position, and Anthropic is currently not only leading that race, but they also have a lot influence over every other company doing this. Then there’s Amazon, Nvidia’s, and SpaceX’s strategy which is focused more on the infrastructure side of it (something Google is also involved heavily in), and effectively being the ones selling the shovels to the gold miners. They’ll make a lot of money off of this in the short term, but eventually this will die down. They won’t disappear, but they are likely at their peak already.
The bigger concern for Anthropic is how healthy they are when they come out of this. They will likely come out with a lot of debt, and that will significantly hamper any further development that they can do. Depending on how big their advantage is, you may find another company can somewhat easily rebuild their technology without all of the debt by leveraging Amazon’s and Google’s data centres. If they can get to a roughly similar level without the debt, that better financial position will lead to them quickly overtaking Anthropic in the future. It all depends on a) how easily replicable Anthropic’s technology is, b) how much debt Anthropic ends up taking on, c) how profitable they end up being once the development race cools down, and d) how much development costs come down. These things can go either way and will likely decide Anthropic’s future.
kylogram | a day ago
Ai isn't making money. We can disagree on valuation all day, but the fact of the matter is that AI costs more to run than it can charge to make up that difference. It's already bankrupt, and all but the smartest players have poured terminally critical amounts of money into it.
These companies can't cut their losses without losing their businesses, and they can't get that money back without going for broke. The ai market is failing, and the only way to survive the crash is to hope and cope.
RIP_Soulja_Slim | a day ago
AI may or may not fail, who knows, it kinda really doesn’t matter. Anthropic and OpenAI are just IP shells being funded by big tech, so all the actual financial burden goes on big tech, right?
AI infrastructure spending last year was ~320B, this year it’s anticipated to be ~480B. That sounds like a lot of money.
Facebook, Google, Amazon, and Microsoft have combined cash on hand of ~550 billion, and combined annual operating cash flows of 430 billion. That’s a trillion dollars of literal just cash spending power across one year. Moving forward, that operating cashflows is another half trillion dollars every year.
If AI has massive returns over time then fantastic, all of these companies will be rolling in cash, if AI ends up being equivalent to lighting cash on fire then congratulations, all of these companies will still be rolling in cash.
Everyone looks at the liability side, everyone seems to be ignoring the balance sheet and cashflows.
Diablos_lawyer | a day ago
I've learned to respect your takes so I'm curious what yours is on how they get profitable?
Yes they're burning money to try and get the infrastructure in place and what not and they can afford to do so with the money they make elsewhere in their businesses. However, from my understanding every new model they create becomes more expensive to run than the last one, not less. Requiring ever larger and newer data centers, (3-5 year life span from what I've been told) Even now the current models are too expensive to offload the true cost onto the consumers so the AI companies are running at a loss. The new models are not going to be cheaper, they're going to be more expensive, so where is the consumer going to get the money to pay for the even more expensive model that may eventually deliver on the productivity promises that so far with the insane spend and drive to utilize it have failed to deliver?
Unless your idea is that they just permanently subsidize AI in perpetuity they need to figure out a way to make money with it or the spending bubble holding up the industry will pop. Every person outside of the AI space, business leader or not, that I've talked to about it's productivity promises says it's just not delivering.
I was using Chatgpt for work and I've been burnt a couple times by hallucinations, even when I gave it a document to pull it's info from it still got it wrong. I've cancelled my subscription because I have to double check everything it gives me anyway.
So I think when people are describing it as a bubble they're not strictly speaking of a debt bubble to pop, although that's still possible for some of the companies in the space, what I think they're talking about is the spending relative to return on investment bubble that will pop. AI spend doesn't increase productivity at even a 1:1 ratio.
For every dollar spent on AI build out we're not seeing a dollar in increased productivity and I don't see a path for that to change. We have a mountain of shovels for a gold rush that doesn't exist.
RIP_Soulja_Slim | a day ago
Yeah, I mean to be honest I’m not sold on the idea that AI will be some massive return on investment for these guys, it might turn out that a lot of them ended up burning through a lot of cash for what amounts to some pretty mediocre ROI.
I’ll be honest, I don’t know enough about the tech progression of AI to have good input on what those costs would look like over time. I’ve heard from some authorities in that world whom I respect that the costs should subside as models are fully trained, but I’ve also heard the opposite, I think it’s a lot of guesswork tbh. I also think a lot of the very confident people commenting on where those costs will trend are presenting speculation as expertise (even those in that industry).
I doubt it’s permanent subsidy, but it’s quite possible that you end up with a few big winners, and a company or two that’s burned through half a trillion dollars with not a lot to show for it, those companies will be fine, but certainly not very happy about burning through said cash for nothing.
As far as AI and it’s workplace uses, it’s a mixed bag, part of the reason why tech bros are so enamored with AI is because it’s like genuinely very very good at doing their job. Its coding ability is fantastic, Claude can build you a whole website in a short period of time with very little necessary in terms of revisions - so tech bros see a model doing the thing that made them in to a billionaire with ease and (incorrectly) assume this model can do all sorts of highly intelligent work. But at the same time, asking Claude to schedule a dinner with two coworkers has it flailing wildly, it can’t fill a fucking PDF, and it’s about as good at researching a given topic as an unpaid intern.
And to your point, the hallucinations are never really going to go away, they can’t, hallucinations are inherently part of how AI works. This is a really really dumbed down summary, but all it’s doing is being a big statistical word generation engine. That inherently has hallucinations, it can’t not.
I think the future use cases for AI will be heavy in tech, but also heavy in replacing the sort of mindless busy work that everyone hates - data entry, transposing info from place A to place B, summarization and analysis of specific documents, automation of task generation, etc. That’s valuable, but it’s not going to render humans obsolete or anything.
Between here and there a lot of companies are certainly gonna waste money on AI, either through investment or through tokens that don’t result in increased productivity, but all of that doesn’t really need to amount to crash type dynamics. It’s buying the expensive car you don’t need, not mortgaging your house for a business that fails.
dyslexda | a day ago
> And to your point, the hallucinations are never really going to go away, they can’t, hallucinations are inherently part of how AI works.
Minor quibble, but this is inherently part of how generative AI works. One of the great casualties of the recent boom is conflating AI, which we've had in various forms for many years and does great work in many domains, with LLMs.
big_cock_lach | 17 hours ago
It’s not just generative AI. Hallucinations are caused by non-determinism which isn’t an uncommon feature in neural networks. There are a lot of AI models that are deterministic and won’t hallucinate though, just like there’s plenty that are.
gimpwiz | a day ago
> Its coding ability is fantastic, Claude can build you a whole website in a short period of time with very little necessary in terms of revisions
It's very good at filling in the blanks in a way that plausibly seems to work, and if you know what you're doing you can have it iterate until it even passes tests, and if your tests are any good you may just ship adequate products. What it is terrible at doing is architecting good solutions and generating an efficient, reasonably readable amount of code. Someone who really understands architecture and trade-offs and knows where they're trying to go - someone experienced - can use these tools very well. Newbies can't use them for shit in any practical way once a project grows above "tiny" because they don't know how and they can't audit the results, and if it plausibly works they just move along, leaving behind something entirely unmaintainable. The real magic is not vendor lock-in per se but tool-class lock-in; the only feasible way to maintain LLM-written codebases of any size is to keep paying for LLM tokens. And like you said, a lot of companies are going to waste enormous sums of money finding this out the hard way.
I generally expect the explosion of LLM usage to be like the explosion of computer usage: Some jobs go away due to being too easy to automate; the automation means a lot of tasks become affordable enough that new industries are suddenly feasible, and they staff up. A lot of churn, but overall I suspect it's not going to cut white-collar employment in general.
Stinkycheese8001 | a day ago
This is the take that most aligns with what I’ve seen and read as well. In general it’s a weird discussion to try to have - either someone is convinced it’s a total sham and the market is going to crash to a point of people jumping out of buildings, OR AI is the most amazing thing that can do literally every single job and we humans will soon be obsolete. When the answer lies somewhere in the middle.
RIP_Soulja_Slim | a day ago
In general with most things the answer lies somewhere in the middle, unfortunately as forums grow there tends to be a decline in technicality and an increase in binary thinking - so more and more topics are boiled down to the extreme binary, and most participants interpret any discussion of that vast middle ground to be someone taking the opposing end of the binary.
C’est la vie.
HowdyDiarrhea | a day ago
LLMs are definitely useful, but we're now at the point where there are literally 10s of thousands of open source models out there that can be implemented on varying levels of hardware, depending on your needs, very easily and cheaply.
Nvidia is already building enterprise hardware (machines that cost in excess of $100k) that companies can use to drive internal LLMs at scale, using whatever model.
As hardware continues to be oriented towards and optimized for LLMs, I think you're going to see them prevalent as plugins and tools for specific use cases. They'll be ubiquitous and cheap, and there will be no need for the likes of the companies that first brought these to market.
I'm a bit fuzzy on specifics of how we got here, but my understanding is that LLMs were reverse engineered, and as a result, they're basically a dime a dozen at this point. On the open source models, you see near parity at the higher end of things as compared to what the LLM companies offer.
Remember the panic when DeepSeek first arrived on the scene? That's the direction things have been rapidly heading.
The next big innovation in this space is going to be automation, where you can give an LLM instructions and it just does whatever you ask autonomously. This already exists, but it's not widespread or without many hurdles.
I've been tooling around in the open source space. When I first understood exactly what these things are, what they do, how they work, and how they use resources, my sentiment shifted very negatively - at least towards the specific hype from the sector.
I agree with what you said about usefulness in certain areas, like programming. I don't think this translates to the value they're trying to sell the public. In case it needs to be said, this stuff isn't actually AI, and it never will be. This is why I was careful to only use the term LLM. We're dealing with what is the equivalent of a very sophisticated, internet enabled T9 model, which was the genesis of the LLM, ironically (or perhaps not).
Diablos_lawyer | a day ago
So basically your saying that even if it is a bubble (debt not involved) and they're never going to get anything close to an ROI of 1:1 that it's fine economically if these companies spend an insane amount of money on it and get nothing back?
Like yes I understand that AI isn't going anywhere and I'm grateful I don't have to spend an extra 5 minutes formatting my spreadsheet and emails (it's not even worth it for that with what it costs now but I whatever), but how does pouring a trillion dollars into something that doesn't work, mean it's not a bubble, and when the real value / cost becomes apparent there will be no negative economic effects downstream?
I understand that the global financial crisis of 2008 was bad because it hit banks and banks are a pillar of the economy but in this case because it'll only affect the balance sheets of the AI companies it doesn't matter? Is that your position?
Olangotang | a day ago
Profitability of the models isn't a fully economic issue, but a Machine Learning one as well. Models get prohibitively (EXPONENTIALLY) more expensive to train as you increase the parameter count, this is a trait of all Transformer models, including LLMs. Those who are tunnel vision econ brained don't understand this, so the industry has been able to bait crypto / block chain idiots into a brainless cult, over a technology they don't understand.
Essentially, the money furnace is going to shovel more and more dollars into it to the tune of multibillions per model, and China will continue to devalue the ketamine coke heads in the Valley.
big_cock_lach | 17 hours ago
It’s always funny seeing SWEs and CSs “correcting” economists on their economic insights on the basis of them not understanding technology, all while demonstrating that SWEs and CSs don’t understand economics. A lot of SMEs need to learn to stay in their field (a common problem for expects in every field), just because you’re an expert in 1 field doesn’t mean you’re an expert in every other field.
AI/ML/statistics, the internet, software, computers, etc aren’t the only technology that exists or was developed by people. They’re also not the only technology that gets exponentially more expensive to develop either. In fact, nearly everything becomes exponentially more expensive to develop. It’s not a unique issue with AI, and it’s certainly not a new issue faced by economists either. The result, from an economic standpoint, is always the same. There is an equilibrium point between how much you spend vs how much you get in return. As the costs become exponentially more expensive, eventually every $1 you spend generates under $1. With new technology, it takes firms some time to find this equilibrium point, and those who overshoot it will make a loss. But it will eventually be discovered and firms will not spend beyond that because it’s economically prohibitive to do so. The initial development costs are also always the most expensive, eventually development (and hence spending) will slow down as a result of this nature. This is all well understood, and ML isn’t any different. Yes, it gets exponentially more expensive to improve, but they won’t spend beyond what’s economically feasible.
Also, it’s very easy to underestimate how much economists actually understand this technology. Not only do they have a very strong understanding of how technology in general impacts the economy, but ML is one technology that they have a particularly good understanding of. If you’re talking about the internet or software, most would have 0 clue about the actual technology. However, economists have been using ML for decades, and are one of the fields that have significantly contributed to its development. There is a whole field of economics, econometrics, that has specifically been looking at the intersect of ML and economics for decades. Most major economists have studied econometrics to some extent, and every economists is not only aware of it, but will rely on it for their insights. They mightn’t have as strong of an understanding as mathematicians, physicists, data scientists, etc but they do still have a good understanding of it. More so than any other technology. Your argument still wouldn’t apply to a technology they’re clueless about such as software, it still follows the same rules as any other technology. However, it’s particularly naive to criticise them for not understanding this technology because it is one that they have a strong understanding of.
Mental-At-ThirtyFive | a day ago
imho, there is only 2 near term threats - rise of alternate algorithms that are not heavy on compute/memory, chinese or any open weights models that corporates are willing to bring to private cloud.
Having exposure for my retirement - this cash level you mention above and revenue (aka token annuity) is what I need to pay attention. Maybe Q1 '27 is something to plan for
belovedkid | a day ago
Pets also wasn’t the cause of the dot com collapse. It was overbuilding of infrastructure (fiber, bandwidth, etc) which led to a price collapse on those services (no profit to be made) which caused the whole thing to implode. They missed the entire plot.
Otakeb | a day ago
/u/RemindMeBot 5 years
RemindMeBot | a day ago
I will be messaging you in 5 years on 2031-07-17 19:11:34 UTC to remind you of this link
CLICK THIS LINK to send a PM to also be reminded and to reduce spam.
^(Parent commenter can ) ^(delete this message to hide from others.)
|^(Info)|^(Custom)|^(Your Reminders)|^(Feedback)| |-|-|-|-|
RIP_Soulja_Slim | a day ago
The problem is most of the people on this site are nearly financially illiterate - so they translate their sentiment regarding AI’s viability as a product directly to their understanding of financial outcomes, and that’s just a bad take.
All of this whole “dotcom bubble 2.0” stuff comes from people unable to read a balance sheet. If all of the collective debt accumulated by these major tech firms comes due tomorrow with precisely zero corresponding revenue attached not a single one of them would flinch.
Here’s a quick example, Microsoft, who has been positively burning through cash on AI commitments, has spent ~80B in 2025 on AI build outs, much of that actually being future capex commitments and not immediate spending. They currently have 78B of cash on hand. Their annualized FCF (after AI spending) over the last 12 months was 72B.
Presuming their AI spending has an ROI of 0%, they will at worst just not raise dividends for a few years.
Amazon has the largest capex on AI of anyone, currently at around ~200B. (Forward commitments). Amazon currently has ~143B of cash on hand, and has operating cashflows of 148B/yr.
You can do this same excercise for all of the other big players here - Meta, Alphabet, Oracle, whomever.
All of the sentiment you see on Reddit is easily proven naive by simply referencing two figures for each company - operating cashflows and cash on hand.
Imagine a guy who makes a million dollars a year spending 200k/yr on hookers and blow. Waste of money? Maybe. Will they go bankrupt? lol be serious.
dravik | a day ago
Those big players are in good shape, but also aren't at the forefront of LLMs.
Anthropic, openAI, and the other market leaders are the ones Reddit is discussing.
RIP_Soulja_Slim | a day ago
But that’s where the money is coming from. Look at Anthropic’s funding partners, they’re in series H now (which is hilarious), and the list is basically major cash flush PE like Altimeter and Sequoia or Amazon, Microsoft, Google, NVIDIA.
Same with Open AI, Microsoft is the largest single backer, with SoftBank, amazon, etc behind that.
Sure, they’re the names, but the cash flow backing is the balance sheets of these big tech companies that are just printing cash left and right.
If you look at the actual data center buildouts, it’s almost always something like a holding entity that borrows 50B to build a data center, that data center is leased by Meta, and Meta is going to lease that computing power to Anthropic, Meta signs something like a 50 year lease covering the costs plus their exit agreement guarantees full buy out of any financial losses should Meta exit the lease early - so basically it’s Meta’s liability, and backed by their balance sheet and FCF.
The problem with these conversations on Reddit is that people are unable to differentiate their sentiment towards the success of AI as a product set and their understanding of financial risk. AI may prove to be completely useless, who knows, the balance sheet risk here is still minimal with almost all exposure matched by current cash on hand or at worst cash on hand + one year of FCF.
For most of these build outs it’s something like a company with 100B of cash and 100B of FCF committing 200b across a decade moving forward. Waste of money? Time will tell. Dotcom bubble? Be serious lol.
oldsmoBuick67 | a day ago
Great insight btw, based on what you’re saying would they be able to keep spending on AI infrastructure regardless of whether demand for the compute power ever materializes? The reasoning being the financials being undergirded by things unaffected by AI demand and not just a circlejerk of Nvidia being cash flush from the demand and cash injecting to keep the music playing.
RIP_Soulja_Slim | a day ago
> based on what you’re saying would they be able to keep spending on AI infrastructure regardless of whether demand for the compute power ever materializes?
As in do they have the financial capacity to do so? Yes.
Microsoft, Amazon, Facebook, and Google combined have operating cashflows of 556 billion dollars. Combined they have current cash on hand of 430 billion dollars. That’s effectively a trillion dollars of cash available across the next 12 months, then another half trillion every year after that.
In 2025 global AI infrastructure spending was something like 318B.
Now Oracle is having it’s own problems, as mentioned in the article and as observed in their financial statements, they’re still very stable but generally betting a lot trying to keep up.
But yeah, is it a good business move? IDK, time will tell but ultimately I’m not super confident that this will be a great ROI. But low ROI is leagues away from dotcom bubble territory. Everyone in this sub seems to be just intentionally ignoring the massive financial strength in tech right now.
Basically, this isn’t your neighbor drowning in credit card debt that they can never pay back, it’s your wealthy neighbor buying a Porsche that might sit in their garage and never get used, but won’t stop them from having the biggest Christmas party every year moving forward anyway.
oldsmoBuick67 | a day ago
In other words, there’s no actual bubble to pop but it gives commentators something to talk about.
Thanks!
RIP_Soulja_Slim | a day ago
Basically yes - almost everyone who is ranting about a bubble is only looking at liabilities and revenue for the AI companies directly, they’re not looking at where those liabilities sit and what cashflows back them.
Might it be a gigantic waste of money? Sure. But people need to decouple their thoughts around the viability of AI from their understanding of big tech’s ability to literally just light cash on fire and be fine.
Basically, if you see someone on here talking about AI bubbles or whatever and their post has zero mention of cashflows, cash on hand, etc then it’s very safe to assume they don’t really know what they’re talking about. Can’t discuss liabilities and ignore assets and income.
DarkSkyKnight | a day ago
Like he says at the end, some will fall and some will continue, and it’s impossible to predict who will continue at this point. But I sincerely hope the government does not bail any of the failing companies out. I know it’s not too likely at this point, but it is extremely concerning if Trump is going to bail Oracle out.
I fundamentally don’t think companies should ever be bailed out by the government. We need to let the natural selection of firms work. Poor management should lead to the demise of those firms.
MagicWishMonkey | a day ago
How often do government bailouts happen? Has it been a thing outside of the 2008 crash?
axiak | a day ago
Didn't the US invest in Intel to give it capital?
MagicWishMonkey | a day ago
Oh yea, that was definitely odd, but was it a bailout?
I would not put it past Trump to try and give Ellison billions of taxpayer dollars, but I don't think the government (when Trump isn't at the wheel) does the bailout thing all that often.
makemeking706 | a day ago
Yes, but I wonder what isn't running on borrowed money these days. Social security? What else? That's probably why they want to plunder it so badly.
MajesticBread9147 | a day ago
Future money is always cheaper than present money.
Google has a return on invested capital of 28%, whereas they pay bondholders 5-6%.
They'd be stupid not to be using debt.
Tiny-Pomegranate7662 | a day ago
The more present money you take, the more future money you better make. That's the crux of AIs problem is not that it's not nifty, it's that the scope of future expected profits are so massive. The bigger the market share, the more variables and ways it can go wrong.
BallsInmyWalls | 23 hours ago
AGI if achieved is going to end the world as we know it, though the likelihood of that is unknown.
SardScroll | a day ago
Social security is and always has been running on borrowed money. Current workers pay for current retirees.
But I agree with you on the general point, just that the counter example is bad.
Rock-n-RollingStart | a day ago
Social Security is absolutely running on borrowed money. The payroll taxes that fund it directly can't cover the benefits we're paying out, which is why the Social Security trust funds are being rapidly depleted.
Those trust funds bought into US Treasury bonds back when there was a payroll tax surplus, and the Treasury pays out on those bonds by selling even more bonds.
The fact of the matter is that this is not a problem we can solve without the middle class sacrificing a whole lot of their purchasing power. Social Security is funded by payroll taxes, not income taxes. You can raise the wage cap to help stave off the inevitable, which will directly impact highly paid, upper-middle class professionals like doctors and lawyers and engineers, but it will not "fix" the system. We have an increasing number of beneficiaries, and a dwindling number of wage-based workers to support them. We will have to raise payroll taxes across the board to avoid insolvency, and that's a tough pill for Jack and Jane Mainstreet to swallow.
Richandler | a day ago
All money is borrowed money. This has been well understood for a long time in history. Of course forgotten, remembered, and attacked, but it has been known.
namafire | a day ago
This needs to be the top comment. Anything else without this nuance is just anti ai circle jerking
CyberSmith31337 | a day ago
There is a reason that all of the biggest players are trying to IPO at the same time. They haven’t found a path to profitability. Ed Zitron, David Gerard, Eli the Tech Guy, and many other tech centric folks have been echoing this for over 2 years. They are out of VC money, and the banks are not willing to cut them any more lines of credit. Even SoftBank couldn’t get additional loans to cover OpenAI’s attempted IPO valuation.
Now they are doing what tech always does when they realize they have a dud; they are dumping their failed investments onto retail investors, packaging up their mistakes as ”opportunities” and using the public as exit liquidity.
Tiny-Pomegranate7662 | a day ago
Ed's point that I thought was salient is that tech has no plan B. If they did, there would be something in the hopper besides AI. Because no one has any other good ideas, they are all chasing the same rabbit. Metaverse, Apple glasses, self driving, yada yada, they really don't have any true game changers that can actually function.
This is fine! The problem is that techs mode of operations is that they always exponential grow and scale. If the product is good, exponential is a money printer. If the product is not, it's very very destructive.
At some point everything that was tech turns into legacy. John Deere and Railroads and Radio used to be tech and then they transitioned out.
obsequiousaardvark | a day ago
You have to understand that a lot of these tech moguls truly believe that the only "future" we have is to build a perfect AI robot species to replace us, since we cannot functionally explore space in our fleshy pink bodies evolved to be suited on earth's environment.
So they literally do not care how much they destroy now to achieve this AGI that will take over the world. They think that this is the only future possible, the only future that matters, and they will kill billions to make it come to fruition.
They are in a cult. The only cult worse than believing that you know god is this AI cult where they think they can build a god from scratch. That's the ultimate act of hubris a human can commit.
Anyway look into TESCREALism and in particular Peter Theil and why he doesn't think it matters if humans go extinct, be he plans on replacing us all anyway. They want to dictate where our future is headed and that's why they don't have another plan in the wings. They're all in on this gamble because they truly believe they already know what's best for the future of humanity. It's part of why they want the US to collapse so they can buy it up and run "Network States." Look up Network States too while you're looking up TESCREAL.
CyberSmith31337 | a day ago
I think something else that is worth pointing out is that technology went from solving problems to fabricating their solutions.
NFTs were supposed to solve digital ownership; they didn’t. AI is supposed to be cutting employee costs; it doesn’t, and in fact, it is more expensive as token prices rise. WeWork was supposed to solve expensive commercial real estate, AirBnB was supposed to solve overpriced hotels, Cryptocurrency was supposed to replace banking, etc etc. All of these things promise the world, but over time, just actually become shittier, less viable versions of existing systems.
And so to piggyback off your point about ”No plan B”, I think it is less that there are no interesting problems to solve, and more that tech is no longer interested in solving problems. Instead, it has become entirely about how to make as much money as possible only, regardless of outcome and with the least liability. There are so, so many problems worth solving; tech just has no interest in doing so.
gimpwiz | a day ago
WeWork was in no way technology, it was just real estate with a fancy website. The absolute brilliance of the guy was he managed to fool a bunch of people into thinking they would get tech-company returns investing in shared office real estate.
And there's nothing wrong with shared office space, tons of small businesses rent shared office space. They don't need or want to lease a larger space, they want like 3 offices and a combo printer copier fax machine that usually works. Making that process simpler and more standardized is totally reasonable, and solves a problem, but the hype surrounding wework solves no problems other than the relative poverty of a founder and maybe a few execs.
gimpwiz | a day ago
"Plan B" is ... keep iterating and getting incremental improvements, while working on various ideas that may or may not pay off. For some that means iterating by adding more ads and trackers into web traffic, for others it means making new products that are somewhat better than old products. None of that would stop if these bets don't pan out, except the ones who wasted all their money and ruined their engineering culture.
agumonkey | 14 hours ago
Sounds highly plausible. SpaceX is already back to earth prices...
EmptyRedData | a day ago
The opinions of these guys aren't good indicators.
These people are extremely confident but will never show you their puts or LEAPs against the companies they say will absolutely fail.
CyberSmith31337 | a day ago
That doesn’t make any sense.
We shouldn’t take people’s opinions seriously because they aren’t willing to lose money betting against billion dollar movements, backed by the banks, the government, the oligarchs, and Wall Street? What kind of hare-brained take is that? They are 3 ordinary people speaking out against the media machine that is serving as a megaphone for the very oligarchs that have a vested interest in their message being believed.
I guess we just shouldn’t listen to people unless they are wealthy.
EmptyRedData | a day ago
These people are grifters. I don't believe they are genuine and I am using their unwillingness to put their money where their mouth is as an example. And I am not saying they ought to bet large sums of money. I'm sure Ed makes quite a lot of money on his blog and speaking gigs, so him putting up a public $1,000 bet would show that he's serious.
They'll tell their audiences that these AI companies are collapsing imminently. They make grandiose claims about how Anthropic and OpenAI are doomed. They also maintain that AI isn't improving over these past few years, but newer models continue to prove them wrong. Not that they will ever acknowledge this in any way.
Ed Zitron claimed the bubble would burst in 2025. He has updated his call to be "no later than Q3 2026" https://www.geekwire.com/2025/ai-bubble-enshittification/
We'll see if he's right for a 5th time in a row that he's tried to call this.
You sound like some conspiracy brained MAGA person with all this talk. They're not brave for speaking out against AI and tech. These things are already deeply unpopular. AI is less popular than ICE if you can believe it: https://www.nbcnews.com/politics/politics-news/poll-majority-voters-say-risks-ai-outweigh-benefits-rcna262196
Edit: Blocked for this, but you'll notice he never responded to any of the claims.
CyberSmith31337 | a day ago
It always cracks me up when someone makes a bad point, and then just immediately turns to ad-hominem and MAGA accusations. Just blocking your stupid ass; not worth engaging with bad faith comments.
KevinGreeneSolar | a day ago
You resorted to ad hominem argument and got blocked, and you're salty about it.
Sounds like you have trouble taking responsibility for your own actions.
Your argument was better before you resorted to insults and betrayed your deep insecurity.
EmptyRedData | a day ago
Do you have anything to add or just here for the dog pile?
Olangotang | a day ago
Is it getting tiring watching people wake up to the bullshit that Altman and Dario are pulling? Everyone including you clowns are noticing the money warnings start to pile up. If you really need to jerk off to an LLM, the smaller local models are free and don't put a multibillion dollar hole in the economy.
EmptyRedData | a day ago
What bullshit are you referring to in regards to Altman and Dario?
Synchwave1 | a day ago
The entire world runs on borrowed money. Since the 1600’s and the rise of central banking, the world has leveraged itself for exponential growth. From 5000 bc to the 1600’s our world advanced, but slowly.
The exponential arc of advancement in the last 500 years has only been made possible through debt financing and fractional reserve lending. The fact people don’t tie those two things together is pretty crazy to me. Our world requires debt. It’s not the boogeyman. It’s necessary to leverage for advancement. Historically, our growth has exceeded our debt. That’s the idea.
Overall_Signal_8437 | a day ago
Yes, but normally you go through a rigorous process with the banks to buy a house, etc. And you borrow against your future income.
In this case...... a helluva lot of money have been thrown into a pit with some sort of prospect there will be great income at some point.... an income that will never come.
And now we're being forced by companies/financial institutions to use it, in a way to save the card house....
Simple as that.
spaghettiking216 | a day ago
That’s not the point of the article. The article is pointing out the unique role debt is playing in the current AI investment cycle, particularly the way it is becoming central to firms that historically have financed their CapEx with cash flow or equity and the larger risks this poses to the economy. And as the article gestures, AI revenue growth is not keeping pacing with spending growth. It’s not even close. The hyperscalers and AI labs are losing money with AI.
Synchwave1 | a day ago
I’ll repeat what I said, it’s a conversation of relativity. Big today doesn’t have to equal big 25 years from now.
Same cycle repeated over and over again. The only difference is the relative scale.
[OP] rollem | a day ago
If you read the article beyond the headline you’ll likely see that there are levels of debt that are low risk and that enable rapid growth as well as levels of much riskier debt that are more likely to lead to financial crises.
Synchwave1 | a day ago
That’s a conversation of relativity. The debt spending of the 90’s and early 2000’s led to crash and financial crisis, but 25 years later that technology has completely transformed the world we live in.
Zoom out and you’ll see from a large scale macro perspective this is exactly as it’s designed to happen.
nik-nak333 | a day ago
When this bubble does pop, we'll see consolidation in the AI space to only a couple of major players who manage to scoop up as much AI tech and R&D as they can. THAT is when we will see AI truly start to displace human workers, once its scalable at cost.